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Built This Week Ep1: How We Built an AI Video Studio in 3 Days
27 Jun 2025
00:42:11
In the debut episode of Built This Week, Jordan Metzner and Sam Nadler walk through how they built Ryz Labs Video Studio — a new internal tool for generating marketing-ready videos using top AI models like Veo 3 and Seed Dance.
They explain how they shipped the first version in just three days using Replit, Replicate, and GPT-4, and how their team used it to produce two full commercials in under 48 hours — without touching a camera.
In this episode:
Why Veo 3 costs $6 for 8 seconds — and how that pricing changes your content strategy
How they enhanced prompts to boost video quality across multiple AI models
What they learned giving everyone on the team shared access to premium video tools
Early roadmap plans for multi-model batch generation and image tools
Why WhisperFlow has become their go-to productivity tool for fast dictation and AI prompting
Built This Week is a podcast about building real tools in real time — focused on AI, product development, and startup hacks that actually ship.
New episodes drop weekly.
Built This Week – The Official Trailer
27 Jun 2025
00:00:53
Welcome to Built This Week — the podcast where we dive into the startups, tools, and wild ideas built in the past 7 days.
Hosted by founders Jordan Metzner and Sam Nadler, each episode features three fast-paced segments:
A brand new project we actually built this week
The coolest new AI tools hitting the market
A breakdown of the top tech stories everyone’s talking about
This show is fast, fun, and raw — whether you’re building, investing, or just curious about what’s next in tech.
Built This Week Ep2: We Built an AI SEO Machine That Writes and Publishes Itself
03 Jul 2025
00:30:51
This week on Built This Week Jordan Metzner and Sam Nadler unveil the AI engine they built to write and publish SEO content across 15 Webflow sites with zero human effort
They break down how they trained each site to sound like a real brand, how the tool runs daily without lifting a finger, and why it's already driving global traffic and leads from search engines and LLMs like Perplexity. They also dive into their new favorite productivity tool Granola and unpack Meta’s talent raid on OpenAI
In this episode • How they built a self-publishing AI SEO machine from scratch • Why voice and images make AI content feel real • How Granola saves their brain on back-to-back interviews • What Meta's OpenAI takeover means for the future of AI power plays • Why Figma’s S1 shows big upside but AI might eat its lunch
Built This Week is a podcast about building real tools in real time. No fluff. No theory. Just AI builds, startup tactics, and weekly drops from the front lines
This AI Platform Lets Anyone in Your Company Manage Operations Without a Single Engineer
29 May 2026
00:23:45
This week on Built This Week we sit down with Wiley Jones, CEO and co-founder of Doss, to demo an AI-native operations platform built for mid-market companies managing the flow of goods, dollars, and data. He incorporated the company a month before ChatGPT existed.
We cover:
What Doss is and why he calls it an Adaptive Resource Platform not an ERP
A live demo of the platform including inventory management, procurement, and order management
How Doss lets companies build their own data model instead of forcing them into the shape of the software
DOSBOT — an AI agent that can self-introspect the entire system and answer complex operational questions
Why switching costs in enterprise software are only relevant if you are talking to the wrong customer
How to identify the 5 to 10 percent of the market that actually wants to move
The ICP — physical product companies doing 20 million to a few hundred million in revenue
News — Robinhood launching AI agents to trade stocks and whether that is innovation or gambling
Whether AI trading bots can actually generate alpha or just raise everyone's tide equally
If you are building in enterprise software, working in operations, or want to understand where AI is taking business systems, this episode is for you.
The AI Product Team Replacement? Inside Autonomy AI’s Live Demo
22 May 2026
00:25:06
This week on Built This Week we sit down with Adir, CEO and co-founder of Autonomy AI, to demo the platform helping enterprise teams build, update, and ship product changes directly on top of their existing codebase.
No slides. Just a live walkthrough of the real product.
We cover: What Autonomy AI is building How non-technical teams can work directly with existing codebases Why the handoff between product, design, and engineering is still broken Building new product views from a simple prompt Connecting AI-generated work to real APIs and pull requests Design mode, Figma-style editing, and mobile responsiveness Why companies are using less Figma and Jira Who is actually buying AI product-building tools Karpathy joining Anthropic and what it means for the space Google’s new AI agents and the future of search
If you are building with AI, managing product teams, or trying to understand how software development workflows are changing, this episode is for you.
AI Is Rebuilding Clinical Trials
07 Mar 2026
00:26:58
Clinical trials are one of the slowest and most expensive processes in modern medicine.
It can take 10–15 years and up to $3 billion to bring a new drug to market — and many trials fail simply because they can’t enroll enough patients.
In this episode of Built This Week, Sam Nadler and Jordan Metzner sit down with Dr. Chadi Nabhan, Chief Medical Officer at RyghtAI, to explore how AI-powered digital twins of clinical trial sites can dramatically improve the speed and success of clinical trials.
RyghtAI has built a platform that creates digital twins of thousands of clinical trial sites worldwide, allowing pharmaceutical companies to instantly identify the best locations and investigators for any given trial.
Instead of relying on manual site selection or reputation-based decisions, AI analyzes historical trial performance, patient demographics, biomarker capabilities, and infrastructure to determine which sites are most likely to enroll patients successfully.
The result: faster trials, better patient representation, and potentially life-saving therapies reaching the market sooner.
In this episode we discuss:
• Why 80% of clinical trials fall behind schedule • Why half of clinical trial sites enroll 0–1 patients • How AI parses 200-page trial protocols in seconds • The role of digital twins in predicting trial success • How AI improves patient diversity in clinical trials • Why biomarker data is becoming essential in modern medicine • How AI agents infer site capabilities from historical trial data • Why informed patients using AI tools may actually improve healthcare outcomes
If AI can dramatically improve the speed and efficiency of clinical trials, it could reshape how quickly new treatments reach patients worldwide.
⏱️ TIMESTAMPS
(0:00) Welcome to Built This Week (0:37) Introducing Dr. Chadi Nabhan from Ryght AI (1:12) What RyghtAI is building (2:14) The problem with clinical trial site selection (3:07) Digital twins for clinical trial sites (4:01) Manual vs AI-driven trial strategy simulation (5:15) Why clinical trials fail (6:03) The massive cost and time of drug development (6:51) How AI identifies the best trial sites (8:00) Ranking clinical trial sites using AI scoring (9:03) Diversity challenges in clinical trials (10:02) Using census data to improve patient representation (10:35) Biomarkers and genomic trial requirements (11:48) Predicting future trial success from past data (12:14) How AI accelerates trial matching (13:04) AI agents reading clinical trial protocols (14:20) Parsing 200-page protocols in seconds (15:00) AI identifying investigators and site contacts (15:57) Helping overlooked clinical sites get discovered (17:47) AI’s expanding role in healthcare innovation (18:00) Eight Sleep raises $50M at a $1.5B valuation (21:09) Apple releases a $599 MacBook (23:00) Dr. Nabhan’s upcoming book: AI and Cancer Care (23:33) Will AI replace Google for patient research? (25:30) The future of personalized AI healthcare (26:10) Final thoughts and wrap-up
AI Is Transforming Construction — We’re Entering a Golden Era
28 Feb 2026
00:27:43
Construction has lagged behind every major industry in technology adoption.
Manual data entry. Spreadsheets. Email-based procurement. Slow invoice approvals. Paper delivery tickets.
That’s finally changing.
In this episode of Built This Week, Sam Nadler and Jordan Metzner sit down with Eldar (Field Materials AI) to break down how AI is automating procurement for commercial and civil contractors — from reading quotes and invoices to verifying pricing, matching delivery tickets, and integrating directly with ERPs.
Field Materials builds AI agents that eliminate manual data entry across the procure-to-pay cycle for electrical, mechanical, concrete, drywall, and other commercial subcontractors working on hospitals, data centers, and billion-dollar infrastructure projects.
We also explore:
• Why construction productivity has barely improved in decades • How AI agents read and process supplier quotes automatically • How foundational model improvements upgrade products overnight • Why procurement automation directly impacts margin • The data center boom forcing construction to modernize • The difference between “adding AI” and building AI-first software • Whether incumbents like SAP and Salesforce are at risk • Why we may be entering a golden era for construction technology
This isn’t theoretical AI.
This is production AI operating inside large-scale commercial construction projects today.
⏱️ TIMESTAMPS
(0:00) Entering the golden era of construction tech (0:24) Welcome to Built This Week (0:43) Introducing Field Materials AI (1:12) What Field Materials actually does (1:41) Scenario modeling demo (BOM shock analysis) (3:51) Pricing intelligence and risk modeling (4:53) How the company started (6:13) Automating quotes, invoices, and delivery tickets (7:23) Who uses Field Materials (commercial subs) (8:49) How procurement actually works today (manual chaos) (10:07) Cutting overhead and scaling without hiring (11:29) Reducing material waste and pricing errors (12:25) Accelerating invoice approval cycles (13:04) AI agents for different document types (14:01) How foundational model upgrades improve the product (15:09) Why construction underinvested in tech (15:52) The data center boom forcing modernization (16:49) AI + robotics + prefabrication (17:31) Anthropic partnerships and enterprise AI integration (18:39) The next wave: AI with “hands” in enterprise systems (19:49) Why incumbents risk building gimmicks (21:07) Salesforce, SAP, and retention vs innovation (24:12) COBOL, modernization, and disruption cycles (26:39) Why building real AI tools is still hard (27:03) Where to find Field Materials
From DNA to Drugs: How AI Is Rewriting Human Biology
21 Feb 2026
00:30:05
DNA is just another language.
In Episode 32 of Built This Week, we sit down with Dov Gertz, founder of Converge Bio, to explore how generative AI is transforming drug discovery.
Every human can be represented as 3.2 billion nucleotides built from four letters: A, C, G, and T. If computers run on zeros and ones, we run on biological code.
