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TitlePub. DateDuration
From $0 to $165M: How Harsh Patel Built and Sold 3 Companies (and What He’d Do Differently)17 Feb 202501:04:33

Harsh Patel is a repeat founder, investor, and board member who has built and sold multiple companies, including MakerSquare, Hack Reactor, and Galvanize, which had a $165 million exit. With experience scaling businesses from zero to one, finding product-market fit, and navigating M&A, Harsh has seen it all.

In this conversation, we discuss:

  • The hardest part of startup growth: Going from nothing to product-market fit
  • How Harsh hacked early distribution to get first customers
  • The rapid scale and exit of MakerSquare in under a year
  • What made Hack Reactor grow from $1M to $8M in revenue so quickly
  • How to know when to sell your startup
  • The future of crypto and AI, and why meme coins might be the next big thing
  • Why Harsh believes company equity will eventually live on the blockchain
  • And much more!

Brought to you by:

  • Fondo — The #1 accounting platform for startups. Get bookkeeping, taxes, and tax credits handled: TryFondo.com

Where to Find Harsh Patel

Where to Find Dav J Phillips

In This Episode, We Cover

  • (00:00) Welcome and introduction
  • (02:15) The challenge of finding product-market fit
  • (06:40) Harsh’s first startup experiences in second grade and beyond
  • (14:20) How he got the first users for MakerSquare using Quora
  • (22:10) Scaling MakerSquare to $1M revenue in 8 months and selling
  • (30:45) Growth lessons from Hack Reactor’s rapid scale to $8M revenue
  • (41:00) Why Hack Reactor sold to Galvanize and what changed
  • (50:35) Turning around Galvanize and selling for $165M
  • (1:02:10) How startups might raise money through on-chain tokenized equity
  • (1:14:00) Crypto, meme coins, and the future of decentralized businesses
  • (1:22:30) Final thoughts and lessons for founders

Referenced in This Episode

  • MakerSquare acquisition by Hack Reactor: TechCrunch
  • Hack Reactor and Galvanize $165M exit: Forbes
  • Quora's role in early startup growth: Quora
  • Pump.fun: The rise of meme coins and tokenized businesses: Pump.fun
  • Trump launching a meme coin and its regulatory implications: Bloomberg
  • The future of AI in startups: OpenAI
From cold email to his 2 startups getting acquired for $100M+27 Jan 202501:52:44


Brought to you by...

Fondo: Your all-in-one accounting platform for startups. Get your books closed, taxes filed, and cash back from the IRS. - https://www.tryfondo.com/

In this podcast episode, I had the pleasure of speaking with Chris Bakke, who shared his journey from working in private equity to finding success in the tech startup world. He described how his experience in private equity was challenging and often felt like a grind, which led him to seek a more fulfilling career in technology. This transition taught him the importance of hard work and resilience, especially when facing tough tasks that may seem unglamorous at first.

Chris emphasized that the key to his success was not just about having a great product but also about persistence and adaptability. He learned that building a business requires a lot of cold outreach and networking, which can be exhausting but ultimately rewarding. His insights highlight that maintaining mental health and motivation is crucial when navigating the ups and downs of entrepreneurship, as it can lead to significant achievements and personal growth

Timestamp
(0:00) - Intro

(0:17) - Origin Story: Growing Up and Early Career

(0:48) - Transition from Private Equity to Tech Startups

(3:03) - Lessons from Private Equity: The Importance of Scrappiness

(8:21) - Building Interviewed: The Idea and Early Customers

(12:01) - Sales Process: From Cold Emails to Conferences

(35:05) - Acquisition by Indeed: The Negotiation Process and Insights

Host Links:

https://x.com/davj

https://www.linkedin.com/in/davjphillips/


Guest Links:

https://x.com/ChrisJBakke

https://www.linkedin.com/in/bakk3/

Trailer15 Jan 202500:00:26

https://www.tryfondo.com/

🎧 START pod: Liam Karlsson & William Gyltman, Co-Founders of Rankad.ai "Turn AI visibility into revenue. On autopilot."31 Mar 202600:12:05

Liam Karlsson had no clue why his SEO clients were losing traffic while rankings held


Then his 57-year-old mom asked ChatGPT for new running shoes


Nike answer. Bought the shoe. Was super happy. 


Google was never part of that customer journey...


That was the seed of Rankad.ai


He pitched Co-Founder William Gyltman. They went all in


Track and grow brand visibility across ChatGPT, Perplexity, Gemini, and Copilot. 


Enter your domain, 30 seconds later you're in the app. AI agent optimizes your site directly


Liam Karlsson & William Gyltman, Co-Founders, Rankad.ai at The Residency Demo Day 


🎙️ Fondo START pod w/ David J. Phillips (full ep in comments)

00:25 “We’re helping companies earn more money in AI search”
02:34 AI search is moving fast: new models, algorithms, protocols
03:05 A new source of income beyond Google traffic
03:31 AI search is growing fast, but has not outrun Google yet
05:34 Enter your domain and get inside the app in about 30 seconds
05:52 Visibility, competitor, and company data inside one platform
06:07 AI gives optimization tasks based on scan data
06:15 The agent executes tasks on your site
09:41 SEO rankings held, but traffic still disappeared
09:47 Liam’s mom used ChatGPT to buy running shoes
10:00 “That was like the seed of Rankad”

🎧 START pod: Matthew Chen, Founder & CEO, Laurence "Autonomous performance marketing"27 Mar 202600:07:41

Amazon sellers do not have a data problem.

They have a decision problem.

They already have the clicks
The conversions
The impressions
The keyword history

What they do not have is a system that knows what to do with it.

So brands pay agencies $5,000 to $50,000 a month - and still lose money on ads

Matthew Chen built Laurence to change that.

A quantitative system for Amazon advertising.
Built for continuous decision-making under profit constraints.
Using existing ad copy, reinforcement learning, and custom models to run ads on autopilot.

When confidence is high, it acts
When data is sparse, it borrows signal from similar keywords

The result: about 40% better performance for customers.

Amazon is the wedge.
Autonomous performance marketing is the bigger vision.

🎧 START pod: Matthew Chen, Founder & CEO, Laurence "Autonomous performance marketing"

00:23 What Laurence does
02:12 How the company found the wedge
02:47 The customer quote that changed the company
03:15 The flaw in the standard Amazon ad model
05:25 The move from Amazon to the wider internet
06:12 How Laurence uses transformers today

JJ Maxwell, CEO & Founder, Pillar (trypillar.com) "Your App's Copilot"17 Mar 202600:16:37

Setting up a single trigger in Zendesk takes 30 clicks

With Pillar it takes one sentence

JJ Maxwell built an open source copilot you build into your app. Users talk to it in natural language and it drives the app for them

The problem: products can do a lot but users don't always know what's there. So they ask support. Or they churn

Before Pillar, JJ built a creator ad marketplace with about 40,000 creators. Then spent two years on another product through YC W24. About $30M on the platform, real users, decent growth. 

Pivoted anyway. 

As soon as he lost belief it was gonna work, he ripped the bandaid off

Web MCP is already rolling out. Companies trying to stop agents from taking actions are fighting a losing battle

🎙️ JJ Maxwell, Founder & CEO of Pillar (trypillar.com) on the Fondo START pod

01:56 What Pillar is: a copilot that’s easy to build into your app
02:19 Why users ask support or churn when product complexity hides value
03:05 “30 clicks” in Zendesk becomes a sentence
03:39 Why AI can do this now: models are better at reasoning and chaining actions
04:19 What implementation looks like: wrap existing frontend code and tool calls
05:25 Why teams can often get Pillar working in about a day
06:09 The Double journey, real traction, and the decision to pivot
11:00 Web MCP and why agent-ready software is coming
12:23 Why companies may not be able to stop agents from taking actions forever

Julian Weisser | The Solo Flippening: How 1-in-3 Startups Broke the Co-Founder Myth20 Dec 202500:18:18

The script has been the same for decades: find a co-founder

Investors demanded it.
Accelerators screened for it.

The narrative became so entrenched that founders started pairing up out of obligation, not alignment.

Julian Weisser, founder of SOLO and ODF, has a name for this phenomenon: co-founders of convenience

And he's proving they're not just unnecessary-they're often the reason companies fail.

This week, Julian released 'The State of Solo Founding' report: "Today, solo founding is considered odd. Soon it will be the default. This report features exclusive Carta data alongside commentary from solo founders who have raised over $250M and the investors who backed them."

The comprehensive tracks solo founder rates across thousands of startups, the headline finding is historic: for the first time, over one-third of new startups are solo-founded (That's 36% in 2025, up from under 25% in 2019)

👉 Download the report here: https://solofounders.com/report

👉 Apply to the Solo Founders Program today. A three-month, in-person residency for 6 ambitious solo founders. Next cohort starts Jan. 23, 2026: solofounders.com/program

(00:44) Why the report matters now
(02:17) The data: 24% → 36%, first year over 1-in-3
(04:32) 3 forces: AI, visible wins, collapsing narrative
(06:00) Investor POV
(07:30) Org design insight: cutting the middle layer
(09:47) Download report: http://solofounders.com/report
(11:01) ODF26: half the cohort flipped to solo
(12:33) Inside SOLO
(14:30) Why coworking doesn't work for startups
(16:37) Outcomes: $1M ARR in 2 months & more
(17:19) Follow @solofounding & @joinodf

Where to find Julian Weisser:‍
X: https://x.com/julianweisser
LinkedIn: https://www.linkedin.com/in/julianweisser
Website: https://weisser.io‍

Where to find SOLO: ‍
X: https://x.com/solofounding
LinkedIn: https://www.linkedin.com/company/solo-founders
Website: https://solofounders.com

Where to find ODF:‍
X: https://x.com/joinodf
LinkedIn: https://www.linkedin.com/company/solo-founders
Website: https://joinodf.com‍

Newsletters: ‍
Texts with Founders: https://textswithfounders.com
Multitudes: https://multitudes.weisser.io‍

Where to find David Phillips:
X: https://x.com/davj
LinkedIn: linkedin.com/in/davjphillips‍

Brought to you by:‍ Fondo — All-in-one accounting for startups @ fondo.com

Nate Matherson | Set It, Forget It—Scaling to 2,000+ Customers at Numeral19 Dec 202500:15:05

Nate Matherson has spent 10+ years as a founder. He's built companies and even exited. After that first exit, he started angel investing in dozens of companies, then launched a fund.

Numeral was one of his early bets. He sent Numeral's CEO Sam an email. By the end of the day, he was working there as Head of Growth. Now he's helping scale the YC-backed sales tax platform serving over 2,000 customers.

Nate's seen what happens when founders don't think about sales tax. "They actually found out that they owed about a half million dollars in sales tax… the buyer subtracted that off what would have gone to the founders."

When Nate was a founder, he'd log into Stripe and that sales tax dashboard was lit up like a Christmas tree. Numeral does free nexus studies and monitoring — takes five minutes to set up, plugs into Stripe and Rippling, then runs itself.

They launched their SaaS product recently, and their whole concept is set it and forget it. They actually love it when customers don't log in. Some of Nate's new learnings? "When I was a founder, I was always pretty good at marketing. I was just marketing not-so-great products, which made marketing a lot harder." At Numeral, with the right product at the right time, everything clicked.


And he knows: great products make marketing easy. Timing makes it effortless.

Key Topics Covered

  • [00:10] $500K sales tax bill found during due diligence
  • [01:10] What is nexus and how it triggers
  • [01:51] From founder to angel to fund manager to operator
  • [04:02] 10+ years building, angel investments, vc fund
  • [05:27] Numeral: e-commerce to SaaS journey
  • [08:12] States that tax SaaS + global VAT complexity
  • [08:40] "Set it and forget it"
  • [10:37] Free nexus study + monitoring in 5 minutes
  • [11:24] What's working in growth 
  • [13:28] Great products make marketing easy, timing makes it effortless
  • [14:25] Nate's investing rule per batch


Follow Nate Matherson:
X: @NateMatherson
LinkedIn: linkedin.com/in/natematherson

Follow Numeral:
X: @numeral
YouTube: youtube.com/@numeraltax
Website: numeral.com
LinkedIn: linkedin.com/company/numeralhq

FollowDavid Phillips:

X: https://x.com/davj

LinkedIn: https://www.linkedin.com/in/davjphillips

Brought to you by: Fondo — All-in-one accounting for startups: fondo.com

🎧 Startup Growth Podcast, Ep. 32 Jayden Clark | Moments to Flywheels: Founders Engineering Repeatable Reach18 Dec 202500:10:38

Jayden Clark didn’t abandon music. He re-scored it for distribution. 

After music school, a hedge fund tour, and a B2B SaaS sprint, he launched MOTS—short, sharp episodes designed to be both of the moment and built to last a quarter. 

His north star isn’t “go viral.” It’s “be clear.”

The insight is disarmingly pragmatic: structure is not the enemy of creativity—it’s the amplifier. Lists compress cognition. 

A beginning–build–end gives every clip a runway and a landing. 

When a five-replies-deep roast on X unexpectedly detonated, MOTS podcast already had the scaffolding to catch the surge. That’s the signature move: follow a consistent weekly cadence, then publish “emergency episodes” when the culture pops. 

The result is a feed that feels alive without feeling random.

