Aakash Gupta

How to Build AI Products in FinTech ($100B Robinhood VP Lessons)

Abhishek Fatehpuria, VP of Product at Robinhood, reveals how they built a $100B fintech empire and why most product teams fail in regulated industries. He breaks down the "swipies" framework that forces product clarity, the 60+ experiments behind their breakthrough referral program, and how to transform legal teams from blockers into enablers. ---- Transcript: https://www.news.aakashg.com/p/abhishek-fatehpuria-podcast ---- ⏰ Timestamps: 00:00 Intro 01:34 Robinhood's AI Assistant: Cortex 08:01 Advice for Products in Fintech 12:10 IPO Stories 14:37 Ads 16:31 How To Build Innovative Products 21:30 Why Most Fintech PMs Fail at Experimentation 27:15 Ads 28:54 Training the Team 30:48 Abhiskek Journey at Robinhood 39:40 Layoffs 47:02 Robinhood's Scaling Journey (2016-2025) 52:54 Should Prototypes Replace PRD's 1:05:40 Why most Fintech PMs are Failing 1:10:48 How To Build a Real Product 1:18:08 Outro ---- 🏆 Thanks to our sponsors: 1. Kameleoon: Leading AI experimentation platform - kameleoon.com/prompt 2. Mobbin: Discover real-world design inspiration - https://mobbin.com/?via=aakash 3. AI Evals Course for PMs & Engineers: Get $1155 off with code ag-evals - https://maven.com/parlance-labs/evals?promoCode=ag-evlas 4. Amplitude: The market-leader in product analytics - https://amplitude.com/session-replay?utm_campaign=session-replay-launch-2025&utm_source=linkedin&utm_medium=organic-social&utm_content=productgrowthpodcast ---- How Robinhood Built a $100B Fintech: 1. Build AI products around problems customers already have rather than creating AI for AI's sake - Robinhood identified core pain points like "why did this stock move?" then built solutions that fit existing workflows instead of forcing new behaviors. 2. Write your product's "swipeys" (onboarding screens) before building anything to force clarity on value proposition. If you can't convince a customer to hit "get started" in one sentence on mobile, you don't have a great product. 3. Curate upstream data sources and focus on information rather than recommendations when building AI for regulated industries. Robinhood secures licenses with news providers while carefully prompting AI to avoid investment recommendations that trigger regulatory issues. 4. Transform legal teams into product partners by hiring domain experts who get excited about building great customer experiences within regulatory constraints. Former SEC regulators who understand both rules and product vision push for better solutions rather than adding friction. 5. Obsess over pixel-perfect details because great design shouldn't be reserved for high-net-worth customers in financial services. When the CEO spends time on animation details, it creates a competitive moat where most companies use bad design as barriers. 6. Test everything relentlessly instead of copying surface tactics - Robinhood's referral program went through 60+ iterations, evolving from $10 cash to variable stocks. Most fintechs copy "$20 for $20" without understanding the deeper insight: give users your core service, not generic rewards. 7. Democratize access by speaking to customer pain points rather than industry jargon. "Get in at the IPO price" addressed frustration of watching stocks gap up from $20 to $50 on opening day, making access emotionally resonant. 8. Unite cross-functional teams under shared business goals by switching from functional silos to business unit GMs. This eliminates "death by a thousand departments" where each function adds friction without considering holistic customer experience. 9. Think mobile-first to force clearer communication and simpler flows since mobile constraints eliminate unnecessary complexity. Even internal planning revolves around what features will be showcased in mobile-centric product keynotes. 10. Ship meaningful features consistently to create a virtuous cycle where teams stay focused and the market recognizes you as an innovation engine. This product velocity compounds into sustained performance by demonstrating consistent execution capability. ---- 👨‍💻 Where to find Abhishek: LinkedIn: linkedin.com/in/abhishekfatipurya Twitter: https://x.com/abhishekf96 Robinhood: https://robinhood.com/us/en/ ---- 👨‍💻 Where to find Aakash: Twitter: twitter.com/aakashg0 LinkedIn: linkedin.com/in/aagupta/ Newsletter: news.aakashg.com #Fintech #ProductManagement #Robinhood #AIProducts #Experimentation ---- 🧠 About Product Growth: The world's largest podcast focused solely on product + growth, with over 187K listeners. Hosted by Aakash Gupta, who spent 16 years in PM, rising to VP of product, this 2x/week show covers product and growth topics in depth. 🔔 Subscribe and turn on notifications to master fintech product building!

