It’s Easy to Build an Average Product | Brendan Grove on AI, Startups, and Distribution
AI has made products faster and cheaper to build. But thatdoes not necessarily make them better.
In this episode of From Code to C-Suite, Liam sits down withBrendan Grove, co-founder of PrizeOut, to discuss what it takes to build and scale a startup when technology is making it easier than ever to get a product into market.
Brendan’s journey began in engineering before moving intoanalytics, data science and product at DraftKings. He later returned to entrepreneurship as a co-founder of PrizeOut, which evolved from gaming payouts into rewards technology for credit unions and their members.
Brendan explains why cheaper development can also create aflood of average products, why distribution increasingly matters alongside product quality, and why founders still need to understand the real problem they are solving.
They also discuss the difficult side of building a company,from deciding which fire actually matters to leading teams through uncertainty, learning from failure and knowing when raising more capital can create problems rather than solve them.
In this episode, we cover:
Brendan’s journey from engineering to DraftKings and PrizeOut
How PrizeOut evolved from gaming payouts to credit union rewards
Why AI is making products cheaper and faster to build
Why easier development can lead to more average products
Why distribution can matter as much as product
Staying focused when there are fires everywhere
Making difficult decisions without knowing if you are right
Building and leading teams through uncertainty
Why raising more money is not always the answer
Why founders have to become comfortable with failure
Building something has become easier.
Building something people genuinely want, distributing it and turning it into a scalable business is still the hard part.
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📲Connect with Brendan Grove
LinkedIn: https://www.linkedin.com/in/brendan-grove-63325966/ (https://www.linkedin.com/in/brendan-grove-63325966/)
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24 Sept 2026
Safer Payments Move Faster | Richard Hoffmann on Risk, Stablecoins, and Agentic Payments
Faster payments are only useful if you can trust them.
In this episode of From Code to C-Suite, Liam sits down with Richard Hoffmann, Head of Product at GrailPay, to discuss the risk infrastructure behind business payments, why trust matters so much in fintech, and what needs to happen before instant payments, stablecoins and agentic payments can scale.
Richard joined GrailPay as employee number three and has helped build the company across operations and product. Today, GrailPay uses first-party and third-party data with machine learning to help financial institutions better understand payment risk and make transactions safer and faster.
Richard also shares his unconventional journey into fintech, what he learned from working directly with founders, and why early-stage careers often require uncomfortable bets, patience and a willingness to learn from what does not work.
We cover:
• Why safer payments can become faster payments
• The hidden risk behind business payment delays
• Why trust matters more than hype in fintech
• Stablecoins and the future of payment rails
• Why agentic payments may be ahead of the market
• How AI could make financial fraud more sophisticated
• Making uncomfortable bets in startups
• Why patience matters early in your career
The future of payments may be faster and moreautomated, but better risk decisioning is what will make that possible.
📲 Connect with Liam Moir-Holland and From Code to C-Suite:
Instagram: https://www.instagram.com/liammoirholland/
LinkedIn: https://www.linkedin.com/in/liam-moir-holland-a194b3158/
LinkedIn (Podcast): https://www.linkedin.com/company/from-code-to-c-suite/
TikTok: https://www.tiktok.com/@code.to.csuite
📲Connect with Richard Hoffmann:
LinkedIn: https://www.linkedin.com/in/richwhoff/
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3 Sept 2026
Fintech Is Changing Again | Chris Hartley on AI, Product Leadership, and the Customer
Fintech is changing again. This time, AI is accelerating what is possible, but technology only matters if it solves a real customer problem.
In this episode of From Code to C-Suite, Liam sits down with Chris Hartley, Chief Product and Operating Officer at Kasheesh, to discuss more than 25 years in fintech, the evolution of product leadership, and how AI could reshape payments and financial decision-making.
Chris began his career on the front lines of a credit union before moving into fintech and spending more than a decade across eBay and PayPal. Today, he is helping build Kasheesh, a fintech platform that enables consumers to split purchases across multiple debit and credit cards, giving them more flexibility over cash flow and credit utilisation.
Throughout the conversation, Chris shares why staying close to the customer has shaped his entire approach to product, what he learned from building financial products at scale, and why product readiness and launch readiness are two very different things.
He also explores what happens as AI agents begin making purchasing decisions on behalf of consumers, the new problems that creates when transactions go wrong, and why product teams need to think beyond automation to trust, control and the overall customer experience.
In this episode, we cover:
• Chris’s journey through more than 25 years in fintech
• Building financial products at Fiserv, eBay and PayPal
• Why staying close to the customer matters at every stage of your career
• The difference between product readiness and launch readiness
• What a failed PayPal experiment taught Chris about testing and iteration
• Moving from individual performance to becoming a multiplier as a leader
• Why customer empathy matters when building financial products
• How AI agents could change payments and purchasing decisions
• What happens when an AI-controlled transaction goes wrong
• Why technology should always be tied to a real customer problem
• Building teams that are confident enough to make decisions and learn from mistakes
AI will change how financial products are built and used. The challenge is making sure the customer remains at the centre of every decision.
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