Converge Bio is training frontier foundation models on DNA, RNA, proteins, and small molecules — helping biotech and pharma companies design better drugs, faster and cheaper.
We also demo a retro-inspired “Cell Defense Arena” game built for Converge to use at conferences.
Then we pivot into AI infrastructure and agent workflows:
The GPU bottleneck and pharma’s growing demand for compute Why molecular AI is 5 to 10 years behind text models How AI could reduce drug timelines from 10 years to 6 to 8 Why cancer and autoimmune diseases may benefit first The limits of FDA regulation in shortening approval cycles OpenClaw, multi-agent systems, and infinite AI teams Cloud versus on prem in the era of foundation models
The big takeaway:
Chatbots are impressive. But AI applied to biology could extend human life.
If you work in biotech, pharma, AI research, or frontier infrastructure — this episode is for you.
New episodes every Friday.
⏱ TIMESTAMPS
(0:00) DNA as code: 3.2 billion nucleotides (0:32) Welcome to Episode 32 (1:00) Meet Dov Gertz and Converge Bio (2:02) Demo: Cell Defense Arena game (3:25) Converge Bio’s $33M raise and mission (4:05) Foundation models for molecular data (5:00) Turning DNA, RNA, and proteins into machine-readable text (6:02) How transformers apply to biology (7:03) 400x more DNA than text on the internet (8:02) Who Converge’s customers are (9:21) Faster, cheaper, better drug discovery (10:39) The three bottlenecks: data, architecture, compute (12:02) The future of personalized medicine (13:02) Which diseases benefit first: cancer, diabetes, autoimmune (14:00) Regulatory realities and clinical trial timelines (16:30) Will AI shorten drug approval cycles? (17:01) NVIDIA, GPUs, and scaling molecular AI (18:30) Pharma as a new AI infrastructure consumer (19:13) Hard pivot: OpenClaw and agentic AI (21:26) Managing teams of AI agents (22:20) Cloud versus on prem debate (25:02) Why developers must adapt weekly (29:26) Closing thoughts and where to find Converge Bio
How AI Is Replacing 100-Hour Due Diligence (Claude 4.6, Private Equity, and Emblem)
13 Feb 2026
00:25:55
Private equity due diligence used to take hundreds of hours. Now it takes seconds.
In Episode 31 of Built This Week, we sit down with August Kiles, Head of Product at Emblem, to break down how AI is transforming investment funds — from venture capital to growth equity to private equity.
Emblem is building what they call the “last platform investors will ever need” — a system that ingests entire data rooms, extracts financials, compares deals, generates reports in Word, Excel, and PowerPoint, and helps funds get to a “no” faster.
We also demo a portfolio scenario simulation tool inspired by Emblem — showing how macro events like regulatory pressure or liquidity surges could impact a 30-company portfolio.
Then we dive into the latest AI news:
Amazon engineers pushing for Claude Code over internal tools
Why Opus 4.6 is a step-function improvement for coding
How AI is changing software development workflows
Elon Musk’s XAI reorg and what it signals about model competition
The big takeaway:
AI is not eliminating analysts. It’s increasing deal throughput and freeing them to focus on alpha.
If you work in VC, private equity, family offices, or growth equity — this episode is for you.
New episodes every Friday.
⏱ TIMESTAMPS
(0:00) Emblem’s mission: the last platform investors will ever need (0:25) Welcome to Episode 31 (0:55) Meet August Kiles from Emblem (1:28) Building a portfolio scenario simulation tool (2:05) Modeling regulatory pressure across a 30-company fund (3:00) Liquidity supernova scenario explained (4:00) What Emblem actually does for investment funds (5:00) AI-powered due diligence and data room indexing (6:00) From 100 hours of analysis to seconds (7:20) The old way vs the AI-powered way (8:30) Will AI reduce analyst headcount? (9:40) Getting to “no” faster in private equity (10:30) Where Emblem shines: seed vs private equity (12:00) Multi-agent model orchestration inside Emblem (13:00) How new models improved financial modeling (15:00) Amazon engineers pushing for Claude Code (17:30) Step-function improvements in Opus 4.6 (19:00) Coding workflows transformed by new models (21:30) Elon Musk’s XAI reorganization (23:00) Why model quality now matters more than IDE (25:00) Final thoughts and wrap-up
Claude Opus 4.6, Codex 5.3, and the Rise of Multi-Agent AI
07 Feb 2026
00:18:48
The biggest shift in AI isn’t a new model. It’s agents managing other agents.
In Episode 30 of Built This Week, Sam Nadler and Jordan Metzner break down how they’re actually using the latest AI releases — including Claude Opus 4.6 and OpenAI Codex 5.3 — to build real software inside their own workflows.
Jordan walks through a private, fully local AI system built with Claude Code that turns raw 23andMe data, blood work, medications, and personal health inputs into a unified health dashboard. The goal isn’t diagnostics — it’s creating a long-term, living record that surfaces insights doctors don’t easily connect.
Sam then demos an AI-powered personal trainer built using the new Codex desktop Mac app and high-reasoning models. The system adapts workouts rep-by-rep, adjusts volume in real time, and highlights the tradeoffs between fast iteration tools and slower, deeper reasoning workflows.
We close with the biggest AI platform launches of the week:
Anthropic’s Opus 4.6 and Agent Teams
OpenAI Frontier and enterprise AI coworkers
Perplexity’s Council Mode and LLM swarms
The era of one chatbot at a time is over. The new skill is learning how to manage AI agents that manage other agents.
No hype. No abstractions. Just what actually happens when builders use AI on themselves first.
New episodes every Friday.
TIMESTAMPS
(0:00) The shift from single-agent AI to multi-agent systems (0:21) Welcome to Built This Week Episode 30 (1:00) Agenda and why this week matters (1:38) Why Jordan downloaded his 23andMe data (2:30) Turning unreadable DNA files into usable insights (3:50) Combining genetics, blood work, and medications (5:05) Drug response insights and hereditary signals (6:10) Generating doctor-ready reports for family (7:20) Why this system runs fully local (8:00) Building personal software instead of buying tools (8:40) Sam’s AI personal trainer built with Codex (9:50) Rep-by-rep workout feedback and fatigue detection (10:45) Designing AI interfaces for real-world use (11:40) Codex vs Claude Code: speed vs deep reasoning (12:20) Anthropic Opus 4.6 and Agent Teams (13:00) OpenAI Frontier and AI coworkers (13:25) Perplexity Council Mode and model swarms (14:05) Why multi-agent management is the real inflection (15:15) Becoming a manager of AI managers (16:00) How many agents one human can manage (17:00) AI’s impact on legacy software companies (18:15) Episode 30 wrap-up and what’s next
We Built an AI Recruiter Coach in 6 Hours (Plus Claude Cowork in Real Time)
01 Feb 2026
00:20:06
Can you really build serious internal AI tools in a few hours — and should everyone on your team be doing it?
In Episode 29 of Built This Week, Sam Nadler and Jordan Metzner break down an internal AI product they built at Ryz Labs called ScreenEval — a recruiter screen analysis and coaching tool built in under six hours using Claude Code, Supabase, and AWS.
We start with a live demo. Sam walks through how ScreenEval ingests recruiter screen transcripts, evaluates candidates, scores recruiter performance, and provides concrete coaching feedback — all without overriding human judgment. The real unlock is turning messy interview transcripts into searchable, structured hiring data across the entire organization.
From there, we test Claude Cowork live — Anthropic’s new interface designed to make building accessible to non-technical users — and compare it to running Claude Code directly in the terminal. We discuss where Cowork shines, where terminal-based workflows still win, and why managing multiple AI agents is becoming a core skill.
We wrap with AI news, including Anthropic’s massive funding round, pricing changes, and why enterprise-focused AI tooling is pulling spend away from other platforms.
No hype. No abstractions. Just what actually happens when you put AI to work inside a real company.
(0:00) Why internal AI tools matter more than external products (0:55) Episode 29 kickoff and overview (1:45) Why Ryz Labs built ScreenEval (3:30) Live demo: recruiter screen transcript analysis (6:15) Candidate evaluation vs recruiter coaching (9:10) What recruiters miss in fast screening calls (11:40) AI feedback that doesn’t override human judgment (14:00) Searching transcripts instead of resumes (17:20) Manager dashboards and recruiter performance analytics (21:10) How long it actually took to build ScreenEval (23:30) The full stack: Claude Code, Supabase, AWS (25:45) Why Anthropic models power everything (27:30) Claude Cowork explained (29:15) Building a new product live with Cowork (32:40) Cowork vs Claude Code in the terminal (36:00) Managing multiple AI agents at once (39:30) Anthropic’s funding round and market momentum (42:15) Why we’re shifting spend away from other AI tools (45:10) AI inside organizations: efficiency without layoffs (48:30) What every team should be building next (50:45) Final thoughts and closing
Why You Can't Pen Test an Airplane — AI Cybersecurity for Aviation
24 Jan 2026
00:20:02
Can you really hack an airplane? And if so, how do you test for it without grounding the fleet for a year?
In Episode 28 of Built This Week, Sam Nadler and Jordan Metzner sit down with Eero Salih, CTO of Syberian, to explore how AI is transforming cybersecurity for commercial aviation.
We start with a live demo — a flight ops cyber radar Sam built to surface real-time security risks across airline operations. Then Eero breaks down what Syberian actually does: building digital twins of aircraft systems to run risk assessments without ever touching the physical plane.
This is critical because traditional penetration testing would ground an aircraft for up to a year for recertification. Syberian's AI-powered approach analyzes over 100 technical documents to map every computer system on board — from avionics to entertainment to crew scheduling — and identify vulnerabilities before they become incidents.