Key Topics Covered

  • Career path: SF Conservatory → hedge fund → B2B SaaS → MOTS + Atlas Media Labs
  • Jazz formulas = content formulas: two-five-one progressions, building blocks, beginning-middle-end
  • Why lists work: digestibility, structure, pattern-matching
  • "Neither timely nor timeless": weekly SF tech culture + emergency current-thing episodes
  • Emergency episode #1: Brian Chesky's bench press 
  • The viral ratio: Meta Ray-Bans clip → five-tweets-deep → Theo's reply → Seth's "roast" GIF
  • "16 hours of screen time": the competitive advantage
  • Distribution strategy across Twitter, YouTube, Apple, Spotify

Timestamps:

00:20) "neither timely nor timeless"

(00:51) Keeping the music alive

(02:10) SF Music → hedge fund → SaaS → pod

(03:20) Jazz improvisation: a content strategy

(03:42) Building blocks & two-five-one progressions

(04:35) How to make content easily digestible

(04:53) The @theo ratio backstory

(06:46) @sethsetse viral quote-tweet

(07:17) Emergency pods vs. weekly episodes

(07:22) Emergency Pod #1: @bchesky's bench press

(09:42) Where to find @mots_pod

Where to find Jayden Clark:

X: @creatine_cycle
LinkedIn: linkedin.com/in/jayden-clark-75991a1aa

Where to find MOTS Podcast:

X: @mots_pod
YouTube: @motspod
LinkedIn: linkedin.com/company/mots-pod


Where to find Atlas Media Labs:

Website: atlasmedialabs.com

Where to find David Phillips:

X: https://x.com/davj

LinkedIn: https://www.linkedin.com/in/davjphillips

Brought to you by: Fondo — All-in-one accounting for startups: fondo.com

Sky Yang & Neo Lee | Content-Market Fit > Product-Market Fit: Why B2B Founders Are Getting Cloned16 Dec 202500:12:44

Sky Yang (CEO) & Neo Lee (CTO) are Co-founders of Imagine AI, an AI-powered content engine that clones B2B founders—replicating their voice, context, and backstory to create scalable personal brands. Before Imagine AI, Sky was elected student body president at UCSD by 32,000 students at age 19, then secured $150 million in state funding for university housing through coalition-building and advocacy in DC, Sacramento and at the UC Board of Regents. He co-founded "Break the Outbreak," a nonprofit that delivered PPE across 18 states and 53 cities during COVID, earning commendations from Senator Dianne Feinstein and Congressman Eric Swalwell. Neo transferred from UCSD to Berkeley, then dropped out to build. He met Sky freshman year at a beach event—asking "Are you Skygodkingdom?"—before they went skydiving together and Neo cut Sky's hair in the woods after COVID.

Their catalyst was realizing founders were building in public on X but deals were happening on LinkedIn. After meeting advisor Gustaf, they pivoted distribution strategy to focus on where B2B founders actually live and transact. Sky calls this "content-market fit"—a state where your content hits your target customer every single time, creating scalable, repeatable inbound motion. They were fully booked from their first week post-YC launch, landing Series B customers. One founder messaged urgently, jumped on a 15-minute call, and paid on Stripe immediately. They recruited over Halloween weekend instead of partying. They hosted a yacht party with $10 billion in collective GDP (320 capacity, 750+ on waitlist). Neo's philosophy: "The product is just amplifying what we already are. Just be authentic." Sky's vision references Westworld: "Your agents will interact with each other instead of humans."

Key Topics Covered:

· What Imagine AI is: a chat-first AI clone with high-fidelity persona creation, subject matter expert interviews, and content engineering to hit content-market fit

· From X to LinkedIn: pivoting distribution to where B2B deals actually happen; Gustaf's advice on market selection

· Sky's origin arc: Chengdu → LA → Bay Area → UCSD student body president → $150M state funding advocacy → Break the Outbreak nonprofit

· Neo's journey: UCSD → Berkeley dropout → "Skygodkingdom" beach encounter → haircut in the woods → building startups pre-Imagine AI

· Content-market fit framework: when your content hits your customer every single time—scalable, repeatable motion with high-intent top-of-funnel inbound

· Week-one hypergrowth: fully booked post-YC launch, Series B customers, 15-minute Stripe close during conference, recruiting over Halloween

· Authenticity over algorithm: amplification not fabrication; the product shapes around you, not the other way around

· Building clones that replicate voice, context, backstory, heuristics, and cognition

· The $10B GDPyacht party: 320 founders, 3 DJs, 750 waitlist—building community as cultural moment

· The 'Westworld' thesis: AI agents interacting on your behalf

· Building in public as 2025 narrative: why founders do great work but nobody knows; solving discovery through personal brand at scale

· Design philosophy: one infinite content motion thread vs. scattered posts; AI handles artifacts, humans make strategic decisions

Chapters:

01:21 - The origin story: "Are you Skygodkingdom?"
02:00 - Neo cuts Sky's hair in the woods
02:36 - Sky's journey: Youngest student body president at UCSD
04:20 - Securing $150M in state funding for student housing
06:28 - The nonprofit during COVID
06:40 - How Imagine AI started: solving their own problem
07:15 - Launching on YC and getting booked solid
08:00 - Using their own product for personal branding
09:08 - What is "content-market fit"?
10:08 - The future: AI clones
11:09 - The $10 billion GDP yacht party in SF
12:11 - Where to find Sky, Neo, and Imagine AI

Where to find Sky Yang:

LinkedIn: https://www.linkedin.com/in/skyyang

X: https://x.com/skygodkingdom

Where to find Neo Lee:

LinkedIn: https://www.linkedin.com/in/neo-lky

X: https://x.com/neo_lky

Where to find Imagine AI:

Website: https://www.imagineai.me

X: https://x.com/imagineagi

LinkedIn: https://www.linkedin.com/company/ai-imagine

Where to find David Phillips:

X: https://x.com/davj

LinkedIn: https://www.linkedin.com/in/davjphillips

Brought to you by:Fondo — All-in-one accounting for startups: fondo.com

Rebecca Medina & Jeff Phillips | How Talent Cheetah Cut PM Hiring from 90 Days to 5 Minutes with Transparent Pricing11 Dec 202500:32:36

Rebecca Medina and Jeff Phillips built an AI-powered talent marketplace that's disrupting recruitment with transparent pricing, direct negotiation, and same-day PM hires for SMBs.

Rebecca Medina had the network. She had decades of Big Tech experience. She had the credibility. But when she needed project management help on a client engagement as an independent consultant, none of it mattered.

"Even with my network of project managers, I couldn't find the right person fast enough," Rebecca recalls. "And it created a big problem for the company because we weren't able to scale as quickly as we wanted."

That pain point became Talent Cheetah.

Five years later, Rebecca and her co-founder Jeff Phillips have built an AI-powered talent marketplace connecting pre-vetted project managers with SMBs. They've scaled to 300 PMs across 34 US states. They've even partnered with the Project Management Institute. But the metric that matters most: the Bureau of Labor Statistics says it takes 90 days to hire a technical project manager. Talent Cheetah does it in minutes—with same-day hiring possible.

In this episode, Medina and Phillips break down the recruitment model that turns recruiting on its head: transparent pricing that exposes hidden markups, lower take rates than traditional agencies, direct PM-to-company negotiation, and real-time hiring through AI matching.

Their core unlocks: many traditional staffing firms charge companies a significantly higher rate than what PMs actually earn—often without disclosing the difference to either side; cultural fit matters just as much as credentials (project management exists on a broad spectrum — the skills needed vary widely across industries, company sizes, and stages of growth.); and past execution remains the strongest predictor of future performance. Their 25-point vetting process includes one pivotal test: candidates must be able to produce legitimate professional references—if you can't find even one after years in the field, you're not ready for the platform.

In this conversation, they reveal just how much AI is automating routine PM artifacts (like meeting notes, risk logs, and timelines) while increasing the premium on leadership and communication; how their intentional U.S.-based strategy competes on quality and transparency in an industry racing to the bottom on cost; and how Talent Cheetah is opening doors for underrepresented groups in project management; why fractional engagements (such as part-time PM support for short durations) are suddenly viable when traditional agencies can't deliver them well.


Key Topics Covered

The pain point origin: Rebecca's consulting crisis when her network couldn't deliver PM talent fast enough

The 90-day problem: Bureau of Labor Statistics average vs. Talent Cheetah's minutes-to-same-day matching

Exposing the hidden markup: traditional agencies bill $x/hour, pay PMs $x/hour, keep $x secret from both parties

No posting fees: free to post unlimited jobs (vs. ZipRecruiter/Indeed/LinkedIn pay-per-post), no sign-up fees for PMs

The 25-point vetting process: professional references, credential validation, and candidates who wait years

The reference test: some applicants can't find anyone to vouch for them after 12-24 months

Four-year minimum: experience requirement (not just title) focused on herding cats and managing projects
US-based strategy: competing on quality, transparency, and credential familiarity instead of global price competition

PMP vs. experience: why certification proves framework knowledge but not execution capability

Direct negotiation: PMs and companies set rates transparently, eliminating hidden recruiter markups

AI-powered matching: real-time algorithm surfaces top 3 PMs, with 297 more to browse

Cultural fit dynamics: startup PMs vs. Big Tech PMs require different personalities
Expanding beyond PMs: network architects, developers, product managers using same vetting framework

PMI partnership: hiring bonanzas and visibility programs in San Francisco

White glove service: helping first-time contractors negotiate rates and structure engagements

AI's impact on PMing: automating artifacts while amplifying leadership and communication needs

Fractional engagements: 10-hour/week arrangements that traditional agencies can't serve
Transparent pricing model: complete visibility vs. hidden markups, lower take rates than Robert Half/Adecco/Tech Systems

Chapters:

(01:55) Origin story: Talent Cheetah

(03:16) What makes Talent Cheetah different: Speed as the #1 differentiator, same-day hiring possible

(04:05) US-based strategy: competing on quality and credential familiarity

(06:08) Supporting underrepresented groups: veterans (logistics → PM transitions) and women in tech

(07:33) Serving both sides: job search help for PMs, FAANG-quality talent for clients

(08:43) White glove service: flexible involvement based on needs, negotiation help included

(09:16) How it works: 30-second account creation, under-5-minute posting, real-time AI matching

(10:15) Platform scale: 300 PMs across 34 US states, discipline-specific but industry-agnostic

(11:04) The 25-point vetting process: four-year minimum, references, credentials, interviews

(14:09) PMP certification vs. hands-on experience: gold standard plus practical execution

(16:02) Exposing the hidden markup: how traditional agencies work

(17:08) AI's impact on PM work: automating artifacts, amplifying leadership and communication

(20:40) Expanding beyond PMs: network architects, developers, product managers

(23:02) PMI partnership: 'hiring bonanzas' and visibility programs in SF

(25:12) Ideal clients

(26:47) Transparent pricing model: no posting fees for companies, no sign-up fees for PMs

(27:36) Getting started: talentcheetah.com, instant talent matching

(30:48) Internal messaging and AI matching: top 3 matches with direct communication

(32:00) Where to find them on LinkedIn, YouTube, talentcheetah.com



Where to Find

Rebecca Medina:
LinkedIn: https://www.linkedin.com/in/rebeccarm
Website: https://www.talentcheetah.com


Jeff Phillips:
LinkedIn: https://www.linkedin.com/in/jeffreyjphillipspmp
Website: https://www.talentcheetah.com


Talent Cheetah:
X: https://x.com/talentcheetah
LinkedIn: ht...

Julian Weisser | 'The Flippening': Why Solo Founders Are Becoming the Default04 Dec 202500:42:53

Julian Weisser is the Founder and CEO of Solo Founders, a three-month residency program in San Francisco where founders live and work together while maintaining full authorship of their companies. He's also the CEO of On Deck Founders (ODF), a program that over seven years and 26 cohorts has helped over 1,000 people start companies that have collectively raised more than $2 billion. 

As an angel investor with more than 150 portfolio companies including Levels, Astroforge, and MagicSchool, he's seen patterns in what actually predicts startup success versus what investors claim they're looking for. He writes the Texts with Founders newsletter sharing bite-sized practical wisdom for entrepreneurs and publishes Multitudes, a newsletter exploring founder psychology and startup strategy.

In this episode, Weisser breaks down the denominator delusion: solo-founded companies were more likely to succeed than co-founded ones, but nobody talked about it because when you look at the total number of successful companies, co-founded businesses eclipse solo successes—while hiding how many unsuccessful co-founded companies exist in the denominator. 

His core unlocks: two-thirds of startups die from co-founder disputes before reaching product-market fit or running out of money, being solo is far better than 99% of potential co-founders, and authorship (the desire to express yourself and put your vision into the world) matters more than contortionism (twisting your company to match what investors want to see). 

The flippening already happened in ODF 26—over half chose solo. In this conversation, he breaks down why MagicSchool's Adil Khan (a former high school principal with no startup experience) succeeded solo, how "co-founders of convenience" kill companies before they reach potential, what makes the Solo Founders residency feel like having "five co-founders while building your own company," and why mimicking trends accrues value to memes instead of founders.


Key Topics Covered:

  • The denominator delusion: why solo success rates are higher but invisible in the narrative.
  • Two-thirds die early: co-founder disputes kill startups before product-market fit or funding issues.
  • Co-founders of convenience: rushing into partnerships because investors demand it.
  • Invalid constraints: questioning beliefs (like needing school/work co-founders) that prevent great companies.
  • ODF's evolution: expanding who can start companies and who they can start them with.
  • The flippening moment: over 50% of ODF 26 chose solo after the program.
  • Authorship vs. contortionism: building authentically vs. pattern-matching for investors.
  • Solo Founders residency: six to seven founders per cohort, living/working together for three months.

Chapters:

  • (00:11) The denominator delusion: why solo-founded companies are more likely to succeed
  • (02:53) How ODF expanded the co-founder search beyond school and work connections
  • (07:05) The flippening: when solo becomes the default instead of the exception
  • (09:27) Why two-thirds of startups die from irreconcilable co-founder disputes, not lack of product-market fit
  • (10:02) Best practices for co-founding: avoiding assumptions and pre-mortems
  • (14:03) How early founders decide to go solo (most don't even consider it initially)
  • (17:42) ODF 26 results: over half chose to build solo
  • (18:48) Founder characteristics across boom cycles: more mimicry and trend-chasing than ever
  • (20:21) Mimicry vs. authorship
  • (22:33) The growth narrative trap: why $100B outcome fixation from massive funds limits great companies
  • (25:09) The Solo Founders residency: three months, "five co-founders"
  • (30:13) The space: own rooms, common areas, office on ground floor, 6am-3am usage
  • (33:27) Who applies: half bootstrapped and sold companies
  • (36:46) Authorship as the defining trait

Where to find Julian Weisser:


X: https://x.com/julianweisser
LinkedIn: https://www.linkedin.com/in/julianweisser
Website: https://weisser.io

Where to find SOLO:

X: https://x.com/solofounding
LinkedIn: https://www.linkedin.com/company/solo-founders
Website: https://solofounders.com

Where to find ODF:

X: https://x.com/joinodf
LinkedIn: https://www.linkedin.com/company/'odf'
Website: https://joinodf.com

Newsletters: 


Texts with Founders: https://textswithfounders.com
Newsletter (Multitudes): https://multitudes.weisser.io

Where to find David Phillips:
X: https://x.com/davj
LinkedIn: linkedin.com/in/davjphillips

Brought to you by:

Fondo — All-in-one accounting for startups: fondo.com

Allen Naliath | Sam Altman + Garry Tan Cold Asks, Win Conditions You Control & Why Friday Stops at 99%02 Dec 202500:19:37

Allen Naliath is the Founder and CEO of Friday, a Chrome extension that integrates AI email management directly into Gmail. Two years ago at Stanford, he struggled with the confidence to ask for what he wanted. So he engineered a solution: a 30-day rejection challenge where he had to hear "no" once per day or start to ask for increasingly audacious requests. The problem: people kept saying yes. He escalated strategically—waiting by a golf cart to ask Sam Altman to sign his laptop, and cold-asking Garry Tan to add him on LinkedIn during a Stanford talk. Garry's response: "Is this a Psyop?" He added him anyway. That connection led to YC. Today, Friday processes emails via predicted action buttons—users press enter repeatedly to archive, reply, or unsubscribe. Allen personally onboards every user to inbox zero in 10 minutes, even with 18,000 unread emails.

