What Comes Next with Arun – Détails, épisodes et analyse

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What Comes Next with Arun

Arunansu Pattanayak

Technologie

Business & Entrepreneuriat

Fréquence : 1 épisode/6j. Total Éps: 13

Most conversations about AI are either too technical for business leaders or too generic to be useful. What Comes Next with Arun fills that gap. Each episode translates real-world data and AI strategy into the language of competitive advantage — drawing on Arun’s 20+ years inside the world’s most complex enterprises, six years as a Microsoft Data & AI Executive, and his experience building Tipsora into a platform serving more than 95,000 professionals worldwide. This is not a podcast about AI tools. It is a podcast about building the organizational intelligence that makes tools matter.

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Données mises à jour le 19/09/2026

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Fluent in the Tools, Illiterate in the Tradeoffs — Frank Bravo on AI's Real Risk

vendredi 18 septembre 2026 • Durée 36:12

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Most organizations aren't behind on AI. They're behind on the thinking required to use it. That's where this conversation with Frank Bravo starts — and it doesn't let up.

Frank is a Bay Area technologist who spent more than three decades leading technology through disruption. For 32 years he was CTO of Embarcadero Media, home of the Palo Alto Weekly, where his team published an entire newspaper's editorial content to the web in 1994 — before Google, before Yahoo, before most people had a browser. Today he's CTO of ProLegal, a legal-services startup, principal of Bravo IT Consulting, and host of the Your Tech Makeover podcast.

Arun and Frank dig into what watching one industry get disrupted for 30 years actually teaches you about this AI moment — including the uncomfortable part, that being early with the tool was never the advantage everyone assumed. They talk about why Frank now builds software faster than ever with AI but lets none of it ship without human review, how a 15-person startup went from idea to launched product in under three months, why every law firm is sitting on the same unsolved problem, and why the hardest part of any technology shift was never the technology.

Frank's throughline is simple and hard to argue with: companies are fluent in the tools and illiterate in the tradeoffs. Clarity isn't decoration on top of strategy — it is the strategy.

Chapters

(0:00) The thinking gap
(0:40) Meet Frank Bravo
(1:50) Common ground — the Future-Proof framework
(3:13) From a computer in the house to CTO of a newspaper
(4:44) Publishing to the web in 1994
(5:33) Leaving a 32-year career for a startup
(6:11) Media to legal: technology is technology
(8:00) Remote work, and seeing it coming before COVID
(10:00) How Your Tech Makeover was born
(14:30) ProLegal as a platform for law firms
(15:13) ProLegal Talent — idea to launch in under 3 months
(17:44) Can AI give legal advice? Where Frank drew the line
(18:41) Building fast with AI — and why nothing ships unreviewed
(20:34) AI behind the scenes: funding personal-injury cases
(22:20) Autonomy, ownership, and a small team that ships
(25:11) Unlimited R&D: the tool that runs a law firm
(29:05) Open source, standards, and data you can actually move
(31:15) Regulation, education, and building things people understand
(33:42) What's launching, and where to find Frank

If this shifted how you think about AI in your organization, follow What Comes Next with Arun and leave a 5-star review — it genuinely helps the show reach more leaders.

Guest — Frank Bravo
Your Tech Makeover: https://www.yourtechmakeover.com
Bravo IT Consulting: https://www.bravoitc.com
LinkedIn: https://www.linkedin.com/in/fabravo/
Newsletter: https://yourtechmakeover.substack.com

Host — Arun
Website: https://www.arunansupattanayak.com/
LinkedIn: https://www.linkedin.com/in/arunansuspeaks/
Book — Future-Proof Your Business: https://www.amazon.com/FUTURE-PROOF-YOUR-BUSINESS-Strategic-Framework-ebook/dp/B0H8MKQTKC

Support the show

Arun's book, Future Proof Your Business:
https://www.amazon.com/FUTURE-PROOF-YOUR-BUSINESS-Strategic-Framework-ebook/dp/B0H8MKQTKC

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The Trust Layer for AI Agents — Ravi Bijlani, KYXStart.Ai

vendredi 11 septembre 2026 • Durée 48:20

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Your AI agent can book a flight, move money, and open accounts on your behalf. But it can't take a selfie or hold a driver's license — so how does anyone know it's really acting for you?

Arun sits down with Ravi Bijlani, founder and CEO of KYXStart.Ai, who is building the trust and verification layer for the agentic era. Ravi spent 24 years in identity and payments before betting that the real bottleneck in AI wouldn't be intelligence — it would be trust.