We also discuss:
Why cyber attacks on aviation are now classified as safety threats
New 2026 regulations forcing airlines to comply with stricter cybersecurity standards
How small teams are replacing developers with AI agent managers
The tools Syberian uses: Claude Code, Windsurf, Anthropic, and Gemini
Why Google and Anthropic are rejecting ads while OpenAI explores them
An ex-Amazon exec who vibe-coded a full CRM replacement in 72 hours
No hype. No theory. Just what happens when you put AI in charge of protecting critical infrastructure.
TIMESTAMPS -------------------------------------------------------------------------------- (0:00) Why you can't hack-test an airplane (0:45) Episode 28 kickoff and guest introduction (1:30) Live demo: Flight ops cyber radar dashboard (3:00) Analyzing real-time security threats across airline systems (4:30) What Syberian actually does (in plain English) (6:00) Why physical penetration testing grounds planes for a year (7:30) Using AI to build digital twins of aircraft systems (8:15) Hiring managers, not developers — AI agents do the coding (9:30) Tools of the trade: Claude Code, Windsurf, Anthropic, Gemini (10:00) New 2026 aviation cybersecurity regulations explained (11:00) How cyber attacks became classified as safety threats (12:30) The ripple effects: baggage weight, fuel calculations, pilot tablets (13:30) Who are Syberian's customers? Airlines, private jets, and more (14:55) AI News: Google and Anthropic reject ads in chatbots (16:30) Why Anthropic's no-ads stance matters for enterprise customers (17:30) Amazon exec vibe-codes full CRM replacement in 72 hours (18:30) Why vibe coding works for internal tools but not production (19:15) Final thoughts and closing
LINKS SECTION -------------------------------------------------------------------------------- Built This Week New episodes every Friday
Jordan Metzner https://x.com/mrjmetz
Sam Nadler https://x.com/Gravino05
We Let AI Control Our Data Warehouse — The Results Were SHOCKING
16 Jan 2026
00:25:01
Can AI actually reduce cloud costs — or does it just create better dashboards?
In Episode 27 of Built This Week, Sam Nadler and Jordan Metzner are joined by Ben, CEO of Espresso AI, to break down a real production system that uses machine learning to actively optimize data warehouse compute in real time.
We walk through a live demo built specifically to expose hidden inefficiencies inside Snowflake and Databricks environments — from over-refreshing dashboards to duplicated queries and underutilized clusters. Then we go deep on how Espresso AI works under the hood: proxy-based routing, workload-aware ML models, and fine-grained compute orchestration that runs without changing application code.
This is not FinOps theater. This is AI actively rewriting how compute is allocated.
We also discuss:
Why most teams overpay for convenience in the cloud
How real-time query routing beats manual cost controls
Where AI helps engineers — and where it absolutely does not
The limits of vibe coding for serious infrastructure
Gemini powering Siri and what it means for voice assistants
Meta’s massive GPU buildout and the future of hyperscalers
No hype. No theory. Just what happens when you put AI in control of real infrastructure.
New episodes every Friday.
Timestamps
(0:00) Why modern AI understands code differently (0:45) Episode 27 kickoff and guest introduction (1:30) Live demo: diagnosing hidden warehouse inefficiencies (3:00) Why dashboards refresh far more than they are viewed (4:30) The real cost of duplicated queries across teams (6:00) What Espresso AI actually does (in plain English) (7:45) Kubernetes for data warehouses, powered by ML (9:30) How real-time query routing works (11:30) Why most companies are not “doing it wrong” (13:00) Transformers and deep code understanding (15:00) Where AI helps engineers today (16:30) Why AI cannot yet run core infrastructure autonomously (18:00) Productivity gains without replacing engineers (19:30) Gemini, Siri, and the next generation of voice assistants (21:00) Meta’s massive GPU investments explained (23:00) Will Meta become a hyperscaler (24:30) Final thoughts and closing
We Built an AI Trading Bot for Prediction Markets — Here’s What Actually Happened
09 Jan 2026
00:29:45
Can AI actually beat prediction markets — or does the house always win?
In Episode 26 of Built This Week, Sam Nadler and Jordan Metzner kick off 2026 by breaking down a real AI trading bot Jordan built for prediction markets like Kalshi, using live market data, whale detection, coordination signals, and confidence scoring.
Jordan walks through the full system — backend, frontend, live alerts, and execution logic — and shares the honest results: a 66 percent win rate that still lost money once fees and market dynamics were factored in.
The takeaway is not hype. It is reality.
The episode also dives into:
Why prediction markets feel like gambling but are regulated differently
How insider-like signals emerge from coordination and volume behavior
Why bots end up trading against bots
Where real alpha might exist (and where it does not)
We also cover:
Google NotebookLM as a serious education and onboarding tool
Turning documents into infographics, slide decks, and audio learning
Nvidia entering autonomous driving and competing with Tesla
Nvidia’s new Rubin architecture and why it matters
Tesla vs Waymo economics and the future of Full Self Driving
Why Anthropic and Claude Code are becoming developer defaults
This is not theory. This is what happens when you actually deploy AI systems into real markets.
Timestamps
(0:00) Why prediction markets are exploding (1:07) Episode 26 kickoff (2:00) Why build a trading bot at all (4:30) Kalshi vs Polymarket APIs (6:00) Live market signals and whale detection (9:30) Win rate vs profitability (12:00) Why fees destroy returns (14:30) Bots trading against bots (17:00) Where real alpha might exist (18:00) NotebookLM for learning and onboarding (21:00) Nvidia enters autonomous driving (24:00) Tesla vs Waymo economics (27:00) Nvidia Rubin chips explained (28:30) Anthropic and Claude Code momentum (29:30) Final thoughts
Car Dealers Are Losing Inventory — AI Is the Only Fix
19 Dec 2025
00:27:50
Car dealerships are losing inventory — and most don’t realize why.
Consumers now expect instant pricing, zero friction, and immediate engagement, yet most dealers still rely on slow callbacks, manual workflows, and outdated acquisition models. The result? Cars go straight to Carvana or CarMax.
In this episode of Built This Week, Sam Nadler and Jordan Metzner sit down with Anthony Monteiro, CEO & Founder of Auto Acquire AI, to break down how AI is fundamentally changing how dealerships acquire vehicles directly from consumers.
Auto Acquire AI gives everyday car dealers — small, medium, and large — the same capabilities as Carvana: instant offers, automated inspections, AI-driven pricing, and real-time engagement, without massive engineering teams or bloated operations.
Jordan also walks through a live AI workflow he built for Auto Acquire, showing how dealerships can automatically analyze inbound intent, score leads, and trigger the right action — SMS, email, or phone — without tying up staff.
This is not theory. This is AI running real dealership operations today.
In this episode, we cover:
• Why dealers can’t compete at auctions anymore • How AI enables instant vehicle pricing without human intervention • Turning web forms into real-time SMS conversations • Using intent scoring to decide when to text, email, or call • Why engagement speed determines who wins the trade • How computer vision automates vehicle inspections from a phone • Why structured automotive data is perfect for AI • How dealers already have inventory sitting in customer driveways • Why most “AI companies” aren’t actually using AI • The real difference between demos and production AI systems
We also dive into autonomous vehicle news, including: • Waymo’s $15B raise at a $110B valuation • Tesla vs Waymo: cameras vs lidar • Why Tesla may license Full Self-Driving to other manufacturers • The reality behind “Full Self-Driving” marketing claims
⏱️ Timestamps
(0:00) Why car dealers are losing inventory (0:38) Welcome to Built This Week (1:07) Introducing Auto Acquire AI (1:42) How Auto Acquire works (2:24) AI workflow demo: intent → action (3:11) Automated SMS conversations (4:55) Why AI removes staff bottlenecks (6:29) Dealership behavior by geography (7:38) Why instant pricing wins (10:34) AI-powered vehicle inspections (12:03) The real pain point in dealer inventory (13:31) Why dealers already own the data (14:46) What “real AI” actually means (17:00) Structured data and real-time pricing (18:05) Waymo raises $15B (19:03) Tesla vs Waymo economics (21:44) Will Tesla license FSD? (24:29) Is “Full Self-Driving” misleading? (27:09) Final thoughts and wrap-up
The Voice AI Platform Built for Enterprises That Actually Need to Scale
15 May 2026
00:23:26
This week on Built This Week we sit down with Karim, founder and CEO of Breeze (heybreez.ai), to demo the enterprise voice agent platform built for companies that actually need to run AI at scale. No slides. No prep. Just a live walkthrough of the real product.
We cover: What Breeze is and how it differs from other voice AI platforms
A live demo of the platform built from a blank screen
Why multi-agent architecture matters for enterprise compliance
How to prevent voice agents from being jailbroken
The latency and model selection decisions that make or break production
The operational layer of voice AI that everyone is ignoring
Phone groups, smart routing, and running 10,000 calls a day
Who is actually buying enterprise voice AI and why
Breeze's partnership model and expansion into MENA and South America
Anthropic raising at a $900 billion valuation and what it means
Whether AI is replacing junior developers and what comes next
If you are building with AI, scaling voice agents, or trying to understand where enterprise AI is heading next, this episode is for you.
Find Karim and Breeze:
Website: heybreez.ai
LinkedIn: linkedin.com/in/kmalhas
Twitter: x.com/kmalhas_
TIMESTAMPS
[00:00] Intro
[01:05] Meet Karim — founder and CEO of Breeze
[02:12] Live demo — building a voice agent from scratch
[07:34] Multi-agent architecture explained
[11:55] Latency vs quality tradeoff in voice AI
[12:56] OTP security and jailbreak prevention
[14:13] The operational layer nobody is building
[16:41] Version control, compliance, and phone groups
[18:43] Who is the ideal customer for Breeze
[21:49] Partnership model and global expansion
[22:55] News — Anthropic raising at $900B valuation
[24:28] Will AI replace junior developers
[26:05] Building from the Middle East — why it matters
Staffing shortages, last-minute cancellations, credential checks, compliance requirements, and manual scheduling are overwhelming care teams and putting patient outcomes at risk.