Naliath's catalyst was advice from a founder mentor: "If you want to work on startups when you graduate, don't even apply to Apple and Google. If you have no plan B, plan A has to work." His core insight: most people's win condition depends on the other person saying yes. He reframed it so yes and no are both wins—the win condition is in his control just by asking. That philosophy runs through Friday's design: it doesn't put email on full autopilot (which "induces anxiety"), it gets users 99% of the way. Friday started as a hackathon project, evolved into a mobile text assistant, then became a Chrome extension after realizing Gmail integration was faster than building feature parity. The average person spends two hours per day in email; Friday users get through 30 emails in 60 seconds.

Key Topics Covered:

- Rejection challenge: daily "no" requirement, mindset shift from fear to relief

- Win condition reframe: "Yes and no are both wins. The win condition is in my control just by asking."

- Cold approaches: Sam Altman golf cart ambush, Garry Tan LinkedIn add during Stanford talk

- Friday evolution: hackathon project → mobile assistant → Gmail Chrome extension

- Anti-autopilot philosophy: "That induces anxiety. It gets you to 99%—you stay in control."

- Predicted action buttons: archive, reply, unsubscribe—all one-keystroke approvals

- Voice matching: Friday drafts replies that sound like you, including dash preference

- 10-minute inbox zero: personal onboarding using auto-archive rules for old emails

- Chat feature: "Look him up online, find his email in my inbox, draft an intro."

Chapters:

(00:33) The rejection challenge that rewired his confidence
(02:08) Sam Altman signed his laptop

(03:35) Changing you win-condition to be in your control
(04:25) Asking for things that are "hard to get"

(05:20) Meeting Silicon Valley Legends

(06:05) "Is this a Psyop?" - how a cold LinkedIn ask to Garry Tan led to YC

(07:03) Dropping out of Stanford: "If you have no plan B, plan A has to work."

(09:23) Friday DEMO: how enter-enter-enter clears 30 emails in 60 seconds

(13:45) The inbox zero system: snooze what matters, archive the rest, empty daily

(15:13) Why Friday stops at 99%: "Full autopilot induces anxiety—you need control."

(17:36) Chat-powered bulk actions: "Look him up online, find his email, draft an intro."

(19:21) Make every day feel like Friday

Where to find Allen Naliath:

X: https://x.com/AllenNaliath
LinkedIn: https://www.linkedin.com/in/allennaliath


Where to find Friday:

Company X: https://x.com/fridaymail
Company Website: https://www.friday.so
Company LinkedIn: https://www.linkedin.com/company/fridaymail


Where to find David Phillips:

X: https://x.com/davj
LinkedIn: linkedin.com/in/davjphillips


Brought to you by:

Fondo — All-in-one accounting for startups: fondo.com

Lindsay Amos | Old vs. New Media, Exclusive vs. Embargo & Why Founder Brands Win Early26 Nov 202500:39:13

Lindsay Amos is the Founder of Amos Communications, a boutique firm for founder-led marketing and PR. From 2018 to 2024, she ran communications at Y Combinator, where she coached thousands of startups and wrote YC's handbook on startup PR. Before that, she worked in comms at Square and Meta, giving her a 360° view of how stories move from boardrooms to bylines to buyer behavior. Today, she advises founders on landing real news (not ads), building durable founder brands, and operating across a media landscape that's shifted from legacy gatekeepers to creator-led growth channels. She also co-created The To-Do List Summit, a workshop bootcamp teaching early-stage teams the tactical basics of comms, video, events, and community, and she writes a Substack on startup storytelling and strategy.

Amos's catalyst was living both media eras: nine months shepherding a single Wired story about Square moving into a new office versus today's "algorithms plus authenticity" environment. Her core unlocks: lead with the what (then earn the why), tie every pitch to a macro trend your audience already cares about, and default to exclusives over embargoes until you're big enough to run a press gauntlet. New media isn't a replacement for traditional outlets; the best founders run both lanes—because audiences follow people first, products second. In this conversation, she breaks down how to pick the right channel, prep for tough interviews, avoid blacklist behaviors, and time transparency (share the "personal hell" after you've won, to teach—not spiral).

Key Topics Covered:

- What "news" actually is: a hook plus a macro trend your customer already thinks about.

- Founder brand vs. company brand: why audiences follow people first (and how to use it).

- Exclusive > embargo (early): how editors green-light stories and why timing matters.

- Practical media ops: avoid Friday pitches, follow up once, don't text or Signal reporters.

- Content that converts: entertaining, educational, or perspective—never just ads.

- Cinematic launches: when video helps, when it's sizzle; why distribution still wins.

- New media shift: reporters → Substack/podcasts; find where your audience actually is.

- The To-Do List Summit: teaching founder-led marketing when agencies aren't the answer.

Chapters:

  • (01:58) Old media → new media
  • (05:26) Why founder-on-camera works—and when it doesn't.
  • (08:59) Playing the LinkedIn game, Substack, and sustaining the channels you'll keep.
  • (11:10) "Personal hell" as narrative fuel—share it after the win.
  • (21:58) Defining a real news hook; anchoring to macro trends (IRL + wellness example).
  • (25:48) Exclusive vs. embargo: how reporters decide what to cover.
  • (26:53) Pitch etiquette that keeps you off blacklists (days, follow-ups, warm intros).
  • (32:32) Founder brand > company brand (early) and the three content modes.
  • (36:33) The To-Do List Summit: workshops over thought leadership; hands-on playbooks.

Where to find Lindsay Amos:
X: https://x.com/lindsayaamos
LinkedIn: https://www.linkedin.com/in/lindsayamos, https://www.linkedin.com/company/amoscomms
Website: https://www.amoscomms.com
Substack: https://lindsayamos.substack.com
To-Do List Summit: https://x.com/todolistsummit

Where to find David Phillips:
X: https://x.com/davj
LinkedIn: linkedin.com/in/davjphillips

Brought to you by:
Fondo — All-in-one accounting for startups: fondo.com

Joe Holberg | Bootstrapped, Beat 30x-Funded Rivals, Acquired: Now He's Running for Mayor 24 Nov 202500:37:51

Joe Holberg is the Founder & former CEO of Spring, a workplace financial wellness platform that began D2C, pivoted to employer-paid, and became a top-rated U.S. offering for three consecutive years, serving 25,000+ users. He bootstrapped from 2015 to 2018, raised a $1M seed, and sold Spring to Mariner Wealth Advisors in 2023, remaining through early 2025. Before Spring, he taught with AmeriCorps on Chicago’s West Side and built CS education at Google. A first-generation college graduate who once slept in his car to finish school, Joe is now a declared candidate for the 58th Mayor of Chicago.

Holberg’s catalyst was seeing financial confusion across backgrounds—even among peers with professional-class parents. Early Spring had universal interest but low willingness to pay; the unlock was changing the buyer (HR) and making a firm pricing decision: “Pricing isn’t science—it’s a decision.” In this conversation, he discusses building Spring, the B2B pivot, lessons from pricing and sales, and his views on city governance, housing supply, business climate, and tech-literate leadership. This episode presents his perspective and experiences as a founder and candidate.


Key Topics Covered:

  • What Spring was: outcomes-oriented financial wellness delivered as a workplace benefit.
  • D2C → B2B: universal desire vs. $20/mo friction; employers fund, employees benefit.
  • Pricing lessons: fewer options, clearer value, faster decisions.
  • Builder arc: bootstrapping (2015–2018), $1M seed, top-rated product, 2023 acquisition; stayed through early 2025.
  • Sales scrappiness: writing a book to establish credibility with HR leaders.
  • Entering politics: motivations, background across economic circumstances, and emphasis on tech literacy.
  • Chicago context (as framed by the guest): population and business trends; collaboration vs. adversarial postures.
  • Governance mechanics: mayor/city council dynamics; CPS school board changes; housing supply constraints.
  • Campaign posture: outsider experience and how he frames his narrative as a candidate.


Chapters:

(00:36) Spring’s origin — addressing financial education gaps observed across income levels.

(01:43) Early arc — glow-stick hustle; first-gen college; sleeping in the car; AmeriCorps; Google; leaving to build.

(04:21) “Credibility book” — unconventional sales asset for HR conversations.

(06:14) The pivot — strong demand, low D2C conversion; employer-paid model.

(08:43) Building years — 2015 start, 2018 $1M seed, solo grind → top-rated 3 years, 25k+ users; 2023 acquisition; through early 2025.

(12:39) Pricing "aha" — choosing and owning a price to accelerate qualified deals.

(14:37) Why enter politics — empathy across the income spectrum; need for tech-aware governance.

(20:02) Entering the arena — outreach, mentorship, and announcing candidacy.

(24:23) Status quo (guest’s view) — resident/business trends; collaboration with builders.

(27:22) How Chicago governance works — mayor vs. council; CPS board; housing supply.

(30:55) Voter expectations — vision, ideas, results.

(32:32) Closing themes — affordability, fiscal considerations, and civic participation.


Where to find the Joe Holberg:
X: @holbergj
LinkedIn: linkedin.com/in/joeholberg
Website: joeforchicago.com


Where to find David Phillips:
X: @davj
LinkedIn: linkedin.com/in/davjphillips


Disclosure / Non-Endorsement Note:

The views expressed by the guest are their own and do not reflect the views of David J. Phillips, Fondo or the Startup Growth Podcast. Appearance on the podcast does not constitute an endorsement of any candidate, campaign, or policy proposal. This episode is provided for informational purposes only.

🎧 START pod: Milind Sagaram, Co-Founder & CEO, Articulate "Speeding Up Construction with AI"27 Mar 202600:06:52

Construction doesn't fail on the jobsite. It fails in the drawings. The jobsite just reveals it

Project managers spend half their time scanning plans page by page for conflicts between disciplines. Plumbing through steel beams. Electrical into HVAC

They still miss most of it. Millions in rework when caught in the field

Milind Sagaram built Articulate to catch these issues before construction starts

AI reads the PDFs. Finds clashes across architectural, structural, and MEP sheets. Generates draft issue reports automatically

The surprise: construction teams aren't resistant. They want it more than anyone expected

🎙️ Milind Sagaram, Co-Founder & CEO, Articulate / Helonic.com on Fondo START pod 

00:18 AI for finding drawing issues before construction starts
02:24 The old workflow: manual plan review
02:45 The consequence: rework and delays
03:00 Small issues, massive downstream cost
03:27 Copilot, not replacement
04:04 Why AI belongs in construction
04:39 What surprised him about selling into the industry
05:59 Who Articulate sells to

Jay Ram | Beyond Evals: Build Environments That Make Agents Better19 Nov 202500:22:01

Jay Ram is Founder & CEO of Hud, the evaluation and RL platform for AI agents. Hud helps startups build RL environments, run fast reward loops, and plug into any RL backend—so teams can cut costs and push last-mile accuracy once they've hit PMF. Before Hud, Jay left a lucrative quant career, shipped an AI prank-calling app that briefly hit #1 on the App Store (≈500k calls), and decided he wanted harder problems and smarter customers. He's a YC W25 alum; Hud is already used by researchers at foundation labs and is expanding into enterprise environments.

Jay's catalyst was realizing he didn't want to just talk weekends—he wanted to build. He and his co-founders first tackled computer-use evals for labs. Inside that work, the language shifted: labs asking for "evals" really needed environments—places where you design rewards, iterate, and actually improve model behavior. Today, Jay frames Hud as the "Next.js of RL environments": opinionated lifecycle, backend-agnostic training, and infra that returns signal fast. Early on, use a foundation model; post-PMF, train your own with SFT/RL—that's where environments matter. Looking ahead, he sees post-training speciation: domain-tuned models for finance, accounting, creative tooling, and more—because teams will own more of their stack again.

Key Topics Covered:

· What Hud is: tools to set up your agent for RL, define tasks, shape rewards, and plug into RFT/other RL backends.
· From evals to environments: why scores measure but rewards improve—and how iteration loops change outcomes.
· Where it fits: use foundation models early; post-PMF train your own for cost leverage + last-mile gains.
· Design + infra: a new category needs opinionated UX and fast results; why lab researchers use Hud for computer-use evals.
· Market timing: the "DeepSeek moment" pulled RL from hobbyists into enterprise interest in 2025.
· Pre-train vs post-train: scale vs accuracy + domain depth—and why post-training is the real edge.
· Future of work: enterprises will own more of the stack; model speciation by domain.
· Reality check: agents ace toy DBs, struggle in production; modeling real environments is the unlock.
· YC W25 arc: vision matched the original app more than mid-batch; enterprise demand is catching up now.
· Finance stack aside: keep ops boring; focus cycles on shipping product (Fondo shoutout in-episode).