In this conversation:
– Why "card-not-present" is becoming "human-not-present"
– KYC for AI agents (KYCA): verifying who — or what — is on the other end of a transaction
– Binding an agent to a device and a verified human, with guardrails ("don't book a flight over $500")
– The coming protocol wars between Google, Stripe, Mastercard, and Visa — and why KYXStart sits above all of them
– How the business actually makes money when the underlying standard is open
– The financial-inclusion endgame: identity with nothing but a phone number and a selfie

Chapters
00:00 – Most organizations aren't behind on AI — they're behind on the thinking
00:41 – Meet Ravi Bijlani and KYXStart.Ai
02:50 – The gap Ravi saw: 24 years in identity and payments
05:10 – Why agents need a trust layer
06:27 – The scale: 180+ countries, billions of identities
07:50 – How this differs from managed identity and RBAC
09:30 – Static identity → signal-based identity; "human-not-present"
11:20 – Guardrails and the $500 flight: KYC for agents
13:50 – Accountability and the agent registry
15:00 – Is there a global standard? The protocol wars
18:00 – Where KYXStart plays: the trust layer on top
21:00 – Monetizing an open standard
26:40 – Diversifying: agent onboarding for banks today
30:00 – Turning it into a platform: AML and risk scoring
33:25 – Team structure: 21 people, founder's mentality
38:20 – The R&D vision: a golden record and financial inclusion 42:00 – Partnerships, the ecosystem, and the tipping point 46:20 – Close

The AI Family Office: Financial Advice for High Earners — with Lord Munjal

vendredi 4 septembre 2026 • Durée 37:04

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High earners rarely lose money because they make bad decisions. They lose it in the gaps — between a financial advisor who only sees stocks and bonds, a CPA who shows up 60 days before the deadline, an insurance agent working a different angle, and an estate plan that's either missing or out of date. Nobody is coordinating the whole picture.

In this episode, Arun sits down with Lord Munjal, Founder & CEO of Alpheva AI, who is building a financial operating system for high earners — an "AI family office" for the people who earn well but were never big enough to afford the real thing.

Using the five stages of the Double Advantage Cycle from Arun's book Future Proof Your Business, they trace how Alpheva found its nest, diversified into education, opened its platform to advisors, built an ownership-minded team, and is now moving toward agentic execution of your money.

In this episode:

00:00 Cold open: behind on AI, or behind on the thinking?
00:38 Meet Lord Munjal and Alpheva AI
01:08 The Double Advantage Cycle framework
02:46 Finding the niche: the origin of Alpheva
03:53 The hidden problem — high earners lose money in the silos
07:05 Democratizing the family office for $400K+ earners
11:55 How the AI and human experts actually coordinate
15:56 AFI vs AGI: vertical intelligence, not general
16:29 Diversifying into education and a future social layer
22:26 Opening the platform to CPAs and advisors
25:18 Build Your Own Alpha: an ownership-minded team
28:02 R&D: agentic execution of your money
31:08 Crypto, metals, and surfacing opportunities
33:00 Shaping the external environment
35:13 Where to find Lord and a listener offer

🔗 Connect with Lord Munjal LinkedIn: https://www.linkedin.com/in/lordmunjal/
Alpheva: https://alpheva.com
Listener offer: use code Arun100 for 10% off

Subscribe and leave a 5-star review — it helps more builders find the show.

Building an AI-Native Platform to Take On the Bloomberg Terminal — with Aidan McConnell

vendredi 28 août 2026 • Durée 48:16

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Most conversations about AI in finance stop at "we use AI." This one goes deeper.

Aidan McConnell started as a data science intern at Sezzle in 2019, worked his way up to Head of AI/ML, then left to build QuantLink AI — a vertically integrated data and analytics platform for investors. Think premium market data, quant workflows, and institutional-grade charts, made accessible enough that a first-time investor can actually use them.

In this episode, Arun and Aidan trace the build using Arun's five-stage framework for sustainable success — and Aidan gets specific about the decisions most founders gloss over:

Why 100% of QuantLink's software is written by AI — and the ontology and deterministic validation that stops it from hallucinating "slop"
The gap he saw in a market already crowded with Bloomberg, Merrill, and Schwab
Why exposing all of their code became a trust strategy for a young company with no institutional track record
The surprise: customers didn't come for the AI — they came for the charts and the reports
Where the platform goes next: an open marketplace for data, models, agents, and templates
His bet on the future of AI architecture — deterministic graphs over generated code