In this episode of Built This Week, Sam Nadler and Jordan Metzner sit down with Arya Health leadership to see how AI is already replacing hours of manual healthcare operations with real production systems.
Arya Health uses AI to instantly match patients with the right caregivers based on credentials, availability, location, eligibility scoring, and compliance rules all while remaining fully HIPAA compliant.
In the episode, we walk through: • How AI turns messy hospital discharge summaries into actionable start of care workflows • How caregivers are matched and notified automatically • Why Arya reframed “shifts” as patients and how that changed everything • How AI fills urgent care gaps in minutes instead of hours • The real security architecture behind HIPAA compliant AI • Why Arya forbids long term AI memory by design • How multi cloud AI works across AWS and Google safely • What happens when AI costs suddenly spike in production • Why scheduling healthcare looks like the traveling salesman problem with time windows
This is not a demo. This is what AI looks like in production healthcare today.
(0:00) This AI fills healthcare shifts in minutes (0:38) Welcome to Built This Week (1:07) Introducing Arya Health leadership (1:42) What Arya Health actually does (2:37) AI generated start of care workflows (3:28) Turning discharge notes into care plans (4:21) Matching patients with caregivers (5:12) Automated outreach and workflow actions (6:02) Leadership reacts to the AI workflow (7:15) How non experts prototype healthcare AI (8:50) Why demos and real healthcare are different (9:19) HIPAA compliance and security realities (10:19) Multi cloud AI architecture explained (11:15) Using AWS Bedrock and Google Vertex AI (12:06) Why only approved cloud models are allowed (13:30) Secure AWS and GCP data isolation (14:26) When AI costs unexpectedly spike (15:12) Single shot prompting in production (17:21) Why Arya blocks long term AI memory (18:01) Controlling AI with typed inputs (20:01) Real world impact and metrics (20:26) Replacing hours of manual scheduling (21:51) Filling urgent shifts instantly (22:45) Improving care quality through consistency (23:22) Reframing shifts as patients (24:05) Building care teams not schedules (24:32) Eligibility scoring and heuristics (25:52) Ranking caregivers by fit (26:13) Optimizing routes and schedules (27:34) Industry news discussion (39:36) Final thoughts and wrap up
OpenAI Code Red? The New AI Reviewer Changing Everything
05 Dec 2025
00:33:29
(Sam Nadler and Jordan Metzner are back — and this week they’re joined by Amar Goel, CEO of BITO, the AI-powered code review agent transforming how engineering teams ship software.
Jordan kicks things off by unveiling a surprise build: a fully custom BITO Slack Bot that can run PR reviews, generate stats, crack developer jokes, write haikus, and even drop into Biddo Disco Mode. Amar reacts live and pulls back the curtain on how BITO’s deep codebase analysis works — revealing how enterprise teams are merging PRs 10× faster, reducing revert rates, and catching issues that “vibe coding” tools simply miss.
From multi-million-line monorepos to legacy systems held together by duct tape, BITO’s agents are surfacing performance bugs, security vulnerabilities, logic issues, and cross-service breakages before humans ever see them. Amar explains why code review is just the start — and why BITO’s deep code intelligence unlocks a new era of AI developer tooling.
Then the trio shifts into the biggest AI news stories of the week: • OpenAI’s internal CODE RED and the escalating model war • Google Gemini’s rise and the threat of distribution • Amazon’s new AI chips and the GPU economics debate • The global AI arms race — from TPUs to supply chains to trillion-dollar CapEx bets
It’s a lively, candid, highly technical conversation with one of the sharpest minds in AI dev tooling.
(0:00) Jordan demos the BITO Slack Bot — PR reviews, jokes, haikus, & disco (1:02) Welcome + introducing guest Amar Goel, CEO of BITO (1:35) Amar’s background + BITO’s mission to build deep codebase AI agents (2:15) Why Jordan built the Slack integration prototype (3:04) What BITO can do today: reviews, tests, explanations, stats & more (4:18) The PR demo: catching security + maintainability vulnerabilities (5:22) Humor in devtools — BITO Fun, BITO Surprise, & developer haikus (6:44) Amar reacts: how customers want notifications & Slack workflows (7:35) Why existing tools fail on large, messy, real-world codebases (8:52) Deep code understanding explained — ASTs, symbol indexes, repo mapping (10:26) Why “vibe coding” breaks down in enterprise environments (11:31) How BITO integrates into Cursor, Windsurf, Claude Code, JetBrains & VS Code (12:10) The explosion of code volume — and why quality gates now matter (13:00) PRs merging 10× faster with BITO + 55% fewer reverted commits (14:05) Training junior devs through AI feedback + customizable sensitivity modes (15:20) What’s next for BITO (without giving away secrets) (16:12) NEWS #1 — OpenAI declares CODE RED (17:01) Google’s Gemini advantage: distribution, docs, slides & ad model economics (18:33) The coming AI model war — NVIDIA, xAI, Anthropic, Google (19:48) NEWS #2 — Amazon’s new AI chips & the GPU supply chain crunch (21:10) NEWS #3 — Global CapEx, GPU shortages & trillion-dollar questions (22:42) Final thoughts + Amar’s closing remarks (23:30) Wrap-up & teaser for next week’s episode
Sam Nadler and Jordan Metzner return with one of the most mind-bending episodes yet. Joined by Carina, founder & CEO of Axiom Math, the startup is building a self-improving, formal-reasoning AI mathematician. The trio breaks down why math is the next AI frontier, how Lean formalization works, and why proving theorems is a completely different challenge than solving them.
Jordan also unveils his newest build: the LLM Math Roaster, a tool that scores, compares, and even roasts large models on proofs, with a full leaderboard, custom problem submissions, and an API for automated evaluation. (Yes, it even benchmarked Gemini, GPT-5, Claude, and Grok head-to-head.)
In AI News, the hosts unpack Google’s massive Gemini 3 launch, Jeff Bezos stepping into the arena with Project Prometheus, and Suno’s $250M raise at a $2.45B valuation, plus what hyper-powerful AI means for creativity, coding, and even music composition.
It’s fast builds, deep math, big models, and a guest who’s literally building the future of reasoning.
— Show Notes: (0:00) Intro + welcoming our guest Carina (1:00) What Axiom Math is building (3:00) Jordan’s LM Math Roaster: how it works (5:00) Testing models on proofs (Gemini, GPT-5, Claude, Grok) (7:00) Why formal proofs beat natural-language reasoning (9:00) The data bottleneck: Lean scarcity & synthetic generation (12:00) How formal systems unlock “research-level” AI math (15:00) Comparing LLM math vs. Axiom’s approach (18:00) AI News: Gemini 3 hits the market (20:00) Jeff Bezos returns with Project Prometheus (22:00) Suno raises $250M — AI-generated music explodes (24:00) How math, code & creativity overlap (25:30) Episode wrap-up + what’s coming next —
Sam Nadler and Jordan Metzner are back! And this week, they’re joined by a special guest: Angie Westbrook, CEO of Standard AI. Together, they explore one of the most creative builds yet: an AI-powered retail DJ that uses computer vision and custom AI-generated music to adjust a store’s soundtrack based on real-time foot traffic. Think: mood lighting meets AI beats, but for shopping.
Angie then pulls back the curtain on Standard AI’s computer-vision platform, describing how their “Google Analytics for physical stores” is unlocking brand-new metrics like visual engagement, real-time shopper behavior, and rapid in-store experimentation. Later, the trio covers major AI news, including Gamma’s massive Series B, SoftBank’s pivot from Nvidia to OpenAI, and 11 Labs’ newly launched marketplace where brands can license iconic voices (yes, even Babe Ruth and Maya Angelou).
Store-scanning AI, predictive retail analytics, dynamic music engines, and a surprisingly heated debate about Michael Bublé, Episode 21 brings energy, innovation, and a fascinating look at how AI is reinventing brick-and-mortar retail from the ground up.
Show Notes:
(0:00) AI-generated retail music demo + how the “store DJ” works (0:55) Welcome + introducing guest Angie Westbrook, CEO of Standard AI (1:27) Angie’s background and Standard AI’s mission (1:49) This week’s agenda: AI DJ, Standard AI deep dive, and AI news (2:35) Why AI never slows down + early thoughts heading into the demo (2:55) The build: AI DJ for retail using computer vision + custom tracks (3:38) Bringing music, mood, foot traffic, and AI together (4:13) How stores currently choose music (spoiler: zero data) (4:50) Five custom AI-generated tracks from 90–130 BPM (5:42) Can music drive sales? The team’s hypothesis (6:04) Demo: welcome music + dynamic BPM changes based on occupancy (7:09) Angie reacts — why music + behavior data could transform retail (8:13) Using engagement metrics to improve music and optimize store layouts (9:14) Holiday music reinvented: AI-generated Christmas playlists (9:58) Transition: What Standard AI actually does (10:32) Standard AI explained: “Google Analytics for physical stores” (11:01) Why sales data is a lagging indicator (and too slow for real insights) (11:54) How AI enables rapid in-store experimentation (12:51) Traditional A/B tests vs. AI-powered retail testing (13:55) Faster experiments → faster revenue lift (14:45) Privacy-first computer vision (26-point body labeling) (16:04) What the system “sees” — digital stick figures, not faces (16:43) Visual Engagement Score: a new metric for product discovery (17:52) Why most new products fail (and how AI fixes it) (18:47) Predictive modeling + simulating store changes with AI (19:58) The future of AI-driven retail experiences (20:46) Fun fact: 85–90% of retail sales still happen in-store (21:12) AI News #1: Gamma raises $68M at a $2.1B valuation (22:21) 70M users + 30M decks/month — Gamma’s explosive growth (23:03) Why incumbents (Google, Microsoft) didn’t beat them (23:56) AI News #2: SoftBank sells Nvidia stake, pivots to OpenAI (24:52) AI News #3: 11 Labs launches the Iconic Voice Marketplace (28:02) Historical icons, celebrity voices, and licensing in the AI era (29:12) Consent, rights, and the new economics of synthetic voices (30:09) Fatman Scoop as your in-store DJ? The team imagines the future (30:25) Closing thoughts + a huge thanks to Angie (31:05) Teaser: Next week’s guest — Axiom Math
Episode 20: Compliance, Pomelli, and the Rise of the Robots
Sam Nadler and Jordan Metzner are back for a landmark 20th episode of Built This Week! This time, the duo breaks down how Ryz Labs used AI to build a full compliance and education platform, complete with video-based lessons, automated tests, and certificates: all powered by Video 3.1, React, and Supabase. They also explore Google’s new AI-powered marketing tool, which auto-generates on-brand social campaigns in seconds (seriously, it’s like having a creative team in your browser). In AI News, the hosts discuss Amazon’s robot-run Whole Foods stores, the growing home robotics market, and what a $20,000 “household robot” really means for the future of everyday automation. Fun, fast builds. Real AI demos. And a glimpse into how AI is quietly reshaping how we work, market, and even shop for groceries.