Chapters:

(00:15) Cold open — "We give you all the tools to set up your agent for RL."
(00:59) Intro — Jay Ram, Hud, and the origin story
(01:41) What Hud does — build RL environments; backend-agnostic (OpenAI RFT, Thinking Machines, etc.)
(02:12) Where environments fit — early: foundation models; post-PMF: train for cost + accuracy
(02:50) From quant to builder — leaving Wall Street to make things
(03:30) The prank-calling app — #1 on App Store; ≈500k calls; why the customers weren't it
(04:40) Evals → environments — labs' "eval" asks were really RL environments with rewards
(05:40) Evals vs RL — scores vs rewarded steps; how updates happen
(07:14) Hard parts — opinionated design + infra speed for researchers and teams
(08:08) Before Hud — no toolkit/standards; emerging gymnasium-style efforts vs Hud's opinionated path
(09:25) YC W25 — applying, partners (Aaron & Matt), why YC felt like "actual college"
(11:05) Vision vs timing — market caught up; enterprises now exploring environments
(12:20) Trend — teams rolling their own models post-PMF (SFT/RL)
(13:01) Today's fragmented stack — hosting, inference, data; Hud's role in the loop
(13:48) The "DeepSeek moment" — hobbyist RL → enterprise interest in 2025
(15:57) Future of agents — own the stack, post-training speciation
(18:26) Why end-to-end is hard — production data systems need real environments
(19:29) Forward-deployed labs — domain hires and environments; how Hud plugs into RFT
(20:15) Rapid wrap — it's early; the stack is shifting fast

Where to find Jay Ram:
X: @jayendra_ram
LinkedIn: www.linkedin.com/in/jay-ram-29003b198/


Where to find Hud:
X: @hud_evals
Website: hud.ai


Where to find David Phillips:
X: @davj
LinkedIn: linkedin.com/in/davjphillips

Brought to you by:

Fondo — All-in-one accounting for startups: fondo.com

Kevin Xu | From $35K to $10M: The Alpha Behind Your Next Bet17 Nov 202500:38:03

Kevin Xu is Founder & CEO of Alpha AI, your “AI money friend” that plugs into real-time markets and your portfolio to explain what just happened—and what matters next—inside a simple chat. Before Alpha, Kevin became a WallStreetBets folk hero as turning $35K in a 401(k) into $10M through high-conviction swing trades. He previously founded Fan Hero (YC S13), worked at Stripe (~#300) and Google/YouTube, and appeared in MSNBC Studios’ Diamond Hands on Peacock.

Kevin’s catalyst was realizing the products he loved—Google, Wikipedia—were built by real people. That sent him to YC, then Stripe for world-class reps, then into the internet’s finance classroom: Reddit. He posted every win and loss, learned in public, and distilled trading into rules like “If it’s good enough to screenshot, it’s good enough to sell.” After building After Hour to socialize trading, he’s now productizing that edge with Alpha AI: a proactive, personable copilot designed to build money confidence for the next million millionaires.

Key Topics Covered:

 • What Alpha AI is: a chat-first AI money friend with market context + your portfolio, proactive “what just happened” nudges, and customizable character.
 • From WSB to product: turning public receipts (35K→10M) into a system—floors, catalysts, concentration, disciplined exits.
 • Earnings humility: why reports are a coin flip; behavior, sizing, and timing are the real edges.
 • Founder arc: Stanford → YC pivot muscle → Stripe discipline → Google scale → After Hour → Alpha AI.
 • Culture shift: finance as entertainment/sport; people don’t need courses—they need context at the right moment.
 • Design over dashboards: one infinite chat thread > scattered tools; AI handles background work, humans make decisions.
 • Missed GME, learned anyway: thesis right, timing wrong—how to keep momentum without hero trades.
 • Distribution & trust: followable identities, real screenshots, timely alerts—how credibility compounds.
 • Building in 2025: attention-maxxing, shipping fast, leaning into new formats (e.g., Sora experiments).
 • Finance stack mindset: keep ops boring—Fondo for the back office, Brex for cash/cards—so you can ship product.

Chapters

 (00:00) Cold open — “I wanted a cool dream”: realizing real people build the internet
 (00:59) Intro — Kevin Xu, Alpha AI, and the origin story
 (01:28) Stanford → YC S13 double-interview; pivot from Alpha Labs to Fan Hero
 (06:11) Stripe (#~300) → Google/YouTube: seriousness vs. internet-native play
 (09:00) WallStreetBets culture: memes, transparency, learning in public
 (12:26) The 401(k) stake: missed HR toggle → $35K starting gun
 (14:53) Early pandemic plays: APT, CODX; the floor + catalyst lens
 (17:33) Chasing pops: cruises, Chewy-era stories, and disciplined exits
 (20:11) The GME almost: all-in October, out in December; lessons on timing
 (23:33) Million-dollar swing days; detachment and the screenshot rule
 (25:10) Big 5 finale → $10M peak; why earnings are coin flips
 (27:15) After Hour: social finance, trust via receipts, real-time notifications
 (30:50) Alpha AI: proactive context, AI friends as the interface
 (32:52) Beyond investing: building money confidence; simple company finance stack

Where to find Kevin Xu:

LinkedIn: https://www.linkedin.com/in/imkevinxu
X: https://x.com/kevinxu
Instagram: https://www.instagram.com/founderkevin

Where to find Alpha AI:

Website: https://alpha.so
X: https://x.com/alpha_ai
Instagram: https://www.instagram.com/chatwithalpha

Where to find David Phillips:

X: https://x.com/davj

LinkedIn: https://www.linkedin.com/in/davjphillips


Brought to you by:

Fondo — All-in-one accounting for startups: fondo.com

Daivik Goel | From Bootstrap to Batch, Last-Minute YC Submit & Why Fintech Speed Matters01 Nov 202500:37:52

Daivik Goel is Co-founder & CEO of Shor, a global payroll platform for startups. Traditional EOR providers charge around $7,000 per year to manage an employee earning $20,000 per year. Shor uses automation to reduce costs and embeds payroll actions into Slack and WhatsApp through AI agents, so founders can request tax documents or payment updates without opening another dashboard.

Daivik and co-founder Avi Konduru submitted their YC application at 7:59 PM, one minute before the deadline. After multiple prior rejections, they got an interview, then a follow-up call, then acceptance. They started YC with a crypto payment idea, pivoted five weeks before demo day to global payroll—a problem they'd worked on two years earlier—and shipped contractor payroll within a week. They've since raised funding and are scaling.

Key Topics Covered:

What Shor is: global payroll/EOR rebuilt for startups; automation handles ops, AI teammates deliver docs/actions in Slack/WhatsApp.

From clever to sellable: pivoted inside YC from crypto/fiat rails to payroll where they had access and clear pain.

Cost math that breaks: why legacy EORs charging ~$7k/yr on a $20k salary fail SMB/unit economics—and how Shor attacks the middle.

Ship speed as strategy: prior fintech muscle let them launch contractor payroll in one week (KYC/KYB, payouts, tax flows).

Design →  dashboards: move work to the user (chat interfaces), keep humans making decisions, let AI do the background jobs.

Distribution as a moat: serve the massive long tail priced out by incumbents; win on affordability + responsiveness.

YC pragmatism: plain-English interviews beat pitch theater; momentum over mockups.

Execution after Demo Day: demand first, fundraising next, delivery always—scaling compliance/country coverage without losing speed.

Founder operating cadence: daily inches over hype cycles; embrace “pivot hell,” but pick battles you can actually win with customers.

Finance stack mindset: reliability and support matter most when back-office tools fail—opt for vendors who show up.

Chapters

(00:00) Cold open — the 7:59 PM YC submission
(00:37) Intro — Davik & what Shor is (affordable global payroll)
(02:51) Waterloo → founder mindset and process discipline
(06:05) YC journey and batch dynamics
(08:26) First leap without an idea + early GTM lessons
(11:56) Marketplaces are hard — takeaways that shaped Shor
(14:56) The last-day YC rush & the crypto/fiat idea
(24:49) Pivot hell inside YC → choosing global payroll
(27:28) Shipping contractor payroll in one week + why now (AI/stablecoins)
(29:33) Fundraising wrapped; AI teammates over dashboards; what’s next

Where to find Daivik Goel:


Multilink: https://bento.me/daivik
LinkedIn: https://www.linkedin.com/in/daivikg
X: https://x.com/DaivikGoel
Instagram: https://instagram.com/daivikgoel
YouTube: https://m.youtube.com/channel/UCzkRfrCXIrW1v60Wyasgq7Q
Substack: https://daivikgoel.substack.com
TikTok: https://tiktok.com/@daivikgoel

Where to find Shor:


Website: https://tryshor.com
X: https://x.com/shor_pay
LinkedIn: https://www.linkedin.com/company/shorpay
Instagram: https://www.instagram.com/shor.pay/
YouTube: https://www.youtube.com/watch?v=OF1m1H0arYY

Brought to you by:

Fondo — All-in-one accounting for startups: https://fondo.com

Cody Schneider | Growth Flywheels, Underpriced Attention & Building Graphed's AI Agent for Marketing Analytics24 Oct 202500:23:55

Cody Schneider is the Founder & CEO of Graphed, an AI agent for marketing analytics. Graphed plugs into common data sources, manages the data warehouse, and lets marketers chat with their data to generate on-demand visuals—“stacked bar of new vs. total users week over week,” “add a line of best fit,” and similar prompts. It’s built to handle scale (Cody mentions onboarding ~25M rows of Facebook data) and to avoid rate limits and sluggish queries by owning the warehousing layer.

In this episode, Cody outlines a practical path from data sprawl to decisions: skip steep BI learning curves and ticket queues; connect sources and ask in plain English for charts and basic analyses. He also talks about how creative volume now functions as targeting—ship lots of concepts, let algorithms find buyers—and positions Graphed as the way to see what’s working without waiting on a data team. For founders and marketers, it’s a clear primer on turning raw rows into faster feedback loops.

Key Topics Covered:

• What Graphed is: an AI agent for marketing analytics that connects sources, manages the warehouse, and lets you chat to generate charts and basic analyses. 
• From tickets to answers: why BI queues and tool learning curves slow teams—and how a chat interface shortens time-to-insight.
• Scale as a requirement: handling large datasets (e.g., ~25M rows of ads data) and avoiding rate limits via a managed warehousing layer.
• Roadmap preview: proactive weekly Slack briefs that summarize what changed and why (future functionality).
• Creative = targeting: in 2025 paid acquisition, high-volume creative acts as the audience filter while algorithms find buyers.
• Stacking S-curves: double down on the working channel, then layer the next before growth plateaus.
• Arbitrage windows: underpriced media (e.g., creator CPMs ≈ $2; low-cost local streaming TV CPMs) and why illiquid channels create edge.
• Unit economics discipline: CAC/ARPU/LTV/payback thinking—losing on month one can be rational if LTV justifies it.
• Validation before build: use ads and landing pages to test demand—even before a product exists.
• Founder ops stack: practical setup (e.g., Stripe Atlas, Mercury, Carta, Fondo) to keep focus on product and sales.


Chapters


(00:00) Introduction to Graphed.com
(02:12) Cody's Journey at Rupa Health
(05:36) Growth Strategies and Metrics
(11:19) Paid Advertising Insights
(15:10) Exploring Programmatic TV Advertising
(18:57) The Vision Behind Graphed.com
(21:57) Building a Financial Stack for Startups


Where to find Cody Schneider:


LinkedIn: https://www.linkedin.com/in/codyxschneider

X: https://x.com/codyschneiderxx 


Where to find Graphed:

X: https://x.com/graphed
Website: https://www.graphed.com

Where to find David Phillips:

X: https://x.com/davj

LinkedIn: https://www.linkedin.com/in/davjphillips


Brought to you by:

Fondo — All-in-one accounting for startups: https://fondo.com

Craig J. Lewis | 750K Contractors Paid, $25M Raised, MassChallenge Board - From Gig Wage to Ogentic AI24 Oct 202500:31:04

Craig Lewis is the Founder & CEO Ogentic AI, builder of Zing—an AI-native enterprise browser that turns intent → action in a secure, workflow-native workspace. Before Ogentic, he founded Gig Wage (750k contractors paid, ~$1B moved, $25M+ raised) and learned payroll inside ADP. That operator muscle fuels Ogentic’s pace: incorporated in June, alpha in July, beta in August. He also serves on the governing board at MassChallenge and angels actively.

In this episode, Craig shares velocity advice like: ship before perfect (feedback > stealth), build pro-human AI (human-in-the-loop), and treat fundraising like sales (expect 19 no’s, optimize investor–founder fit, when it’s right—TTFM). He outlines the back-office stack that keeps your startup in good shape and his board philosophy: offer perspective, not prescriptions. If you’re building enterprise AI—or just want to move in weeks, not quarters—this one’s for you.


Key Topics Covered:

  • Ogentic AI focuses on enterprise productivity and automation.
  • Building a strong back office is crucial for startups.
  • Fundraising is a numbers game; persistence is key.
  • Feedback is essential for product development.
  • AI will replace some jobs but also create new ones.
  • Having a technical co-founder can accelerate growth.
  • Navigating the fundraising landscape requires understanding investor fit.
  • MassChallenge supports entrepreneurs in solving global challenges.
  • The future of work will involve augmenting human capabilities with AI.
  • Startups should find their niche in the AI market.


Chapters

(00:00) The Rise of Ogentic AI

(13:37) Building a Strong Back Office

(17:02) Navigating Fundraising Challenges

(19:14) The Role of MassChallenge

(23:12) AI and the Future of Work

(27:40) Fundraising in the AI Era


Where to find Craig J. Lewis:

Linkedin: https://www.linkedin.com/in/mrfutureofwork

X: https://x.com/CraigJamalLewis 

Instagram: https://www.instagram.com/craigjlewis


Where to find Ogentic AI:

 
Website: https://ogenticai.com
LinkedIn: https://www.linkedin.com/company/ogenticai
X: https://x.com/ogenticai
Instagram: https://www.instagram.com/ogenticai

Where to find David Phillips:

X: https://x.com/davj

LinkedIn: https://www.linkedin.com/in/davjphillips


Brought to you by:

Fondo — All-in-one accounting for startups: https://fondo.com

Grace Gong | Lessons on Building Founder–Investor Community: Curate for Outcomes, Not Optics17 Oct 202500:27:37

Grace Gong is the Founder & CEO of Smart Venture Media, podcast host, angel investor, and author. She’s interviewed 500+ founders, investors, and operators on her podcasts, then parlayed that network into a high-signal community: curated founder–VC dinners, conferences (including the Smart AI Summit), and rooms where intros turn into customers and checks. The flywheel started during the pandemic with 5 pm Friday Zooms—and evolved into tightly curated IRL events supported by sponsors and operators.