Chapters

00:00 — The thinking gap: why organizations fall behind on AI
00:28 — Meet the guest: Aidan McConnell, QuantLink AI
01:08 — Arun's five-stage framework for sustainable success
02:34 — Finding the niche: the gap in a saturated market
05:49 — Flipping the game: letting users build their own signals
08:30 — The B2B shift and user responsibility
09:51 — Transparency as a trust strategy
11:27 — Building the core: AI-first, human layer on top
12:24 — Ontologies and deterministic validation
16:00 — The eval harness: data-fetching vs. product layer
21:30 — Diversification: charts, reports, and the "boring" wins
28:28 — Becoming a platform: the open marketplace vision 31:20 — People and the ownership mindset 35:10 — Affiliates and incentives 36:37 — R&D: vertical models and the future of AI architecture 41:03 — The external environment: regulation and consumer education 44:21 — What's shipping next + how to try it

Competitive Intelligence Architecture: The Real Source of AI Advantage

vendredi 21 août 2026 • Durée 08:09

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In the finale of this series, Arunansu Pattanayak brings together every framework from the show into a single worldview — one he argues is the most important strategic idea for any leader heading into the next decade.

The claim is simple and uncomfortable: the winners won't be the organizations with the best AI. They'll be the ones that build the most intelligent architecture underneath it. Tools are commoditized. Buying the same software as your competitor gets you the same capability as your competitor. What compounds — and what can't be quickly copied — is the intelligence architecture beneath the tools.

This episode names that idea directly: competitive intelligence architecture — the invisible infrastructure of the intelligence economy, as decisive now as electricity and transportation networks were in the 20th century.

In this episode:

Why more AI alone doesn't make you more competitive
The one shift every leader should make: from "what tools?" to "what architecture?"
Technology-first vs. architecture-first thinking — and why the reversal matters
The three sources of durable advantage that can't be reverse-engineered
Three concrete things to do after nine episodes of frameworks

Chapters

00:00 — Behind on the thinking, not the tools
00:38 — One complete worldview
01:08 — Pulling the threads together (the series recap)
02:25 — Naming it: competitive intelligence architecture
03:07 — Intelligence as the new invisible infrastructure
03:35 — The one shift: from tools to architecture
04:14 — Durable advantage: three things that can't be copied
05:27 — Three things to do now
06:29 — The question underneath everything
07:23 — Where to go next

Subscribe and leave a 5-star review — it's the fastest way to help another leader find the show.

🎧 Apple: https://podcasts.apple.com/us/podcast/what-comes-next-with-arun/id6788060249 🎧 Spotify: ▶️ YouTube: 🌐

Why Your AI Strategy Is Already Obsolete

mercredi 12 août 2026 • Durée 08:25

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Most organizations aren't behind on AI. They're behind on the thinking required to use it.

In this solo episode, Arunansu Pattanayak makes a prediction: if your AI strategy is built around specific tools, platforms, and vendors, most of that document will be obsolete within 12 months — not because your team planned badly, but because you built on the fastest-moving layer of the stack instead of the slowest.

Arun breaks down why vendor-driven thinking feels like strategy but quietly hands your direction to someone else's roadmap, why technology roadmaps fail for a structural reason, and how to reframe the whole thing around durable capabilities: evaluating and integrating new tools fast, governing your data well no matter the platform, and retraining teams as workflows shift.

You'll walk away with a one-exercise action item you can run on your current strategy doc this week — and a simple test for whether you have a real strategy or just a procurement list.

Build the long-term intelligence system first. Let the tools rotate through it.

Subscribe and leave a 5-star review.

Support the show

Arun's book, Future Proof Your Business:
https://www.amazon.com/FUTURE-PROOF-YOUR-BUSINESS-Strategic-Framework-ebook/dp/B0H8MKQTKC

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The Technology Was Never the Problem

vendredi 31 juillet 2026 • Durée 07:58

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Most organizations bought the AI. What they skipped was the thinking required to make it matter.

In this solo episode, Arunansu Pattanayak sets aside the frameworks and tells one story — the moment, after 20+ years inside Merrill Lynch, Citibank, Credit Suisse, JP Morgan, TD Bank, and Microsoft, when he finally understood what actually breaks in transformation. It was never the technology.

He unpacks why technically excellent systems fail to change anything: people keep using old workarounds no one asked about, leadership announces "data-driven decisions" while the culture keeps making the same instinct-driven calls, and departments quietly guard their own version of the truth because controlling the data means controlling influence. None of those are technology problems. They're organizational behavior problems wearing a technology costume.

The episode closes on the realization that reshaped how Arun works: intelligence architecture isn't a technical framework — it's a sequencing philosophy. Governance, culture, and decision-making readiness, built deliberately in the right order, alongside the technical build rather than bolted on after.

This week's action item is inside.

Subscribe and leave a 5-star review if this shifted how you think about AI in your organization.