Show Notes:
(0:00) Intro + hitting 15,000 subscribers (1:00) What’s on deck this week (3:00) The rise of AI-powered compliance training (4:00) Demo: AI-generated videos + exam builder (6:30) Building with Supabase + React + Video 3.1 (8:30) Why we built (not bought) our education platform (10:00) Google’s new social marketing tool demo (12:30) Creating full brand campaigns with AI (15:00) Sponsor: Ryz Labs – build faster with world-class teams (16:00) AI News: Amazon’s robotic Whole Foods (18:00) The $20K home robot – hype or reality? (22:00) What robots can (and can’t) do yet (24:00) Reflections on episode 20 + what’s next (25:30) Teaser: Next week’s guest – Angie Westbrook, CEO of Standard AI
Mirror, Mirror on the Wall… Who Built the Smartest AI of All?
31 Oct 2025
00:23:07
Episode 19: Mirror, Mirror on the Wall… Who Built the Smartest AI of All?
It’s a spooky special! Sam Nadler (a.k.a. Bad Bunny) and Jordan Metzner (the resident vampire) celebrate Halloween with a pair of AI-powered builds that bring equal parts fun and fright. First, they unveil Mirror, Mirror on the Wall, a poetic, Gemini-powered “talking mirror” built in Google’s new AI Studio. Then, they conjure up a “Trick-or-Treat Route Optimizer,” a playful demo that uses Maps and AI to find the best candy streets in your city. In Tool of the Week, they explore Google’s Build Studio, a fresh entry into the “vibe coding” space, and explain why it’s a step-function improvement over other no-code tools. Gemini comes baked right in. Finally, in AI News, they break down Nvidia’s record-breaking $5 trillion valuation and Elon Musk’s Grok-a-pedia, a controversial AI-powered rival to Wikipedia. Fun, fast builds. Real AI demos. And a whole lot of Halloween spirit.
—
Show Notes: (0:00) Intro + Halloween costumes (1:00) Mirror, Mirror on the Wall – the spooky AI build (3:20) How it works – Gemini, speech-to-text, and text-to-speech (5:00) Building with Google’s new AI Studio (8:00) Guess the Costume app demo (9:00) Trick-or-Treat Route Optimizer with Maps + Gemini (13:00) Why Google’s “vibe coding” tool feels like a leap forward (15:20) News: Nvidia hits $5T valuation (18:00) Elon Musk launches Grok-a-pedia (21:40) Halloween wrap-up + what’s next week
Sam Nadler and Jordan Metzner get into the Halloween spirit with a playful AI build — TrickOrTreat, an interactive web app that lets users snap a photo and instantly generate custom AI costumes and “Happy Halloween” videos. Built in Replit using NanoBanana and Video 3.1, it’s a perfect mix of fun, speed, and creativity. The hosts discuss how quick AI builds can boost team culture, inspire side projects, and push generative video forward.
Then they spotlight Publer, the social media syndication tool that keeps their content engine running across platforms, and how it helps teams automate posts without losing authenticity.
In the AI News Rundown, they react to Kohler’s new “smart toilet camera” (yes, really), break down OpenAI’s ChatGPT Atlas browser launch, and explore Google’s new AI Studio app builder - three stories showing how fast (and weird) the AI world is moving.
— Show Notes
(0:00) Intro (1:20) TrickOrTreat demo — how the AI costume builder works (3:30) Why Jordan built it + tech stack (Replit, NanoBanana, Video 3.1) (5:30) Funny results, costumes, and team reactions (8:40) Real use cases for generative video (9:50) Tool of the Week – Publer for social media syndication (12:10) How Publer helps scale content across platforms (14:30) AI News: Kohler’s “toilet camera” and privacy questions (20:00) AI News: OpenAI launches ChatGPT Atlas browser (25:00) AI News: Google AI Studio introduces “vibe-coding” app builder (29:40) Wrap-up + closing thoughts
This week on Built This Week, Sam Nadler and Jordan Metzner get into the Halloween spirit with a playful AI build, TrickOrTreat, an interactive web app that lets users snap a photo and instantly generate custom AI costumes and “Happy Halloween” videos. Built in Replit using NanoBanana and Video 3.1, it’s a perfect mix of fun, speed, and creativity. The hosts discuss how quick AI builds can boost team culture, inspire side projects, and push generative video forward. Then they spotlight Publer, the social media syndication tool that keeps their content engine running across platforms, and how it helps teams automate posts without losing authenticity. In the AI News Rundown, they react to Kohler’s new “smart toilet camera” (yes, really), break down OpenAI’s ChatGPT Atlas browser launch, and explore Google’s new AI Studio app builder - three stories showing how fast (and weird) the AI world is moving.
—
Show Notes
(0:00) Intro (1:20) TrickOrTreat demo — how the AI costume builder works (3:30) Why Jordan built it + tech stack (Replit, NanoBanana, Video 3.1) (5:30) Funny results, costumes, and team reactions (8:40) Real use cases for generative video (9:50) Tool of the Week – Publer for social media syndication (12:10) How Publer helps scale content across platforms (14:30) AI News: Kohler’s “toilet camera” and privacy questions (20:00) AI News: OpenAI launches ChatGPT Atlas browser (25:00) AI News: Google AI Studio introduces “vibe-coding” app builder (29:40) Wrap-up + closing thoughts
This week on Built This Week, Jordan Metzner and Sam Nadler sit down with Tristan Wilson, CEO of Edgevanta, an AI startup that brings automation to one of the world’s most traditional industries: construction. From parsing 1,200-page bid packages to predicting pricing with AI agents, Edgevanta is helping estimators work faster, smarter, and more profitably. Then, the hosts dive into the week’s biggest AI news: Nvidia’s $2B investment into Elon Musk’s xAI, OpenAI’s projected $1 trillion infrastructure spend, and how AI adoption is accelerating across industries, from consulting giants to construction firms.
— Show Notes:
(0:00) Intro – welcome + guest intro: Tristan Wilson, CEO of Edgevanta
(1:10) What We Built: Edgevanta Tycoon, AI-powered construction sim game
(2:45) How Edgevanta helps estimators bid faster and smarter
(5:30) Breaking down the role of estimators + pain points in civil construction
(8:00) How AI agents parse 1,200-page bid packages in minutes
(11:00) Real-world impact: saving hours, reducing bid errors, and recovering millions
(13:45) Using AI to improve “go/no-go” decisions in construction projects
(16:15) How estimators are reacting to AI, from fear to full adoption
(19:50) AI News #1: Nvidia invests $2B in Elon Musk’s xAI
(22:30) AI News #2: OpenAI’s $1 trillion infrastructure plan and what it means for the future
(26:30) Closing thoughts – AI’s early days in construction + industry-wide acceleration
Sora 2 Took Over AI Video + Our New Parking Data Tool
03 Oct 2025
00:27:02
Episode 15: Sora 2 Took Over AI Video + Our New Parking Data Tool
This week on Built This Week, Jordan Metzner and Sam Nadler debut Tix LAX, a new platform that visualizes parking tickets across Los Angeles using city APIs, from officer leaderboards to the surprising car colors that rarely get ticketed. Then, they dive into Sora 2, OpenAI’s latest video model that lets you insert yourself directly into AI-generated clips, whether skydiving, cooking sushi, or working on an oil rig. In the AI news rundown: OpenAI reaches a staggering $500 billion valuation, Apple shifts focus from Vision Pro to AI glasses, and a new startup builds AI-powered defense technology to shoot down drones.
— Show Notes:
(0:00) Intro – welcome + topics for this week
(1:20) What We Built: Tix LAX – LA parking tickets mapped with city data
(2:40) Inspiration from San Francisco’s viral parking ticket tracker
This Headset Reads Your Brain in Real Time. We Demo It Live.
08 May 2026
00:21:17
This week on Built This Week we sit down with Ramses Alcaide, founder of Neural, to demo a noninvasive brain computer interface that tracks your focus in real time through a pair of headphones. No surgery. No implants. Just data.
We cover:
What a brain computer interface actually is and how it works
A live demo of focus tracking during the episode
A browser plugin that adjusts podcast speed based on your brain activity
How the technology detects brain fatigue before you feel it
Gaming, medical, and sports applications
How AI finally unlocked BCI for consumer devices after 40 years in labs
The science behind ice baths affecting men and women differently
Why kids are bypassing age verification AI with a fake mustache
Why AI security cameras are still failing at basic common sense
The edge compute problem nobody in consumer hardware wants to talk about
Why your brain signature might be the future of identity verification
If you are building with AI, interested in wearables, or want to understand what brain computer interfaces actually are today, this episode is for you.