In this episode, Grace outlines a practical approach to community-building: curate for outcomes, not optics (every seat should benefit from every other seat). Her angel filter doubles as her invite list. Online → IRL is the sequence: earn trust digitally, concentrate it offline.  For founders aiming to stand out without burning cash, this is a clear primer on turning audience into deal flow.

Key Topics Covered:

  • Building community has to happen organically.
  • Engaging with entrepreneurs can lead to unexpected opportunities.
  • Sales and storytelling are crucial skills for success in VC.
  • Offering value to others is key to building relationships.
  • The people you meet at events can significantly impact your journey.
  • Planning events requires meticulous attention to logistics.
  • Creating a curated experience enhances networking opportunities.
  • AI is transforming the media landscape and how we build companies.
  • Networking is essential for both founders and investors.
  • Continuous learning and adaptation are vital in the fast-paced tech world.


Chapters

(00:00) Building Community: The Organic Approach
(02:50) Journey into Venture Capital: From Real Estate to VC
(05:44) Insights from Interviews: Lessons Learned in VC
(08:53) Angel Investing: Key Considerations
(11:51) Creating Value: The Importance of Community
(15:02) Event Planning: From Small Gatherings to Large Conferences
(17:59) The Smart AI Summit: Curating Experiences
(20:54) Future of Media: Building with AI
(23:48) Final Thoughts and Online Presence


Where to find Grace Gong & Smart Venture Media:


Linktree: https://linktr.ee/gracegong115

Where to find David Phillips:

X: https://x.com/davj

LinkedIn: https://www.linkedin.com/in/davjphillips


Brought to you by:

Fondo — All-in-one accounting for startups: https://fondo.com

Collin Wallace: Inside venture funds, why billion-dollar outcomes make sense - and how founders stack the odds15 Oct 202500:44:48

Collin Wallace is a partner at Lobby Capital with 20+ years as an engineer, inventor, operator, and investor. Before Lobby, he was Managing Director of Techstars Silicon Valley, launching the first two Bay Area accelerator programs with JPMorgan and eBay. He founded FanGo (Techstars S10)—acquired by Grubhub in 2011, where he became Head of Innovation (OrderHub + pre-IPO patents)—and later co-founded ZeroStorefront (YC W19), acquired by Thanx in 2022. Collin advises the Roelof Botha & Huifen Chan Innovation Program, co-teaches Startup Garage at Stanford GSB, has run two YC Demo Day Funds, and has invested in 80+ startups (e.g., Payjoy, Landed, Mosaic Voice, Postscript, Vellum).

In this episode, Collin gives founders some great advice: you’re running two businesses (product for customers, equity for investors). Fund math in concentrated portfolios means ~2 of ~20 bets must carry returns; with dilution to ~10% at exit, winners need multi-billion-dollar potential. Sequence your proof: Pre-seed = prove value; Seed = prove people pay (repeatably); Series A = scale what’s already repeatable. Don’t scale misses (the Steph Curry test). And match capital to your vehicle - venture is rocket fuel: perfect for rockets, destructive for "pickup trucks".


Key Topics Covered:

  • Running a startup involves selling to customers and investors.
  • Different VCs have varying expectations based on fund size and strategy.
  • Founders should tailor their pitches to the specific needs of investors.
  • Understanding investor dynamics can improve fundraising success.
  • Successful founders diverge from conventional thinking in their industries.
  • Ambition and hustle are key traits for founders.
  • Expectations change significantly after receiving funding.
  • Consistency and repeatability are crucial for scaling a startup.
  • Community engagement can foster innovation and collaboration.
  • The back office is essential but often seen as a distraction.

Chapters

(00:00) Introduction to Colin Wallace and His Journey
(02:14) The Shift in Growth Expectations for Startups
(05:03) Understanding Investor-Fit and Fundraising Dynamics
(11:12) The Importance of Founder Attributes
(17:15) Navigating the VC Landscape and Expectations
(21:03) Post-Funding Realities for Founders
(22:40) Understanding Seed Capital and Series A Expectations
(25:19) The Evolution of Funding: Series B and C
(29:05) Coaching the Next Generation of Founders
(32:09) Building the Back Office: The Unsung Hero
(35:42) Community Building and Inclusive Events

Where to find Collin Wallace:

Linkedin: https://www.linkedin.com/in/collin-wallace/ 

X: https://x.com/pithyprof 

Website: https://lobby.vc/people/collin-wallace/ 

Where to find Lobby Capital:
Linkedin: https://www.linkedin.com/company/lobby-capital/
X: https://x.com/lobby_vc
Website: https://lobby.vc/

Where to find David Phillips:

X: https://x.com/davj

LinkedIn: https://www.linkedin.com/in/davjphillips


Brought to you by:


Fondo — All-in-one accounting for startups: https://fondo.com

Alessandro Chesser: Turn Founder Shares into Tax‑Free Gains with QSBS Trust Stacking09 Oct 202500:33:42

Alessandro Chesser is the founder and CEO of Dynasty, a startup focused on making Qualified Small Business Stock (QSBS) trust stacking accessible to founders. Before launching Dynasty, he led sales at Carta from the early days to roughly $300M in ARR, gaining hands-on insight into equity workflows, 409A dynamics, and how distribution is built around real, recurring needs. Dynasty offers a subscription service—$1,500 per year for up to four family trusts—that includes trust creation, annual administration, and tax return filing, turning a traditionally bespoke, high-cost process into something founders can set up early in their journey.

In this episode, we unpack the mechanics and timing that make—or break—QSBS outcomes. We cover the core tests (acquiring shares before $50M in assets, five-year hold, qualified C-corp status), state-level differences (New York recognizes QSBS; California does not), and why early planning can start both the QSBS and long-term capital gains clocks while avoiding later surprises. 

Chesser talks about trust stacking—gifting shares into multiple family trusts so each may pursue its own QSBS exclusion—and notes practical guardrails and expert advice for dong it right. Beyond the tax planning, Chesser shares go-to-market lessons from Carta and Dynasty: using the network effect (e.g., certificates signed), creating urgency with must-do workflows (like 409A), iterating growth levers monthly, hiring decisively, and using social + creator partnerships instead of traditional cold outbound. The result is clear: tactical advice for founders on when to exercise, when to gift, how to document, and how to avoid the common QSBS pitfalls discussed in the conversation.

Key topics covered

- QSBS allows startup shareholders to sell up to $15 million tax-free.
- Most startups qualify for QSBS, but there are specific criteria.
- Holding shares for at least five years is crucial for QSBS eligibility.
- The new rules under the big beautiful bill change QSBS eligibility timelines.
- Dynasty helps founders maximize QSBS benefits through trust stacking.
- Early exercise of stock options can prevent alternative minimum tax issues.
- Filing an 83B election is essential for QSBS qualification.
- Social media is a powerful tool for startup growth and marketing.
- Building partnerships with influencers can enhance visibility and credibility.
- The cost of setting up trusts for QSBS is significantly lower with Dynasty.

In This Episode, We Cover

(00:00) Introduction to QSBS and Its Importance

(06:35) Understanding QSBS Eligibility and Benefits

(13:08) The Role of Dynasty in Maximizing QSBS Benefits

(16:29) Alessandro's Journey and the Birth of Dynasty

(18:36) Growth Strategies and Lessons from Carta

(27:14) Leveraging Social Media for Growth

Where to Find Alessandro Chesser:

LinkedIn: https://www.linkedin.com/in/alessandro-chesser-84763748

X: https://x.com/SandroChess

Where to Find Dynasty:

Website: https://www.getdynasty.com

LinkedIn: https://linkedin.com/company/getdynasty

X: https://x.com/getdynasty_com

Where to Find David Phillips:

X: https://x.com/davj

LinkedIn: https://www.linkedin.com/in/davjphillips

Brought to you by:

Fondo — All-in-one accounting for startups: https://fondo.com

Jeff ‘Jiho’ Zirlin: From 300 Users to $4B+ in Trading Volume, The Story Behind Axie Infinity’s Meteoric Growth03 Oct 202500:35:54

Jeff ‘Jiho’ Zirlin is a co-founder of Sky Mavis, the team behind Axie Infinity and the Ronin blockchain. At the forefront of Web3's most groundbreaking experiments, Jeff helped transform Axie from a small crypto-native community into a cultural phenomenon that onboarded millions to blockchain technology. With over $4 billion in NFT trading volume - earning a Guinness World Record - Axie didn't just talk about bringing people to crypto; it actually did it. Beyond Axie, Jeff pioneered the Ronin blockchain, which now hosts 70+ games and has proven that purpose-built infrastructure can unlock exponential growth for crypto applications.


In this episode, we trace the evolution of Web3 gaming from its origins in the CryptoKitties community to today's institutional adoption cycle. The conversation explores how manual onboarding and white-glove user acquisition laid the foundation for viral growth. Jeff shares the pivotal moments that shaped Axie's trajectory: tokenizing experience points, creating the "play-to-earn" model that democratized crypto mining, and the strategic decision to build their own blockchain when existing infrastructure couldn't scale. We also examine the current state of crypto gaming, the shift from retail mania to Wall Street adoption, and why the next wave of innovation might create entirely new cultural mediums rather than just new ways to make money.



Key topics covered:

  • The CryptoKitties Mafia: How a December 2017 viral game spawned the founders of Axie, OpenSea, and the modern NFT ecosystem
  • Manual onboarding at scale: From personally gifting Axies to Binance angels to hitting 2 million users
  • The biological insight: Why CryptoKitties failed (no death = exponential breeding) and how ecosystem balance became Axie's core principle
  • 300 users was "#1": How being the largest crypto game with just 300 players became a marriage proposal line - and a growth trajectory
  • Tokenizing the game economy: The moment players asked to buy experience points and accidentally invented play-to-earn
  • "You can't build your startup on another startup": Why Loom Network's failure forced Sky Mavis to create Ronin blockchain
  • The Ronin Effect: Deploying at 30,000 users, scaling to 2 million in six months - and the infrastructure playbook now powering 70+ games
  • The Uniswap wealth effect: How every Axie player unexpectedly received $4,000, creating a growth catalyst nobody predicted
  • Why gaming onboards better than DeFi: More people game than trade - and nostalgia beats complexity when introducing scary new technology
  • From Binance to NYSE: This cycle's institutional meta and why crypto gaming hasn't figured out Wall Street yet
  • The new Renaissance: How fractional reserve banking created the actual Renaissance, and why crypto's lasting impact will be cultural, not financial
  • Loyalty programs vs. helicopter money: Evolving from infinite money glitches to targeted behavioral incentives
  • 70+ economic experiments: From AI-powered tanuki battles to on-chain "Runescape" - why only one or two need to work
  • The cypherpunk optimism: Why crypto offers a more definite, grounded vision for the future than AI or robotics


Where to find...

Jeff 'Jiho' Zirlin:

Skymavis:


Axie 


Ronin


David Phillips:


In This Episode, We Cover


(00:00) From 300 to thousands of Users: The Binance Effect

(17:41) Community-Driven Growth: The Role of Guilds

(18:38) Experimentation as a Growth Strategy

(19:52) Challenges and Advantages in Crypto Growth

(20:03) Learning Through Gaming: Onboarding to Crypto

(21:27) The Uniswap Airdrop: A Catalyst for Growth

(22:18) Onboarding and Scaling in Crypto Gaming

(23:17) The Ronin Network: A Solution for Scalability

(24:40) The Evolution of Ronin and Its Community

(25:10) Expanding the Ronin Ecosystem: New Games and Innovations

(27:02) Economic Experiments in Crypto Gaming

(28:56) The Cultural Renaissance of Crypto

(30:14) Future Innovations in Web3 Gaming

(31:36) Optimism for the Future of Crypto

Brought to you by:

Fondo — All-in-one accounting for startups: https://tryfondo.com

Parthi Loganathan: Beyond Cold Outbound - How Letterdrop Transforms Intent Signals Into Revenue Opportunities23 Sep 202500:31:16

Parthi Loganathan is the founder and CEO of Letterdrop, a Y Combinator-backed startup that helps B2B companies build pipeline by focusing on the warmest leads and people who are actually in market. Since launching Letterdrop, he's helped companies move beyond saturated email and cold calling tactics to identify prospects who want to talk and send them highly tailored messaging. The platform analyzes public conversations, CRM data, and sales calls to segment buyers and enable personalized outreach without relying on high-volume approaches.


In this episode, we explore the fundamental shift happening in B2B sales as traditional cold outbound becomes less effective and companies invest in higher-effort tactics to stand out. The conversation covers the evolution from Letterdrop's origins as an SEO tool to its current focus on conversation intelligence, driven by market changes from ChatGPT's emergence. Parthi shares insights about the three essential components of effective outbound messaging, why customer conversations represent untapped content goldmines, and his firsthand experience being demoed by an AI sales agent. We also examine his predictions about AGI's timeline and the philosophical question facing all founders: do you build for today's market or tomorrow's technological reality?


Key topics covered:

  • Why cold email reply rates dropped 40% in 2024 and the shift away from "spam your TAM" tactics
  • The reality that only 2-3% of your market wants to purchase at any given time
  • Three components of effective outbound: solid observation, poking the P0 problem, and value-first offers
  • Letterdrop's strategic pivot from SEO tools to conversation intelligence as ChatGPT emerged
  • How customer and prospect conversations contain unique content that competitors can't replicate
  • The founder journey from Google product manager through multiple micro-SaaS startups to YC
  • Real experience with an AI AE conducting demos better than human salespeople
  • Why "marinating" in a single problem space beats jumping between different markets
  • The philosophical choice between building Cursor (for today) versus Anthropic (for the future)
  • AGI timeline predictions and whether UBI will arrive before widespread job displacement

Where to find Parthi Loganathan:


Linkedin: https://www.linkedin.com/in/parthiloganathan/

X: https://x.com/parthi_logan


Where to find Letterdrop:


Website: https://letterdrop.com/

Linkedin: https://www.linkedin.com/company/letterdrop/

X: https://x.com/letterdropco

Podcast: https://open.spotify.com/show/43bSCi3FcFaJ28H7qEK59X?si=2f6afe15cea342ea

Where to Find David Phillips:

X: https://x.com/davj

LinkedIn: https://www.linkedin.com/in/davjphillips/


In This Episode, We Cover


(00:00) Introduction to LetterDrop and Its Mission
(02:52) The Evolution of Outbound Sales Strategies
(06:11) Crafting Effective Outbound Messages
(09:09) Parthi's Journey as a Founder
(12:02) Leveraging Social Conversations for Sales
(14:59) Creating Content from Customer Conversations
(17:55) Back Office Operations for Startups
(20:49) The Role of AI in Sales
(23:38) The Future of Work: AGI and UBI
(26:46) Closing Thoughts and Future Questions


Brought to you by:

Fondo — All-in-one accounting for startups: https://tryfondo.com


🎧 START pod: Tejas Bhakta, Founder & CEO , Morph "Subagents and tools that improve coding agents"27 Mar 202600:20:15

Agents don’t need bigger models. They need better tools.