AGAakash GuptahostAFAbhishek Fatehpuriaguest

Sep 11, 2025·1h 18m·Watch on YouTube ↗

📖 CHAPTERS

1. 1

   Robinhood at $100B: why this conversation matters

   Aakash frames Robinhood’s recent surge in market cap and introduces Abhishek Fatehpuria, the VP of Product behind many core brokerage experiences. The episode is positioned as a rare look into Robinhood’s product-building playbook in a highly regulated domain.

2. 2

   Cortex AI assistant: solving “why did this stock move?” in the user workflow

   Abhishek explains Robinhood Cortex and the first shipping use case: Stock Digest. The goal is not to add AI for novelty, but to compress the investor’s research loop directly inside moments users already experience in-app (e.g., reacting to price-move notifications).

3. 3

   AI guardrails in FinTech: trust, licensing, and “no recommendations (yet)”

   The discussion turns to what makes AI product development different in finance: regulatory constraints and the need for customer trust. Abhishek outlines their approach—curate inputs, control outputs, and avoid crossing into advice until the bar can be met.

4. 4

   From AI demos to product roadmap: Trade Builder and problem-first AI strategy

   Abhishek shares Cortex’s broader concept beyond Stock Digest, including a Trade Builder that helps turn a hypothesis into an executable trade. The unifying theme is starting from validated customer problems and designing AI around them—not building AI “because AI.”

5. 5

   Advice for FinTech PMs building AI: regulatory fluency, realism, and patience

   Abhishek generalizes lessons for PMs: understand what the tech can do, understand what regulation allows, and progress incrementally. He emphasizes that trust in money-related AI is earned step-by-step for customers, legal partners, and regulators.

6. 6

   Tokenization explained: stock tokens and demand for private-company access

   Aakash asks about the Cannes presentation where Robinhood announced tokenization efforts. Abhishek explains stock tokens as “stablecoins for stocks” to improve international access, and highlights strong retail demand for investing in private companies that stay private longer.

7. 7

   IPO Access: how Robinhood gets retail into IPO allocations

   Abhishek tells the origin story of IPO Access and how the product works operationally. Robinhood joins the selling group, collects retail indications of interest during the roadshow period, shares demand with underwriters, and allocates shares based on what’s granted the night before listing.

8. 8

   Robinhood’s innovation DNA: value + delight, plus “Swipeys” as working backwards

   They zoom out to what makes Robinhood’s product approach distinct in regulated products that are hard to reinvent. Abhishek describes a consistent bar: ship products that deliver meaningful customer value and a delightful experience, and use “swipeys” (mobile onboarding screens) to force clarity early.

9. 9

   Polish, pixels, and partnering with Legal without “Frankenstein” outcomes

   Aakash probes how Robinhood avoids death-by-a-thousand-departments in regulated launches. Abhishek credits deep domain expertise in legal/compliance, a culture of shared product ownership, and specific behaviors: assume good intent, sell the vision, and deeply understand the underlying rule/issue.

10. 10

    Robinhood scaling and key moments: joining in 2016, mission breadth, events, and the IPO

    Abhishek reflects on why he joined (talent density) and what kept him (product craft and ambition). They discuss product velocity, Robinhood’s product events as a focusing mechanism, and the emotional highs of the IPO alongside brand lows during 2021 controversies.

11. 11

    Org structure and planning: GM business units, goals over OKRs, and strategic metrics

    The episode shifts into operating model: Robinhood moved to GM-aligned business units (brokerage, crypto, money) after the 2022 RIF, bringing many functions under shared orgs. Abhishek explains planning via big bets and keynote-driven roadmaps, plus simplified goal-setting and core strategic arcs/metrics.

12. 12

    How PMs use AI internally + PRDs vs prototypes in regulated product work

    Abhishek shares how he wants PMs using AI today: early ideation, research, and reducing administrative toil, while cautioning against expecting deep product insight from AI-generated PRDs. He argues prototypes and “swipeys” are better for product reviews, though PRDs still matter in FinTech for edge cases and regulatory detail.

13. 13

    Experimentation mastery: the referral program’s evolution and why many PMs stop too early

    Abhishek recounts his early growth work building Robinhood’s referral program, emphasizing relentless iteration. The biggest unlocks included switching from cash to variable stock rewards, adding a “claim your stock” action to drive activation, and follow-up nudges that reinforced ownership.

14. 14

    Career and leadership lessons: rising from intern to VP and picking the next ‘inevitable’ company

    The conversation closes with Abhishek’s personal trajectory—from engineering intern to VP—and the habits he credits: embracing detail work, showing up for cross-functional partners, and building trust. He also offers a framework for students: find post-PMF inevitability, responsible/lean founders, and companies that invest in people.