TIMESTAMPS
[00:00] Intro
[00:44] Meet Ramses — what is a brain computer interface
[01:40] How the headphones track focus in real time
[02:28] Live focus tracking demo on the podcast
[03:00] Browser plugin that adjusts podcast speed to your brain
[04:35] How to use biofeedback to stay focused
[07:02] Brain health tracking — cognitive strain and brain age
[07:33] Gaming use case — overclocking your brain with HP
[08:16] ER doctors and high stakes focus applications
[09:08] How AI finally brought BCI out of the lab
[10:01] Origin story — PhD, family tragedy, US Army backing
[11:45] How to find Ramses and the product
[13:09] Ice bath experiment — men vs women brain data
[14:45] News — AI security cameras calling dogs bears
[15:13] Why edge AI for consumer hardware is brutally hard
[16:28] Brain data and camera AI share the same constraint
[17:08] Kids bypassing age verification with a fake mustache
[19:23] Brain signature as the future of identity verification
Inside the $1.4 Trillion Solopreneur Market + the Tools We Built (ft. Hooman, Collective CEO)
26 Sep 2025
00:38:38
This week on Built This Week, we team up with Hooman (CEO, Collective) to build—and ship—new tools for solopreneurs. Jordan demos a cash-flow forecaster, insurance compliance checks, lending readiness, and AI business insights…plus a just-for-fun “Make It Rain” mode and mini-game. Then we go deep on Collective’s roadmap and the future of the one-person business.
What we built -Cash-Flow Forecasting from your P&L + balance sheet (with sliders for revenue, expenses, and owner salary) -Insurance Compliance review (flags lapses like workers’ comp and gaps like cyber) -Lending Readiness & Risk report (eligibility + risk summary) -AI Business Insights panel (Gemini-powered analysis) -Bonus: “Make It Rain” theme + a quick 3D game (three.js)
Guest spotlight — the solopreneur wave -Solopreneurs are already 38% of the U.S. workforce, generating $1.4T in revenue -27M+ Americans run solo businesses; 5.5M make $100k+ -Why so many switch to an S-Corp with Collective: average $10k/year in tax savings; plans from $349/mo; and a “CFO-in-your-pocket” vision with AI agents
Tech stack -Front end: Vite + React, Tailwind (UI), filtering library for snappy tables -Models: started on Grok 120B, then moved to Gemini for larger context windows -Fun stuff: three.js for the Make-It-Rain mini-game
Chapters (tap to jump) 0:00 Cold open + theme 0:42 Hosts + guest intro (Hooman, Collective) 2:15 Why we built these features 3:00 Build #1: Cash-flow forecasting demo 8:48 Build #2: Insurance compliance check 9:36 Build #3: Lending readiness + risk report 10:17 Build #4: AI insights dashboard 10:37 Build #5: “Make It Rain” mode + 3D game 14:15 Collective deep-dive: product, pricing, and who it’s for 22:21 AI news + mega-capex talk (NVIDIA, Oracle, OpenAI) 33:50 The margin crunch + round-tripping debate 37:50 Wrap-up & subscribe
About us Built This Week — Jordan Metzner & Sam Nadler build something new every week and break down the AI + startup news that matters. New episodes every Friday. Subscribe for the next build.
AI Built My Liver + We 3D Printed Our Podcast (Reddit x Google, Lyft x Waymo News)
19 Sep 2025
00:20:08
This week on Built This Week, we go full builder mode.
Jordan uses Claude to create a live 3D simulation of a liver, showing exactly how statins like Crestor crush cholesterol inside your body. Then Sam takes the mic — and the printer — and 3D prints Built This Week keychains, proving you can literally print your podcast at home.
Finally, we break down the biggest AI + tech headlines:
Reddit doubling down with Google
Groq raising $750M at a $7B valuation
Lyft teaming up with Waymo to launch robotaxis in Nashville
If you want AI, hardware, and startup news with founder energy — this is the episode.
Timestamps below 👇
⏱️ Timestamps
(0:00) Intro + what’s coming this week (1:11) Jordan’s Claude-powered 3D liver + cholesterol demo (3:22) Statins, Crestor, and real-time LDL impact (5:20) How doctors + patients could use this tool (6:23) Beyond medicine: AI visuals in other industries (7:23) Sam’s 3D printing showcase (8:19) Bambu Lab X1C + MakerWorld: keychains + builds (9:19) Printing tools, fidgets, and custom gifts (10:27) AI + 3D printing: customizing complex models (11:36) Favorite prints + side hustle with charms (13:19) AI News: Reddit extends Google deal (14:49) Groq raises $750M at $7B valuation (16:29) Lyft + Waymo bring robotaxis to Nashville (18:39) Closing thoughts + subscribe reminder
Listen on Your Favorite Platform: Spotify – https://open.spotify.com/show/0ahiOCzYxhhkEgbtz9kkeC Apple Podcasts – https://podcasts.apple.com/us/podcast/built-this-week/id1823270832 Amazon Music – https://music.amazon.com/podcasts/1017d387-fbb0-4bbf-9488-817cee38e058 Deezer – https://www.deezer.com/us/show/1001995001
Follow the Hosts:
Jordan Metzner • LinkedIn – https://www.linkedin.com/in/jordanmetzner/ • Instagram – https://www.instagram.com/mrjmetz/ • X – https://x.com/mrjmetz?lang=bn
Sam Nadler • LinkedIn – https://www.linkedin.com/in/sam-nadler-1881b75/ • X – http://x.com/Gravino05
Recipes from Receipts: AI Cooking, Kidpreneur E-Com & Replit’s $250M Raise
12 Sep 2025
00:19:16
This week on Built This Week, Jordan Metzner and Sam Nadler bring a mix of practical, playful, and breaking AI news.
First, Jordan demos Ryz Chef, a tool that turns your grocery receipts (Amazon, Instacart, even fridge photos) into 11 Mediterranean-inspired recipes — complete with breakfast, lunch, dinner, and dessert options. Then Sam shares how he and his daughter are using AI-generated imagery to launch a small e-commerce project selling 3D-printed hoodie charms, combining entrepreneurship, creativity, and social good. Finally, the hosts break down the biggest AI news: Replit’s $250M raise at a $3B valuation, Oracle’s AI-fueled surge, Vimeo’s acquisition, and Robinhood’s new “social trading” product.
Timestamps
(0:00) Intro + what’s on the docket this week
(1:00) Introducing Ryz Chef: turning receipts into recipes
(2:10) How the AI extracts groceries and builds meals
(5:30) Demo: 11 recipes generated from an Amazon cart
(6:16) Mediterranean recipes, desserts, and Unsplash images
(7:45) Prompting AI like a professional chef
(8:54) Dietary restrictions, kids meals, and macros
(9:31) Full-circle idea: recipes → shopping list → nutrition
(11:01) Sam’s side project with his daughter
(12:16) Building an e-commerce store for 3D-printed hoodie charms
(13:24) Using Google AI Studio to generate lifestyle images
(14:39) Fast, high-quality visuals with simple prompts
(15:04) Hot AI news: Replit raises $250M at $3B valuation
(16:15) Oracle stock surges 45% — Ellison tops the rich list
Coding the Beat: Strudel, Claude Dashboards & OpenAI’s $1B Play
05 Sep 2025
00:23:57
Episode 11: Coding the Beat: Strudel, Claude Dashboards & OpenAI’s $1B Play
This week on Built This Week, Jordan Metzner and Sam Nadler dive into the intersection of AI, music, and enterprise tools. Jordan shows off a new project built on Strudel, a live-coding JavaScript music library, turning it into an AI-powered DJ + Ableton-style mixer that generates new beats on the fly. Then, the hosts spotlight a daily use case of Claude that creates instant CFO-style dashboards from raw spreadsheets or PDFs, beating out other LLMs for speed and clarity. Finally, they break down OpenAI’s $1.1B acquisition of StatSig, what it means for Codex and the AI coding race, plus big moves in Figma’s IPO, Google’s antitrust settlement, and the rise of enterprise-focused AI like You.com.
Show Notes: (0:00) Intro + Jordan discovers Strudel for live-coding music (2:20) Demo: remixing tracks with AI-generated beats (5:02) Building an AI-powered two-deck DJ tool inspired by Ableton (8:14) How LLMs are lowering barriers to music production (10:13) Claude use case: auto-generating dashboards from Google’s 10-K (12:59) Why Claude outperforms other LLMs for financial and ops data (14:27) Codex gains traction; Rise Labs engineers switch from Claude Code (15:56) OpenAI acquires StatSig for $1.1B to boost Codex + experimentation (17:14) Anthropic predicts 90% of code will be bot-written (18:17) Figma’s IPO rollercoaster & enterprise adoption (19:37) Google avoids selling Chrome in antitrust ruling (20:29) You.com raises $100M pivoting to enterprise AI search (22:08) Why back-office ops are AI’s sleeper hit in enterprises
This week on Built This Week, Jordan Metzner and Sam Nadler unveil the AI image platform they’ve been building from scratch at Ryz Labs, powered by Gemini’s new “nano-banana” update and other AI models. Designed to deliver faster, cleaner, and more customizable visuals, it pushes image generation beyond today’s mainstream tools. Then, they put Gamma under the spotlight, a presentation app that reimagines how decks and docs are created with AI at the core. In the AI news rundown: Google’s Gemini image model gets a “bananas” upgrade, Will Smith faces backlash over suspiciously AI-generated tour footage, and Anthropic launches a Claude AI agent embedded directly into Chrome, raising big questions about the future of browsers.