Morph trains coding subagents.
Not for humans. For frontier models.


Fast Apply edits at 10,000 tokens/sec.
WarpGrep handles code and log search.


Both keep the main model’s context clean

Because when context gets too large, performance drops.


Now Morph is pushing coding subagents even faster.

One newer model runs at 33,000 tokens/sec: https://docs.morphllm.com/sdk/components/compact


🎙️ Tejas Bhakta, Founder & CEO, Morph

01:30 Fast Apply + WarpGrep
02:26 Context fills up around 100k
02:38 Keep the main model context clean
03:31 “You can’t scale human attention 100x”
07:28 Founders are missing how to value human attention
08:30 New model at 33,000 tokens/sec
10:08 Better, faster, and cheaper than the frontier

John Paul Mussalli: How One EMT's Scrappy Prototype Evolved Into an AI Tool That Won Over 20% of NYC's EMTs16 Sep 202500:21:03

In this episode, I sat down with John Paul Mussalli, the co-founder and COO of CareSwift, a Y Combinator-backed startup building AI-powered software to streamline documentation for EMT workers. 

JP and his cofounders brings a unique blend of technical expertise and entrepreneurial drive to the healthcare technology space, having previously worked across diverse fields from real estate automation to web development. 

Since co-founding CareSwift, he's helped scale the platform to serve over 2,000 EMTs in New York City alone, generating more than 90,000 automated reports. Beyond product development, JP leads go-to-market strategy and is currently pursuing EMT certification himself to deepen his understanding of the industry's challenges.

In this episode, we explore the journey from scrappy prototype to venture-backed startup and the critical lessons learned along the way. 

Key topics covered:

  • How a ChatGPT prototype evolved into a venture-backed healthcare AI platform
  • The hidden costs of poor EMT documentation: $1,800 per error and 11% industry revenue loss
  • Why 25% of New York's EMTs organically adopted CareSwift without marketing
  • Critical incorporation mistakes that can delay funding and how to avoid them
  • The strategic decision to expand from narrative reports to full documentation workflow
  • Why domain expertise matters when building AI for specialized industries
  • Navigating regulatory compliance and the founder stack for healthcare startups
  • The reality of Y Combinator: 996 work culture and rapid iteration cycles
  • From 15-20 minute reports to 2-minute automated workflows saving hours per shift
  • Why sometimes a bug in Apple Mail can redirect your entire startup journey


Where to find John Paul Mussalli 


- Linkedin: https://www.linkedin.com/in/jpmussalli/
- X: https://x.com/jpm1126


Where to find CareSwift:


- Website: https://careswift.ai/

- Linkedin: https://www.linkedin.com/company/careswift/

Where to Find David Phillips:

- X: https://x.com/davj

- LinkedIn: https://www.linkedin.com/in/davjphillips/


In This Episode, We Cover


(00:00) Introduction to CareSwift and Its Founders

(02:54) The Birth of CareSwift: Addressing EMT Challenges

(06:09) Impact of CareSwift on EMT Efficiency

(09:01) Navigating the Startup Journey: Lessons Learned

(09:35) Navigating Startup Structures and Legalities

(12:14) The Journey Through Y Combinator

(15:06) Daily Life as a Founder in Y Combinator

(17:13) Building a Founder Stack: Tools and Resources

(18:57) Future Plans

Brought to you by:

Fondo — All-in-one accounting for startups: https://tryfondo.com


Reuben Torenberg: Inside SF's Office Market Comeback: Deals, Trends & AI Company Growth12 Sep 202500:27:38

Reuben Torenberg is a Senior Vice President at CBRE, the world's largest commercial real estate services firm. Reuben specializes in helping startups in San Francisco navigate the complex and rapidly changing office leasing landscape. Since joining CBRE in 2014, he's represented some of the biggest names in tech - including Airbnb, Coinbase, Cruise, and Dropbox - and is widely known as the go-to broker for early-stage startups and growth-stage companies alike. Beyond real estate, Reuben is also a community builder, having founded SF Hoops and SF Links, two of the city's most exclusive and founder-heavy social sports leagues.

In this episode, we explore the dramatic transformation of San Francisco's commercial real estate market and the evolving dynamics between landlords, tenants, and the broader tech community. The conversation delves into current market trends in both office and retail spaces, examines how AI companies are reshaping demand patterns, and discusses the critical importance of community building in the tech industry through initiatives like SF Hoops. We also dive deep into pricing strategies, emerging market opportunities, and provide a comprehensive outlook for businesses seeking space in San Francisco.


Topics covered:

  • Why SF's commercial real estate recovery is finally here after 5 years of decline
  • How AI companies are driving massive demand and changing the market dynamics
  • Where to find the best deals: neighborhood analysis and sweet spot sizing (10-20K sq ft)
  • Why rents are rising and landlords are getting more confident by the day
  • Buildings selling at 80% discounts and what it means for new opportunities
  • The return-to-office mandate trend and its impact on space demand
  • Lower SoMa as the last frontier for deeply discounted office space
  • Retail space conversion opportunities in Union Square
  • Why you should secure space now vs. waiting for better deals
  • Pricing breakdown: what 10, 25, and 50-person companies should budget
  • How to navigate the search process and when to use a broker
  • & Much more


Where to Find Reuben Torenberg:

CBRE: https://www.cbre.com

X: https://x.com/RTorenberg021

LinkedIn: https://www.linkedin.com/in/reuben-torenberg-b985b646


Where to Find SF Hoops:
https://sfhoopsleague.com

https://x.com/SFHoopsleague


Where to Find David Phillips:

X: https://x.com/davj

LinkedIn: https://www.linkedin.com/in/davjphillips/


In This Episode, We Cover

(00:00) Current Trends in San Francisco Commercial Real Estate

(02:53) Navigating the Market: Opportunities and Challenges

(05:54) The Shift in Office Space Demand

(08:43) Retail Space and Its Transformation

(11:55) Landlord Strategies and Market Dynamics

(14:52) The Rise of SF Hoops: Networking Through Sports

(17:59) Future Outlook: What to Expect in the Coming Months

Brought to you by:

Fondo — All-in-one accounting for startups: https://tryfondo.com

Stephen Llevano: The Founder Journey, Startup Surprises, and Takeaways for Every Founder03 Sep 202500:31:18

Stephen Llevano is the founder and CEO of Capabuild, a software platform designed for restoration contractors who work on insurance jobs. Capabuild helps these businesses manage compliance, streamline field documentation, and create accurate estimates — fast.


In this episode, Stephen shares the full story behind Capabuild: how it started, what he got wrong early on, and the key insights that helped turn it into a real business.

One of the biggest takeaways? The power of watching customers work in their real environment — instead of relying on what they say they need.

We dive into how observing contractors in the field led to unexpected product decisions, how Capabuild evolved its pricing model after early pushback, and what it takes to build trust in a traditional, change-resistant industry.

Stephen also shares his thoughts on building for overlooked markets, supporting local service businesses, and why long-term traction comes from delivering real operational value — not chasing trends or vanity metrics.

If you’re building software for non-obvious industries or trying to unlock early traction, this episode is packed with practical, hard-earned wisdom.


Check out Capabuild:


This episode is brought to you by:

  • Fondo — Automate your accounting and unlock up to $500k from the IRS: tryfondo.com

Where to find Stephen Llevano


Where to Find David Phillips


Takeaways

  1. Connecting directly with customers as a founder is crucial for product success
  2. Observing customers in their actual work environment reveals true needs beyond feedback
  3. Pricing strategies must evolve based on real customer insights and market dynamics
  4. Building a startup requires more time and emotional investment than initially expected
  5. The insurance industry is shifting, creating new opportunities for adaptive contractors
  6. Personal relationships often drive initial customer acquisition and business development
  7. Deep market understanding is essential for navigating industry complexities
  8. Operational efficiency directly impacts a contractor's ability to serve clients effectively
  9. Supporting local service businesses creates stronger community economic foundations
  10. Every entrepreneurial experience offers valuable learning opportunities worth embracing


Chapters

  • (00:01) The Entrepreneur's Journey
  • (03:03) Identifying Market Opportunities
  • (05:55) Building the First Version of Capabild
  • (08:51) Customer Acquisition and Pricing Strategies
  • (11:57) The Evolution of Capabuild
  • (20:56) Operational Challenges and Solutions
  • (23:51) Future of the Industry and Capabild's Mission
Saving Startups Millions, R&D Credit Deep Dive, and Breaking Down the Big Beautiful Bill: Jake Wedig15 Aug 202500:39:42

Jake Wedig is the Director of Tax at Fondo, where he helps startups navigate complex tax legislation and maximize their tax benefits. With deep expertise in startup tax strategy, Jake specializes in R&D tax credits, Section 174 compliance, and helping growing companies optimize their tax positions while managing cash flow challenges.

In this conversation, Jake breaks down the recent changes in tax legislation that every startup founder needs to know about, particularly the game-changing provisions in the One Big Beautiful Bill and how startups can leverage R&D tax credits to get substantial cash back on their development investments.


We explore the challenges that Section 174 has created for startups and dive into practical strategies for navigating these changes, including when amending tax returns makes sense and how to leverage bonus depreciation and Section 179 deductions. Jake also explains the powerful long-term benefits of Qualified Small Business Stock (QSBS) for founder wealth optimization.


Key topics covered:

  • How the One Big Beautiful Bill creates new tax optimization opportunities for startups
  • Maximizing R&D tax credits for substantial cash returns on development investments
  • Navigating Section 174's impact on R&D expense deductions and cash flow management
  • Strategic use of amended returns to recover from unexpected tax positions
  • Leveraging bonus depreciation and Section 179 for immediate equipment deduction benefits
  • Understanding QSBS benefits and the five-year holding period requirements
  • The importance of proactive tax planning partnerships between startups and advisors
  • Staying ahead of evolving tax legislation to capture emerging opportunities
  • And much more

Brought to you by:

Where to find Jake Wedig

Where to Find David Phillips

In This Episode, We Cover

  • (01:42) Understanding the New Tax Bill
  • (03:31) R&D Tax Credits and Their Importance
  • (07:51) Impact of Section 174 on Startups
  • (13:05) Amending Returns and Cash Flow Considerations
  • (16:38) The Role of Tax Advisors for Startups
  • (30:55) Bonus Depreciation and Section 179
  • (35:23) Qualified Small Business Stock (QSBS) Benefits
Nathan Latka: Bootstrapping to $2M ARR, Turning Down $6.5M, and Funding 500+ Startups05 Jun 202500:18:29

Nathan Latka is the founder and CEO of Founderpath, a fintech platform that has deployed nearly $200 million in non-dilutive capital to 500+ software companies. He’s also the creator of GetLatka, a massive SaaS database built off the back of his top-ranked Latka podcast, where he’s interviewed thousands of founders. Nathan’s entrepreneurial journey began at 18 with the launch of Heyo, a Facebook fan page SaaS tool he bootstrapped to $2M in ARR before raising venture capital and eventually exiting.

In this conversation, Nathan shares hard-earned lessons from building and exiting companies, explains why most founders don’t understand the true cost of raising VC, and offers a compelling case for why debt and secondaries can be a smarter option. We also explore:

  • How he bootstrapped Heyo to $2M ARR before raising VC
  • The $6.5M exit offer he had to turn down (and regrets)
  • What most founders misunderstand about venture capital
  • How GetLatka became the #1 ranked SaaS benchmarking database
  • Why the future belongs to tiny teams with huge revenue
  • The three AI trends shaping SaaS company formation
  • How FounderPath prices startup equity daily—instantly enabling secondaries
  • Why hooks and attention matter more than ever
  • And much more

Brought to you by:

Where to Find Nathan Latka

Where to Find David Phillips

In This Episode, We Cover

  • (00:00) Intro to Nathan and FounderPath
  • (01:30) The story behind Heyo and bootstrapping to $2M ARR
  • (03:50) Raising venture and losing optionality
  • (05:30) The $6.5M offer and why his board said no
  • (07:10) Lessons from a slow death and how to move on
  • (08:15) Why Nathan started the Latka podcast
  • (09:30) Building GetLatka to 3,000+ daily organic clicks
  • (11:00) The power of hooks and attention in modern SaaS
  • (12:45) Inside FounderPath: non-dilutive capital for SaaS
  • (14:30) How venture debt differs from traditional VC
  • (16:15) Why secondaries are healthy, not harmful
  • (18:00) How FounderPath prices startup equity daily
  • (20:10) Big trends: tiny teams, chat-based dashboards, attention > tech

Referenced

Selling Before You’re Ready: How Early Stage Founders Close Their First Customers27 May 202500:41:34

Ajith Govind and Avinash Joshi are the co-founders of Cactus, an AI copilot for solopreneurs such as private chefs and caterers, helping them streamline admin tasks and grow their business. Brian Kuan, Community Manager at Vanta, hosted the conversation. Together, we explore early-stage sales, building trust, and the YC network's unique power to catalyze startup momentum. In this episode, we discuss:

  • Why founder-led sales is irreplaceable
  • Leveraging Bookface and social media for early traction
  • Building trust with SMBs and solopreneurs outside your network
  • Cold outreach tactics that actually worked
  • Why you should launch even a half-baked product
  • The underestimated power of urgency in early sales
  • Stories behind onboarding first customers at Fondo and Cactus
  • The emotional moments that proved they were building something impactful
  • How fundraising and selling are deeply intertwined
  • Much more

Brought to you by:


Where to Find David Phillips

Where to Find the Guests:


Brian Kuan (Vanta, W18)

Ajith Govind (Cactus, X25)

Avinash Joshi (Cactus, X25)

Where to Find the Companies

In This Episode, We Cover

  • (00:00) Introductions and what each company does
  • (03:12) How Fondo found its first customer through a cold DM to Sam Parr
  • (05:40) How Cactus began by solving a personal need with personal chefs
  • (09:05) Using Bookface to unlock growth
  • (13:00) Tips for selling to startups and SMBs
  • (16:45) How product-led growth and founder empathy drive traction
  • (20:18) Balancing building with selling as a founder
  • (25:12) Founder-led sales vs. traditional sales teams
  • (28:00) How trust is built—especially outside your network
  • (32:40) Lightning Round: first big sales wins, boldest cold DMs, best YC perks
  • (38:35) Sales tactics they wish they knew on Day 1
  • (41:00) Fundraising urgency and investor psychology

Referenced

From Overpriced to Undervalued: Why Now is the Time for Startups to Get in on SF's Real Estate Deals20 May 202500:35:57

Reuben Torenberg is a First Vice President at CBRE, the world’s largest commercial real estate services firm. Reuben specializes in helping startups in San Francisco navigate the complex and rapidly changing office leasing landscape. Since joining CBRE in 2014, he's represented some of the biggest names in tech — including Airbnb, Coinbase, Cruise, and Dropbox — and is widely known as the go-to broker for early-stage startups and growth-stage companies alike. Beyond real estate, Reuben is also a community builder, having founded SF Hoops and SF Links, two of the city’s most exclusive and founder-heavy social sports leagues.