Support the show

Arun's book, Future Proof Your Business:
https://www.amazon.com/FUTURE-PROOF-YOUR-BUSINESS-Strategic-Framework-ebook/dp/B0H8MKQTKC

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Future-Proofing Is a Myth. Build Change Fitness Instead

mercredi 22 juillet 2026 • Durée 08:20

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Most organizations aren't behind on AI. They're behind on the thinking required to use it.

In this solo episode, Arunansu Pattanayak makes an uncomfortable argument for anyone who has ever built a five-year strategic plan: future-proofing, as most people define it, is a myth. Complex systems don't behave predictably over multi-year horizons — and the further out you forecast, the more confident the prediction sounds and the less likely it is to be right.

That combination of high confidence and low accuracy is what makes long-range prediction dangerous as a strategic foundation. When leadership bets three years of investment on a confident call, they don't just risk missing a target. They allocate resources, build org charts, and architect systems around an assumed future — and end up with a structure that actively resists the future that actually arrives.

The alternative is what Arun calls change fitness. Borrowed deliberately from physical fitness: you don't train for one specific challenge you're certain is coming. You build general strength, flexibility, and conditioning so your body can respond to whatever shows up.

In this episode:

Why forecasting and adaptability are different questions that lead to different investments
The strategic rigidity trap — how confident predictions get hard-coded into org charts and architecture
What change-fit organizations actually build: modular architecture, short feedback loops, distributed decision authority
Why strategic plans should be treated as living hypotheses, not fixed commitments to be defended
The one question worth more than any five-year forecast

The question to sit with: What capability would make us stronger — regardless of what happens next?

Subscribe and leave a 5-star review to help more leaders find the show.

Get certified and explore what we're building at tipsora.com Connect with Arun: arunansupattanayak.com

More AI Won't Make You More Competitive — Here's What Will

mercredi 15 juillet 2026 • Durée 08:21

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Most organizations are not behind on AI. They are behind on the thinking required to use it.

In this solo episode, Arunansu Pattanayak — ex-Microsoft Data and AI executive and CEO of Tipsora — makes an argument that might sound strange coming from someone who has spent his career in AI: more AI is not going to make your organization more competitive.

The large language models, copilots, and agentic systems everyone is racing to adopt are becoming commodities. Your competitor can license the same tools, read the same case studies, and hire the same talent. If you can buy it, it cannot be the source of your edge.

Arun breaks down what actually creates durable competitive advantage in an intelligence-driven economy:

Why tools, use cases, and even talent are copyable — often within a single quarter
The three things competitors cannot replicate: proprietary data, decision culture, and architecture
The first-mover myth: why being first with a new AI tool buys you headlines, not advantage
The difference between organizational intelligence and AI dependency — and why one is durable while the other is rented
A practical action item: how to identify the one advantage AI alone cannot create for your competitors

If this episode shifts how you think about AI strategy, share it with someone who needs to hear it — and subscribe and leave a 5-star review so more leaders can find the show.

Connect with Arun:

Website: https://www.arunansupattanayak.com/
LinkedIn: https://www.linkedin.com/in/arunansuspeaks/
AI certifications for you and your team: tipsora.com

Support the show

Arun's book, Future Proof Your Business:

The 5 Layers Every AI-Ready Organization Needs (In Order)

dimanche 12 juillet 2026 • Durée 11:23

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Most organizations don't have an AI problem — they have a sequencing problem. They're building layer four before laying layer one.

In this solo episode, Arunansu Pattanayak, ex-Microsoft Data & AI executive and CEO of Tipsora, draws on 20+ years across financial services, enterprise technology, and beyond to lay out a five-layer framework for building an organization that actually wins in an intelligence-driven economy:

Layer 1: Data governance and architecture — the unsexy foundation everything else inherits
Layer 2: Intelligence infrastructure — ending the "three departments, three versions of the truth" problem
Layer 3: Data as a business model — turning data from cost center to profit center
Layer 4: AI-driven decision culture — a human transformation, not a technical one
Layer 5: Competitive durability — the outcome you can't buy, only build

Plus the one question every leader should answer before this episode ends: which layer is your organization's weakest link?

Ready to move from thinking to building? Get certified at tipsora.com or connect at arunansupattanayak.com.

If this episode shifted how you think about AI readiness, subscribe and leave a 5-star review.

Support the show

Arun's book, Future Proof Your Business:
https://www.amazon.com/FUTURE-PROOF-YOUR-BUSINESS-Strategic-Framework-ebook/dp/B0H8MKQTKC

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What Comes Next with Arun – Détails, épisodes et analyse

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Apple Podcasts

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Amazon1

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