— Show Notes:
(0:00) Intro + demo of new in-house AI image editing prototype
(3:03) Building a chatbot-style AI tool for small businesses & e-commerce
(8:15) Risks of deepfake-style edits and blurred lines between real vs AI
(9:10) Google Gemini’s “bananas” model upgrade explained
(10:49) Anthropic brings Claude agents directly into Chrome
(13:29) Will Smith’s tour footage is accused of using fake AI crowds
(15:17) Tool of the Week: Gamma AI presentation builder
(16:31) Live demo: generating a 3-card “Built This Week” deck in minutes
(19:22) Why Gamma beats Google Slides/PowerPoint at AI integration (for now)
(21:24) The future of consultants, schools & pitch decks in an AI-driven world
This week, Jordan Metzner and Sam Nadler unveil Ryz ATS, a fully functioning applicant tracking system built in-house using Claude AI. From job templates and smart matching to drag-and-drop pipelines and sourcing CRM, this tool streamlines the entire hiring process with AI as a co-pilot. Then, they explore Envato’s new AI image generation features, built for non-designers and creators alike. In the AI news rundown: xAI leaks Grok chats into Google search results, Meta re-orgs its AI division under Scale AI’s founder, and OpenAI brings back the ChatGPT model picker, confusing UX and all.
— Show Notes: (0:00) Intro
(2:10) Building an ATS from scratch with Claude Code
(3:15) Prototypes & using multiple AI agents in parallel
(5:12) Walkthrough: jobs page, candidate pipelines, offers & feedback forms
(13:43) Choosing the right prototyping tool: Bolt vs Claude Code vs Replit
(14:05) Tool of the week: Envato AI for stock content & image generation
(15:17) Testing Envato’s AI-generated podcast ads (and why text fails)
(18:22) Why stock libraries like Envato still matter
(19:01) AI News: Meta’s AI re-org & Scale AI acquisition fallout
(20:37) Cultural tensions inside Meta around AI talent pay
(21:06) AI Grok leaks chats into Google search results
This week, Jordan Metzner and Sam Nadler go deep on Public.com, the modern investing platform opening its trading infrastructure to developers. They demo a new tool built live on Public’s API, explore the real potential of programmable investing, and sit down with Emily Kurtz (Head of Product at Public) and Jake Trefethen (Director of AI) to unpack what’s coming next. Plus, in the news: Shopify now wants PMs who code, GPT-5 Pro hints at research-grade intelligence, and OpenAI’s model picker is back, and messier than ever.
— Show Notes: (0:00) Intro + guests from Public (1:30) What is Public.com and how does the API work? (3:30) Demo: Jordan’s trading bot built on Public’s API (13:00) Comparing LLMs for financial reasoning (17:30) Public’s broader vision + AI research features (20:30) Generated assets and AI-assisted portfolio tools (22:55) GPT-5 Pro release: early impressions (24:30) The return of model picker + emotional attachment to AI UX (26:30) Shopify now requires PMs to vibe-code (29:00) What “vibe-coding” means and where it fits in product hiring (31:00) Wrap-up and thanks to the Public.com team
Jordan Metzner and Sam Nadler share a simple but powerful internal tool: a Slack-integrated daily check-in system that’s helped their remote team stay accountable, async, and aligned. It’s lightweight, fast, and has changed how their team shares progress. Then they revisit Clay, a thoughtfully designed relationship management tool that helps founders and operators stay in touch without the CRM bloat. In the news, they break down the latest on GPT-5 Pro, OpenAI’s rumored “research-grade” AI, and what the new product tiers might mean for the future of AI.
—
Show Notes: (0:00) Intro
(1:21) Why we built a daily check-in tool for remote teams
(3:22) How the system works + Slack + AI summaries
(6:44) What it’s built with and what it unlocked for us
(9:15) What teammates actually do + future features
(10:30) Real example: AI blocker spotted and solved
(11:17) Tool of the Week: Clay for personalized outreach
(16:04) AI News: OpenAI’s new open-source models + Groq demo
Episode 6: From Avatar to AI Hire: Building NTRVSTA
Jordan Metzner and Sam Nadler dive into NTRVSTA, a new AI-powered interview automation platform Jordan built to help teams move faster and smarter in the hiring process. The tool uses avatars to conduct adaptive, friendly interviews 24/7 across technical and non-technical roles. They break down how it works, why it saves time, and what they’ve learned from early users. Plus, in the news: Microsoft hits a $4 trillion valuation, Figma’s IPO surges over 250%.
— Show Notes:
(0:00) Intro
(1:17) Why we built NTRVSTA — solving interview inefficiency
(2:51) How AI avatars help scale top-of-funnel interviews
(9:22) Product demo: scoring, transcripts, highlights, and whiteboard
(16:36) How it was built: avatars, scoring, and translation tech
(20:05) News: Microsoft hits $4 trillion valuation
Jordan Metzner and Sam Nadler reveal Mate: a custom-built social platform designed to bring remote teams closer through clubs, shared interests, and personality-rich profiles. Then they spotlight Clay, a sleek relationship management tool that helps founders and teams stay in touch with the people who matter, minus the CRM bloat. Finally, in the news: OpenAI signs a $30B cloud deal with Oracle, Trump issues an executive order banning “woke AI,” and Google reports its AI Overviews now reach 2 billion users monthly, with 100 million using AI Mode in the U.S. and India.
— Show Notes: (0:00) Intro
(0:51) Why we built “Mate”: a social app for our team
(2:10) What Mate is and how it works
(4:13) Why remote teams need tools like this
(5:04) Demo: profiles, badges, clubs, and interests
(7:21) How our team uses it today
(8:56) Tech stack: built with Bolt, Cursor & Supabase
Claude Design Changes Everything (Figma in Trouble?)
24 Apr 2026
00:20:51
This week on Built This Week, we break down one of the most interesting new AI product launches in recent memory: Claude Design. No demos. No fluff. Just what happens when AI starts replacing traditional design workflows. We cover: • What Claude Design is and how it works • Creating ad campaigns, decks, and full product redesigns with simple prompts • Why it could become a serious competitor to tools like Figma • How teams are exporting AI designs directly into production code • The rumored xAI / Cursor deal and what it means for the coding race • ChatGPT Images 2.0 and whether it lives up to the hype • Why Google might be quieter now—but still dangerous long term If you're building with AI, working in design, or trying to understand where creative tools are heading next, this episode is for you. ⏱ TIMESTAMPS [00:00] Intro [00:45] Claude Design overview [01:50] First impressions after using Claude Design [03:00] How the interface works [04:20] Building decks, ads, and redesigns with prompts [06:10] Creating ad campaigns for Hip Train [07:45] Exporting projects, sharing, and production handoff [10:15] Full internal app redesign with AI [12:45] Is Claude Design a Figma killer? [13:00] xAI / Cursor acquisition rumors [16:15] ChatGPT Images 2.0 reactions [18:30] Why AI is still in the early innings [21:40] Google’s new TPUs and staying in the race [22:40] Wrap up & what’s next for Built This Week
Links BuiltThisWeek.com New episodes every Friday
Jordan Metzner https://x.com/mrjmetz
Sam Nadler https://x.com/Gravino05
Why Our Recruiters Stopped Reading Resumes And Let AI Take Over Everything
18 Jul 2025
00:31:11
Episode 4: Hiring in Half the Time: Meet Ryz Score Jordan Metzner and Sam Nadler reveal Ryz Score, an internal tool they built to help recruiters stop wasting hours on bad resumes. It uses AI to rank candidates and streamline hiring decisions. For the Tool of the Week, they explore surprising ways people are using ChatGPT: from health tracking and meal planning to full-on life automation. And in the news, they break down Grok’s new 3D AI avatars, OpenAI’s plan to monetize in-chat shopping, and Claude’s expansion into finance with its first industry-specific platform. — Show Notes:
(0:00) Intro (1:30) What is Ryz Score? The AI resume filter (10:15) Tool of the week: ChatGPT as a personal assistant (11:13) Using GPT for meal tracking & other hacks (16:34) Claude enters finance — Bloomberg disruptor? (22:14) OpenAI adds shopping + affiliate revenue (25:46) Grok’s NSFW AI avatars — companion or concern? (30:12) Final thoughts: loneliness, Alexa 2.0, AI futures — Platforms / Tools Mentioned: • Ryz Labs – https://www.ryzlabs.com • ChatGPT – https://chat.openai.com • Claude by Anthropic – https://claude.ai — Listen on Your Favorite Platform: • Spotify – https://open.spotify.com/show/0ahiOCzYxhhkEgbtz9kkeC • Apple Podcasts – https://podcasts.apple.com/us/podcast/built-this-week/id1823270832 • Amazon Music – https://music.amazon.com/podcasts/1017d387-fbb0-4bbf-9488-817cee38e058 • Deezer – https://www.deezer.com/us/show/1001995001 — Follow the Hosts: Jordan Metzner • LinkedIn: https://www.linkedin.com/in/jordanmetzner/ • Instagram: https://www.instagram.com/mrjmetz/ • X: https://x.com/mrjmetz?lang=bn Sam Nadler • LinkedIn: https://www.linkedin.com/in/sam-nadler-1881b75/ • X: http://x.com/Gravino05
Built This Week Ep3: Auto-Marketing for Podcasts? Let’s Build It!
11 Jul 2025
00:29:54
Jordan Metzner and Sam Nadler unveil a tool Jordan secretly built — a mini CRM that scrapes podcast emails via RSS and auto-generates personalized, AI-written outreach using Gmail. Then they demo their favorite AI tool for creative expression: Suno, the text-to-song app that powers everything from Built This Week’s theme music to cookie-sale jingles and classical-to-trap remixes. Finally, they discuss the rise of the AI band Velvet Sundown and how AI might reshape education after OpenAI, Microsoft, and Anthropic partner with America’s largest teacher union.
This AI Tool Turns Meetings Into Jira Tickets Instantly
17 Apr 2026
00:19:32
This week on Built This Week, we break down how AI helped a non-technical teammate build a real internal product that now helps teams move faster across the company.
No buzzwords. No fake use cases. Just real AI in production.