In this episode, we dive into the state of commercial real estate for startups in 2025, including:

  • Why SF is now a tenant’s market — and what that means for startups
  • How to find cheap, high-quality office space (and avoid costly mistakes)
  • How much space your startup really needs at each stage
  • Why brokers are free for tenants — and why every founder should use one
  • Where the best startup neighborhoods are in SF right now
  • How coworking has evolved — and why it's a smart move for teams <10
  • What landlords are offering in TI (tenant improvement) allowances today
  • How much to offer below list — and why you should always send multiple proposals
  • The return of Class A space and what’s happening in Mission Bay, Hayes Valley, and Jackson Square
  • Much more

Brought to you by:

Where to Find Reuben Torenberg

Where to Find David Phillips

In This Episode, We Cover

  • (00:00) Intro to Reuben and CBRE
  • (01:30) From sports to real estate: Reuben’s career path
  • (03:15) Lessons from Custom Spaces and early startup deals
  • (04:50) Major tenants Reuben’s worked with: Airbnb, Coinbase, Cruise
  • (06:30) How SF Hoops became a startup founder hub
  • (08:05) SF Links and the evolution of social networking for tech
  • (09:40) How startups actually find space in SF
  • (11:00) What tenant brokers do and why they’re free
  • (13:00) Square footage per employee and planning for growth
  • (15:00) COVID's impact: SF market shift explained
  • (17:30) Class A space demand and the "flight to quality"
  • (19:45) Leasing terms, TI allowances, and negotiation tips
  • (23:00) Market insights from Q1 2025: 2.9M sq ft leased
  • (25:15) Hottest neighborhoods: Mission Bay, Jackson Square, and beyond
  • (28:00) Best advice for founders raising and scaling: flexibility, furnished space, subleases
  • (30:00) Budgeting by headcount: ballpark lease costs for 5, 10, and 25-person teams
  • (32:00) Final takeaways and next steps

Referenced

He Built Mafia Wars to $10M a Day and Now Makes Bets on 130+ Startups05 May 202500:37:28

Roger Dickey is a serial entrepreneur and prolific angel investor with over 130 startup investments under his belt. From humble beginnings coding games as a kid to building Mafia Wars at Zynga—a game that reached a $300 million annual run rate—Roger has scaled multiple companies and exited to giants like Zynga, Home Depot, and private equity. He's also pioneered the "search lab" approach to company building, a structured yet high-velocity process for launching and validating startup ideas. In this episode, we cover:

  • Roger’s early obsession with coding and games
  • How Dope Wars turned into a breakout Facebook game success
  • The origin and explosive growth of Mafia Wars at Zynga
  • Building a startup that scaled to $100K/day in revenue
  • The matrix method for startup idea generation
  • Why distribution, not code, is today’s biggest moat
  • Why he believes in going deep on one growth channel
  • Lessons learned from two successful search labs
  • The importance of knowing when a product isn't working
  • What he's exploring now across SaaS, games, and social
  • Much more

Brought to you by:

Find the transcript at: https://www.tryfondo.com/podcast (or wherever you're hosting it)

Where to Find Roger Dickey

Where to Find David Phillips

In This Episode, We Cover

  • (00:00) Intro and Roger's startup credentials
  • (01:04) Roger’s coding origin story and first “viral” product
  • (05:01) How Dope Wars exploded on Facebook
  • (10:45) Building and scaling Mafia Wars at Zynga
  • (16:00) Product-led growth mechanics and viral loops
  • (21:00) Inventing and reinventing distribution
  • (25:35) How Roger structured his “search lab” process
  • (31:00) Metrics and mindset for early-stage validation
  • (34:55) CAC, LTV, and cracking the S-curve of growth
  • (38:47) Scaling a $100K/day construction tech startup
  • (44:10) The role of deep focus vs. testing across channels
  • (48:05) What Roger’s building next and how he’s thinking about it

Referenced

Fresh Blood in Old Insurance: How Vouch Built a Business Revolutionizing Startup Coverage28 Apr 202500:40:11

Travis Hedge is the co-founder and Chief Revenue Officer of Vouch, an insurance platform purpose-built for high-growth technology companies. After growing up around a family-owned insurance agency in Columbus, Ohio, Travis spent his early career at Nationwide Insurance and SVB Capital, where he saw firsthand the gaps in insurance for startups. He co-founded Vouch in 2018, and in just a few years, the company has scaled to nearly 6,000 customers. In our conversation, we dive into:

  • How Travis’s third-grade dream of becoming an insurance agent turned into a mission-driven startup
  • The critical moment that pushed him to found Vouch
  • The importance of founder-led sales and getting your first 20 customers
  • Why partnerships alone won't get you early traction
  • How Vouch built a full-stack insurance platform versus being a digital broker
  • The go-to-market lessons learned from Utah to nationwide expansion
  • How early hiring mistakes shaped Vouch’s sales strategy
  • How Travis thinks about demand generation and balancing inbound and outbound
  • Why domain expertise is essential in evaluating AI vendors
  • The inflection points that changed how Vouch scaled
  • How AI will reshape insurance but not eliminate the human element
  • Much more

Brought to you by:

Where to Find Travis Hedge

Where to Find David Phillips (Host)

In This Episode, We Cover

  • (00:00) Introduction to Travis and Vouch
  • (01:20) Travis’s early inspiration from his family's insurance business
  • (05:00) Lessons from Nationwide and SVB Capital
  • (10:30) The painful moment that sparked Vouch’s creation
  • (14:00) Building a startup insurance platform from scratch
  • (19:00) Getting the first 20 customers without relying on partners
  • (23:00) Lessons in early hiring and go-to-market team building
  • (27:00) How demand gen strategy evolved
  • (33:00) AI’s real role in insurance and go-to-market
  • (38:00) Big revenue and customer milestones
  • (43:00) How Vouch now serves both seed-stage startups and late-stage scale-ups
  • (47:00) How insurance mistakes can cost startups millions
  • (51:00) The best time for founders to get insurance
  • (56:00) Closing thoughts and Travis’s advice to founders

Referenced

Amazon's New Nemesis: How a 21-Year-Old Hit $1M ARR By Gaming Big Tech Engineering Interviews07 Apr 202500:24:06

Roy Lee is the 21-year-old founder and CEO of Interview Coder a breakout startup that has taken the internet by storm. In one year, Roy went from having his Harvard acceptance rescinded to building an AI tool used by thousands of aspiring developers to land jobs at companies like Amazon, Meta, and TikTok. His story — marked by risk-taking, resilience, and relentless building — has captivated millions on social media and sparked a firestorm of controversy in academia and Big Tech alike.

In this episode, we cover:

  • Why Roy's Harvard acceptance was rescinded, and how he bounced back
  • How a year of isolation turned into a coding bootcamp of one
  • Why community college is underrated — and how it shaped Roy’s founding team
  • How Interview Coder went from MVP to $10K MRR in a few months
  • The Amazon interview video that triggered a firestorm at Columbia
  • How going viral led to threats of expulsion — and Roy’s strategic response
  • Why Roy believes controversy is essential for attention
  • How the Z Fellows program changed his trajectory
  • A sneak peek into Roy’s new startup: Pike
  • Much more

Brought to you by:

  • Fondo — All-in-one accounting platform for startups. Bookkeeping, taxes, and cash back from the IRS: https://trifondo.com

Where to Find Roy Lee

Where to Find David Phillips

In This Episode, We Cover

  • (00:00) Welcome and intro
  • (01:05) Roy's Harvard saga and forced gap year
  • (03:00) Learning to code in isolation
  • (05:10) Attending community college and meeting co-founders
  • (07:00) Transferring to Columbia and launching Interview Coder
  • (08:00) Building a viral-first product in 4 days
  • (10:20) The MVP, tech stack, and early traction
  • (12:00) Using the tool to land offers from Amazon, Meta, and more
  • (13:30) Turning open source into $10K MRR
  • (15:00) The infamous Amazon video and Columbia’s response
  • (17:30) Leveraging virality to fight institutional pressure
  • (19:30) Controversy and creator growth strategy
  • (20:40) Getting into Z Fellows and its impact
  • (22:00) Roy’s new startup: Pike
  • (23:30) What's next and where to follow along

Referenced


🎧 START pod: Pamir Ehsas, CEO & Co-Founder, Arcline "AI-native legal services for startups"25 Mar 202600:15:02

Pamir Ehsas spent years as outside counsel serving startups. 


He saw the same problem on repeat


Simple legal work took weeks. Pricing was opaque. Lawyers kept starting from scratch instead of using AI


So he built Arcline. 


AI generates the first draft. Elite lawyers from the best firms, and schools (Harvard, Oxford etc.) do the final revision


Up to 80% of the work gone. Same-day turnaround (Try getting that from a traditional law firm) 


50+ venture-backed startups already onboard when this ep was recorded


Most legal AI tries to replace the lawyer. Pamir replaced the busywork

02:09 “Fondo, but for legal” / AI-native legal for startups
03:12 Sold AI to law firms first; then pivoted to end users
04:52 Why Arcline uses experienced lawyers, not junior lawyers
05:43 Faster, higher-quality work — including complex matters
07:00 Big Law was slow; incentives were broken
07:36 Why going direct creates the data loop to improve AI
08:34 AI does the grunt work; lawyers create trust
11:08 What startups actually come to Arcline for
12:26 The long-term vision: legal advice at your fingertips

Three Startups, $70M Raised, and One Successful Exit02 Apr 202500:46:34

Jay Reno is the founder and CEO of PointHound, a free platform helping hundreds of thousands of people earn and redeem credit card points for maximum value—often unlocking free business class flights. But Jay’s journey started long before PointHound. He previously founded Feather, a furniture subscription startup that redefined how millennials furnish their homes. Under Jay’s leadership, Feather scaled to $15M in annual recurring revenue, raised over $70M in funding, and was ultimately acquired in 2022.

In this conversation, Jay and David dive deep into the full founder arc—from early failures to scaling a venture-backed operation—and everything he's applying to his new startup. They discuss:

  • How Jay lost his life savings on his first company—and what he learned
  • The origin story behind Feather and the cold email that changed his life
  • How Feather scaled from a duct-taped operation to $15M in ARR
  • The operational challenges of running a semi-vertical logistics business
  • Why the pandemic forced a complete shift in strategy
  • What it’s like raising capital when everything looks perfect—but still isn’t easy
  • How to build loyalty and change consumer behavior with time
  • Why most people are wasting their credit card points—and what to do instead
  • How PointHound helps anyone fly business class for free
  • The cards Jay wishes he used while running Feather
  • What Jay learned going through YC… twice
  • Much more

Brought to you by:

  • Fondo — Your all-in-one accounting platform for startups. Bookkeeping, taxes, and R&D credits, on autopilot. https://tryfondo.com
  • PointHound — Redeem credit card points for free flights. No guesswork, just travel. https://pointhound.com

Find the transcript at: Startup Growth Podcast

Where to Find Jay Reno

Where to Find David Phillips

In This Episode, We Cover

  • (00:00) Introduction and welcome
  • (01:22) Jay’s first founder punch with his grocery delivery startup
  • (03:06) Early lessons from failure and jumping into Feather
  • (04:43) Starting Feather and how the West Elm deal happened
  • (06:55) Applying to YC from a pizza shop Wi-Fi
  • (08:59) Feather’s scrappy early operations—manual delivery and DIY logistics
  • (13:14) Raising a $3.5M seed and hitting 7% week-over-week growth
  • (19:46) Operating out of a chaotic Dumbo retail space
  • (22:34) Discovering a B2B growth channel and building a team
  • (26:48) The surprising difficulty of raising a Series A
  • (30:22) Closing a $30M warehouse line to unlock scale
  • (33:20) How COVID froze growth and forced strategy shifts
  • (36:02) Selling Feather to Vesta in 2022
  • (37:03) Jay’s time in VC and why he returned to building
  • (38:53) The pain of points mistakes and the birth of PointHound
  • (40:20) The best (and worst) credit cards for startups
  • (41:51) Making points redemption 10x easier and smarter
  • (43:40) Getting PointHound’s first users through Reddit and Bookface
  • (45:32) Final thoughts and where to find Jay

Referenced

He Bought a College to Fix Higher Ed — Tade Oyerinde’s $100M Vision25 Mar 202500:35:37

Tade Oyerinde is the founder and chancellor of Campus, a revolutionary online community college reimagining access to higher education. Starting with viral dorm-room startups, Tade’s journey took him from building UniRoulette and CampusWire to acquiring an accredited college and launching Campus. Today, Campus serves over 2,000 students, employs 240+ staff, and has raised $100M+ in venture capital, all while helping students graduate debt-free.