We cover: • The AI tool that automates meeting follow-up work • How transcripts become tickets, reports, and dashboards • Why internal AI products are becoming a huge advantage • How companies can train non-technical teams to build • What happens when everyone can create software • Why the next wave of AI is about empowerment If you're serious about using AI to improve your business, this episode is for you.
⏱ TIMESTAMPS (00:00) Intro (00:32) Welcome back (00:40) Guest introduction (01:28) Inside the Radar tool (02:36) Solving workflow bottlenecks with AI (03:23) Instant task generation from meetings (04:45) Smarter project visibility with dashboards (05:56) Real productivity gains (07:00) From personal tool to company product (08:08) Future roadmap (09:24) AI-generated business reviews (10:19) Building an AI-first culture (11:30) Teaching non-technical teams (12:49) Real examples across departments (13:57) Why this changes work forever (15:06) News segment (17:44) Closing thoughts
🎙 HOST INFO Hosted by Jordan Metzner and Sam Nadler Co-founders of Ryz Labs We build AI-native companies and tools used by startups, enterprises, and investors.
🔗 CTA + LINKS Subscribe for weekly breakdowns of real AI builds and what actually matters New episodes every Friday
Follow along: YouTube: Built This Week Spotify: Built This Week Apple: Built This Week
We Built an AI Tool That Replaced a Week of Work
10 Apr 2026
00:23:00
This week on Built This Week, we break down a real AI tool we built that’s already saving days of work in production.
No demos. No fluff. Just how AI is actually being used inside a real business.
We cover: • The internal tool that replaced complex spreadsheets and cut turnaround time in half • How we generate client-ready presentations instantly with AI • Why tool selection matters more than ever in the agentic era • Google AI Studio and how we use it to prototype fast • Anthropic’s unreleased model and what it means for AI safety • Meta’s latest push into AI and why competition is heating up
If you're building with AI or thinking about how to apply it inside your company, this episode is for you.
⏱ TIMESTAMPS
00:00 Intro 00:40 What we’re covering this week 01:30 The problem with planning large offsites 02:28 How you lose money without perfect cost visibility 03:23 The AI tool we built (Offsite estimator) 04:29 Hidden costs AI catches that humans miss 05:36 From spreadsheets to automated workflows 06:04 Instant client presentations with AI 07:19 Cutting turnaround time from 10 days to 3 08:09 Tech stack behind the tool (Codex, Supabase, React, AWS) 08:58 Real customer impact and results 10:05 What we’re building next (automation + client portal)
10:40 Google AI Studio deep dive 11:14 How we actually use it for prototyping 12:55 Image, music, and video generation tools 14:48 When to use which AI tool
15:33 The real framework for choosing AI tools 16:45 Anthropic’s unreleased model 17:54 Why it might be a security risk 18:32 Who should control powerful AI
19:45 Meta’s new AI push 21:10 Why competition is accelerating
22:30 Wrap up
🎙 HOST INFO
Hosted by Jordan Metzner and Sam Nadler Co-founders of Ryz Labs
We build AI-native companies and tools used by startups, enterprises, and investors.
Why AI Inference Is So Expensive (And How Positron Is Solving It)
03 Apr 2026
00:29:03
Training gets the headlines.
Inference is where the money is.
In Episode 37 of Built This Week, we sit down with Mitesh, CEO of Positron AI, to break down one of the biggest bottlenecks in AI today: inference infrastructure.
While the world focuses on trillion-parameter models and frontier labs, the real constraint isn’t intelligence — it’s memory, bandwidth, energy, and cost.
We cover:
• Why inference is where 90% of AI spend happens • The memory wall problem in large models • Why GPUs weren’t designed for text generation • How Positron is building terabyte-plus memory chips • The economics of 10 trillion parameter models • Why memory bandwidth utilization matters • Why CPUs are suddenly back in demand • The difference between speed-optimized and cost-optimized AI systems • The slider bar future of AI infrastructure
We also dive into:
• OpenAI’s $122B valuation • Anthropic vs OpenAI secondary market dynamics • Why Nvidia isn’t going anywhere • Why commodity memory might beat premium stacks in certain use cases • The rise of agentic workflows and what that means for compute
If you care about the future of AI, silicon, infrastructure, or trillion-dollar companies — this episode is for you.
New episodes every Friday.
⏱ TIMESTAMPS
(0:00) Why inference is the real AI bottleneck (2:00) What Positron AI is building (4:30) The memory problem in trillion-parameter models (6:30) Why GPUs struggle with inference economics (9:00) Energy, bandwidth, and supply chain constraints (12:00) Memory capacity vs memory speed tradeoffs (16:00) The “slider bar” model of AI infrastructure (18:30) OpenAI’s $122B valuation discussion (21:00) Anthropic vs OpenAI secondary markets (23:30) CPUs making a comeback (26:00) Agentic workflows and compute demand explosion (28:00) Closing thoughts on AI infrastructure
How We Built an AI Video Editor for Recruiters (Remotion + Claude + Codex)
22 Mar 2026
00:18:45
Our recruiters are not video editors.
But now they can cut highlight reels in minutes.
In Episode 36 of Built This Week, we break down a tool we built internally at Ryz Labs that lets our recruiting team generate polished candidate highlight videos without touching Premiere, Final Cut, or CapCut.
The problem:
When presenting candidates to clients, resumes are standard. But seeing a candidate speak for 60 seconds changes everything.
The issue was speed. Editing sizzle reels required our video team, added delays, and was not scalable.
So we built a highlight reel generator powered by:
• EntreVista AI interview transcripts • Claude and Codex for clip selection • Remotion for video rendering via code • AWS S3 for instant share links
The system automatically: • Analyzes transcripts • Identifies high signal clips • Groups them by communication, role fit, and personality • Allows light manual adjustments • Renders a branded video in 5 to 10 minutes
No editing experience required.
Then we dive into Remotion and why “video as code” is one of the most underrated AI enabled workflows right now.
Finally, we discuss the growing cost of AI usage inside organizations: • Token spend management • Surprise AI bills • Model access guardrails • Productivity vs cost tradeoffs
AI is democratizing building.
But it is also introducing a new management layer.
New episodes every Friday.
⏱ TIMESTAMPS
(0:00) The problem: recruiters are not video editors (0:25) Welcome to Episode 36 (1:20) Why highlight reels improve candidate selection (2:30) The scalability issue with manual video editing (3:30) Demo: AI Highlight Reel Builder (4:15) How transcripts power automatic clip selection (5:00) Communication, role fit, personality grouping (6:10) Manual adjustments for recruiters (7:00) Rendering time and infrastructure challenges (8:00) Final sizzle reel output demo (9:00) How it was built with Codex (10:00) What is Remotion (11:30) Video editing as code explained (12:30) Other Remotion use cases: product trailers, documentation videos (13:45) Democratizing creative production (14:30) AI token costs inside organizations (15:15) Surprise AI bills and infrastructure lessons (16:30) Managing model access across teams (17:30) Productivity vs spend tradeoffs (18:15) Closing thoughts
Instead of hiring designers, copywriters, analysts, SEO specialists, and performance marketers… companies are starting to run AI marketing agents that handle everything.
From planning campaigns to creating content, analyzing performance data, generating ads, and optimizing strategy automatically.
In this episode of Built This Week, Sam Nadler and Jordan Metzner sit down with Iliya Valchanov, CEO of Juma, to explore how AI agents are transforming modern marketing workflows.
Juma is building an AI marketing super-agent that can autonomously plan, execute, and optimize marketing campaigns across channels like social media, ads, analytics, and SEO.
During the episode, Ilia demos how a single prompt can generate a complete social media strategy, content calendar, and visual assets in minutes.
Even more surprising — Ilia explains how their own company replaced a 7-person go-to-market team with just one person using AI agents.
We also dive into the future of AI agents, how developers are working with coding agents like Claude Code and Codex, and why the next wave of AI tools may turn websites into constantly evolving, self-optimizing systems.
In this episode we discuss:
• How AI agents automate entire marketing workflows • Turning a single prompt into a full social media calendar • Why marketing teams are early adopters of AI • How AI agents connect to tools like Google Analytics, HubSpot, and Meta Ads • Why saving time isn’t the real benefit of AI • How AI increases marketing quality and experimentation • How agencies measure ROI and billable hour savings from AI • Why companies need a dedicated “AI transformation leader” • Claude Code vs Codex vs Cursor for AI coding workflows • Andrej Karpathy’s new auto-research AI experiments
This episode is a glimpse at how AI agents may reshape marketing, coding, and digital products over the next decade.
⏱️ TIMESTAMPS
(0:00) Welcome to Built This Week (0:31) Introducing Ilia from Juma (0:46) What Juma is building (1:26) Live demo: AI marketing agent (2:10) Generating a social media calendar with one prompt (3:02) Researching competitors automatically (3:52) Building a full content strategy (4:30) Creating Instagram carousels with AI (5:21) Integrations with Google Analytics, HubSpot, and Ads (6:03) Can AI learn which content performs best? (6:49) Who is using Juma today (7:40) Marketing teams vs marketing agencies (8:05) Replacing a 7-person marketing team with AI (8:58) Publishing blog posts in 3 minutes (9:40) Why AI unlocks new marketing opportunities (10:27) Measuring ROI and billable hours saved (11:06) How AI removes the need for specialized marketing roles (12:00) Why ad optimization is the biggest AI opportunity (12:27) Biggest lessons from running AI agents in marketing (13:04) Why companies need an AI transformation leader (14:02) Claude Code vs Codex vs Cursor (16:00) The future of AI coding agents (18:56) Why developers are reading less code (20:45) How programming may change in the AI era (22:06) Andrej Karpathy’s new auto-research AI tools (24:38) AI experiments and self-optimizing websites (27:10) Final thoughts on the future of AI agents (28:06) Where to find Juma