In this conversation, Tade shares the winding path to building Campus, including:

  • Building viral products from a college dorm
  • Pivoting away from unsustainable growth and recognizing false signals
  • Learning the limitations of synchronous social platforms
  • Discovering the adjunct professor pay gap—and turning it into a wedge
  • The insight that top professors teach at community colleges too
  • Why he acquired a college instead of starting one from scratch
  • Building custom education software from the ground up
  • Raising capital from Sam Altman, Jason Citron, and General Catalyst
  • Why Campus prioritizes human support over AI
  • Much more

🔑 Key Takeaways

  • Viral ≠ Valuable: Tade learned early that virality alone doesn’t lead to retention or sustainable business models.
  • Adjuncts are the secret weapon: Many top professors are adjuncts—underpaid and overlooked—yet open to better platforms.
  • Perception ≠ quality: Community colleges often offer courses from the same professors as elite schools, but carry social stigma.
  • Build infrastructure, not integrations: Campus runs fully on internally built tools for instruction, administration, and student support.
  • Debt-free college is viable: Through Pell Grants and optimized economics, 86% of Campus students pay $0 out-of-pocket.
  • Support at scale is human-powered: Every 50 students are supported by a real advisor, counselor, or coach—not AI.
  • Raising was milestone-driven: Capital was unlocked at each inflection point—acquisition, accreditation, first students, scaled cohorts.
  • Skepticism is a superpower: Having experienced the hype-crash cycle before, Tade built Campus with deliberate, durable conviction.

Brought to you by:

Where to Find Tade Oyerinde

Where to Find David Phillips (Host)

In This Episode, We Cover

  • (00:00) Intro to Tade and the Campus vision
  • (01:35) The Tade origin story: homeschool, aerospace, and building UniRoulette
  • (03:45) Going viral and raising a seed round in London
  • (05:55) The retention issue with synchronous social apps
  • (07:15) Pivoting into mobile apps for universities
  • (09:35) Building CampusWire and avoiding enterprise sales
  • (11:05) Cold emailing 1M professors to grow
  • (12:45) How COVID created a head-fake spike
  • (14:20) Discovering the adjunct pay gap
  • (15:35) The insight that UCLA profs teach at community colleges too
  • (16:25) Why community college students weren’t retaining
  • (18:10) Walking away from CampusWire to start Campus
  • (19:45) Meeting Ralph Wolff, and the plan to buy a college
  • (21:10) How Tade raised to acquire an accredited school
  • (23:05) The challenge of buying a college as a dropout
  • (24:40) Getting the first students and launching Campus
  • (26:10) Making college free via Pell Grants
  • (27:40) The impact of improving retention on gross margins
  • (29:10) Building all the software from scratch
  • (30:10) Campus’ live class model and top professors
  • (31:05) Hiring a full-time human for every 50 students
  • (32:10) Lowering CAC from $15K to sustainable levels
  • (33:50) Unlocking funding across inflection points
  • (35:10) What’s next for Campus

Referenced
UniRoulette (inspired by ChatRoulette):
https://en.wikipedia.org/wiki/Chatroulette

The Social Network (Film):
https://www.imdb.com/title/tt1285016/

Clubhouse liquidity challenges:
https://www.nytimes.com/2021/07/11/style/clubhouse-app-decline.html

Andreessen Horowitz's investment in Clubhouse:
https://a16z.com/2021/01/24/investing-in-clubhouse/

CampusWire (Tade's previous startup):
https://www.campuswire.com/

General Catalyst:
https://www.generalcatalyst.com/

UC San Diego Transfer Admissions:
https://admissions.ucsd.edu/transfer/

FAFSA Application (for Pell Grants):
https://studentaid.gov/h/apply-for-aid/fafsa

From Data Engineer to Meme King: How MEMES Make MILLIONS17 Mar 202500:35:10

In this episode of the Startup Growth Podcast, I sit down with Jason Levin, the founder and CEO of Memelord Technologies. Jason shares his unconventional path—from creating YouTube videos as a kid and ghostwriting for founders to authoring Memes Make Millions and launching a software that empowers companies like HubSpot and Coinbase to create viral memes. Discover how he leveraged newsletter hacks, guest posts, and cold DMs to build an organic growth engine and why starting small can lead to massive success.

Timestamps & Key Topics:
(00:00) – Introduction:
David introduces the episode and welcomes Jason.
(00:49) – Origin Story: Jason recounts his early journey—from making YouTube videos at age 11 to mastering creative software in middle school.
(03:00) – Book Inspiration: Learn how a controversial lyric sparked the idea behind Memes Make Millions.
(04:00) – Transition to Software: Discover how Jason pivoted from ghostwriting to developing meme software that now drives billions of impressions.
(11:00) – Growth Hacks: Insight into how a simple newsletter (“meme alerts”), strategic guest posts, and cold DMs fueled his growth.
(21:00) – Pricing & Iteration: Jason explains his playful pricing strategy (6.9/month) and the value of early user feedback.
(29:00) – Evolving the Product: New features like SMS/Telegram alerts, AI-powered captions, and face swapping innovations.
(33:00) – Final Thoughts: Jason’s parting advice on staying true to your creative vision and the power of humor in branding.

Key Takeaways:

  • Embrace Your Passion: Transform early creative interests into scalable business ideas.
  • Organic Growth Wins: Use persistent, human-driven strategies—like newsletters and cold DMs—to build an engaged audience without relying solely on paid ads.
  • Start Small, Iterate Quickly: A low initial price attracts early adopters and sets realistic expectations for continuous improvement.
  • Focus on Revenue: Prioritize metrics like Monthly Recurring Revenue (MRR) over follower counts to gauge true business success.

Guest Information & Resources:

Brought to you by tryfondo.com:
This episode is proudly sponsored by tryfondo.com – the easy accounting solution that helps startups get their bookkeeping done, file taxes, and claim up to $500k in tax credits effortlessly. Check them out for founder-friendly financial services!

How Kush Patel Built a $25 Million Business from Scratch—And How You Can Too24 Feb 202500:54:42

Kush Patel is the co-founder of App Academy, a pioneering coding bootcamp that introduced the income share agreement (ISA) model to tech education. With a background in finance and a deep passion for unlocking access to opportunity, Kush helped scale App Academy from a modest, bootstrapped startup into a $25 million revenue business with global reach. In this episode, we dive into Kush's entrepreneurial journey, from launching the first free cohort on Hacker News to transforming lives through coding education. We discuss:

  • How growing up with an entrepreneurial father shaped Kush’s mindset
  • His transition from hedge fund finance to tech entrepreneurship
  • The origin story behind App Academy and why the ISA model was revolutionary
  • How Kush scaled the company from 20 students to thousands worldwide
  • The challenges of transitioning from in-person education to online learning
  • Why bootstrapping gave App Academy a competitive edge
  • Leadership lessons from growing a team from zero to over 100 employees
  • His current focus as Board Chair and why he’s investing in personal growth and health
  • Much more

Brought to you by:

Where to Find Kush Patel

Where to Find the Host

In This Episode, We Cover:

(00:21) Entrepreneurial inspiration from family.

(04:49) Coding bootcamp's innovative launch.

(09:46) Selecting students for coding class.

(12:49) Income share agreements in education.

(15:19) Launching and iterating contracts.

(19:04) Growth channels for App Academy.

(23:02) In-person coding bootcamp launch.

(27:17) Continuous product improvement strategies.

(30:39) Hiring for high potential talent.

(35:09) Online education challenges and opportunities.

(36:11) Online education community building.

(42:11) Freemium model and brand equity.

(44:39) Product funnel management strategies.

(49:29) Bootstrapped company growth success.

(51:35) Building a sustainable business.

Referenced:

🎧 START pod: Naman Ambavi, Founder & CEO, Oximy "See and control all AI activity across your enterprise"25 Mar 202600:16:56

An employee used his corporate Gemini account to generate fake receipts for reimbursements

Not because he was lying. He just didn't have the real ones

That's when the CISO realized they needed Oximy

Ask an enterprise how many AI tools they use. They say 10. The real number is probably 40+

Most of the risk isn't malicious. People just want to get things done faster. So customer lists end up on free tools with no DPA

The first instinct is to block everything. But people bypass restrictions anyway

The real question: how do you say yes to AI without losing control?

That's Oximy. A control layer for enterprise AI adoption. Track usage, manage spend, enforce governance

🎙️ Naman Ambavi, Founder & CEO, Oximy on Fondo START pod

00:19 — What Oximy helps enterprises understand and manage
02:24 — From India to the Bay, and the thesis behind Oximy
03:29 — Track adoption, cost, and risk controls
03:52 — “They say they’re using not more than 10… the number goes roughly over 40”
04:22 — Compliance, retraining risk, and why oversight matters
05:10 — Most misuse starts with harmless intent
06:23 — The gap between Silicon Valley and corporate America
07:35 — How to say yes to AI without losing control
10:25 — Why the pain shows up most clearly at 1,000+ employees
12:59 — Why banning AI is the first instinct — and why it doesn’t last

🎧 START pod: Raffi Isanians, Founder & CEO, Mage Legal "Automatic AI M&A Legal Diligence"24 Mar 202600:43:03

Attorneys are trained to spot issues. That’s literally what law school teaches.

Show them your product, and the first thing they’ll say is: “the margin is off on this.”

Every hour they spend learning software is an hour they’re not billing.

Raffi Isanians knows that because he lived it.
Kirkland. Gunderson. Years inside private equity and venture work.

That’s why Mage Legal has a simple standard: if a lawyer opens the product with no instructions and can’t figure it out, "we’re failing"

Comprehensive AI coverage across the entire data room:
red and yellow flags, diligence memos, disclosure schedules, redline comparison. 1,500 documents in tens of minutes. 

All async.

05:15 - Puts a TOS into ChatGPT 3.5, comes back 85-90% there


06:20 - Every hour learning a tool is an hour not billed


08:37 - The product worked, nobody wanted it


09:00 - YC partner on the two-year window


09:53 - AI is an F1 engine in a world of bicycles

13:00 - Clients are pushing AI adoption, not the lawyers


15:19 - The goal is zero behavior change


17:00 - 1,500 documents, diligence memos, tens of minutes


18:22 - One good associate now does the work of six

30:56 - Engineers simplify, lawyers complicate


33:00 - 11PM, picture of his daughter, back to work

40:34 - Simple enough to use with zero instructions

🎧 START pod: Lucas Ngoo, Co-founder & CEO, Cortex AI "The Real World Is the Next Training Ground for Embodied AI"19 Mar 202600:10:46

The internet was the training set for intelligence

Nobody has built the equivalent for the physical world

Previously, Lucas Ngoo co-founded Carousell, scaled it past $1B 

Now at Cortex AI he's collecting the data robotics labs need to train foundation models

Cameras, VR headsets, glasses on factory workers, retail workers, everyday people. Recording real-world manipulation work (Maybe tens of millions, even hundreds of millions of hours)

Not building the robot. Not training the model. Collecting what goes in

2026: scale data in a big way 
2027+: start rolling robots out, 90% teleoperation, 10% autonomy

While humans step in, the system keeps learning

That's the flywheel toward full autonomy

01:38 Cortex as the data layer for general-purpose robotics
02:19 Why text data doesn’t transfer cleanly to the real world
02:51 Recording day-to-day human manipulation work
03:23 “Tens of millions” to “hundreds of millions of hours” of data
06:37 Cortex’s role: “We are really the data piece”
07:28 When humanoids become part of everyday life
08:00 2026 as the year data scales
08:13 90% teleoperation, 10% autonomy
08:37 Data flywheel toward full autonomy
08:55 Synthetic data + real-world data reinforcing each other

🎧 START pod: Gavin Brennen, Cofounder, Lance "The Future of Hospitality"18 Mar 202600:09:14

Some hotel software is still DOS-based. Sometimes pen and paper (that's why guests are waiting 45 mins to get towels)

Gavin's dad has worked at Marriott for the last nine years. When he showed Gavin the old software, that was the spark

Lance builds AI agents that answer calls, handle back office operations, run sales workflows & more

Started with voice, got inside the hotels, and realized how much more they could automate

With coding agents one engineer acts like five

Big contracts need custom solutions. Now they can deliver

🎙️ Gavin Brennen, Co-Founder, Lance (YC W26) on Fondo START pod

01:02 The reality of hotel software
01:53 The insight that sparked the company
02:01 A better way to handle guest requests
02:46 Why Lance had to build desktop agents
03:08 The centralized dashboard layer
04:00 Why hotel problems are highly custom
04:32 One engineer can now act like five
05:51 “Go all in”

Nikhil Reddy, CEO & Cofounder, Arzule "Gong for ecosystem driven growth"18 Mar 202600:12:02

Direct sales reply rates are going down. AI spam is making it worse

Nikhil Reddy saw the shift early: as trust matters more, partnerships become a real revenue channel

Problem is most partnership teams are still running on spreadsheets. They don't know where to focus. Attribution across emails, events, and co-marketing is a mess

Arzule uses CRM data, market signals, and ecosystem signals to help partnership teams discover and prioritize the partnerships that actually drive revenue

Two people building it. Already working with companies generating over $400M in ARR

Applied late to YC's fall batch, never even got a reply. Applied again for winter, got in, and their group partner told them to pivot the next day. That became Arzule

🎙️ Nikhil Reddy, Co-Founder & CEO, Arzule on the Fondo START pod

01:09 What Arzule does and who it's for
02:24 Direct sales is dying. Trust is taking over
02:43 Pivoting mid-batch from multi-agent coordination to partnerships
03:12 Why partnership teams are finally getting their moment
03:54 The data layer: CRM signals, ecosystem signals, company-specific inputs
04:09 Why attributing revenue to partnerships is so hard
05:24 Affiliate links, rev-share, bounties, and contracts in one platform
06:03 What onboarding looks like for larger customers
07:02 Start analyzing everything early, even if it feels relationship-driven
07:48 Tracking signals like new partnership hires and market expansion
08:28 Revenue attribution as the core of predictable partnerships
09:26 Applied late, got no reply, applied again, pivoted the day after getting in
10:02 Move fast and pick something you want to do for 10 years

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