When AI Makes Engineering Too Fast for Product Teams | Oji Udezue (ex-Typeform & Calendly)
Oji Udezue unpacks the “three-speed problem," where ENG, product, and GTM now move at radically different paces, and shares how teams can stay aligned as AI accelerates execution beyond.
TL;DR
In this episode of LaunchPod, we’re joined by Oji Udezue, product leader, former CPO at Typeform, and VP of Product at Calendly, to discuss how AI is completely revolutionizing traditional product development cycles.
Oji shares:
The “three-speed problem,” as Oji calls it — how AI will bring about a 10x increase in engineering velocity. But where does that leave product management and go-to-market teams if they can’t keep up?
Why AI is a BS term, as it’s really five new AND distinct capabilities – and how to use those as a framework for smarter product strategy
And how his “shipyard model” for product teams will ensure you keep up and thrive, even as AI reshapes how we build software
1. Redefine “PM craftsmanship” for the AI era (8:13)
Oji argues that the rise of AI tools changes what it means to be a great product manager:
“If you think about it, artificial intelligence is a meaningless word. What I ask builders, software executives, product people to do is to use different, more compelling and clear words.”
He introduces a framework of five true capabilities: generation, interaction, synthesis, personalization, and autonomy that help product teams talk more precisely about AI.
“Every conversation about AI — you say, which one of these five things are we talking about? You’ll have stronger conversations immediately.”
What product leaders can do: Train PMs to think in systems, not syntax. The new craftsmanship is sensemaking at speed, knowing which of AI’s five capabilities your product is actually leveraging.
2. When building gets faster than thinking (16:22)
Oji explains that AI has flipped the traditional product–engineering dynamic, but with AI-assisted coding, that constraint has vanished:
“The core limiting function of our teams for the longest time has been the speed of engineering. Everything we’ve done from waterfall to agile has all been to optimize slow engineering. Over the next ten years, engineering is going to accelerate by five and then ten X, maybe more.”
And that creates a new kind of risk:
“If product management and design don’t accelerate, it’s gonna logjam on the capacity to build. If go-to-market doesn’t accelerate, it’s gonna logjam on the capacity to build.”
What product leaders can do: Redesign your team rituals around decision velocity, not just delivery velocity. Replace long requirement cycles with rapid intent alignment.
3. Leadership in an age of abundance (18:25)
AI’s acceleration isn’t just a tooling challenge; it’s a leadership one. Oji explains that the new era demands sharper focus:
“If you have a ship with a warp-speed drive, and you’re pointing at 360 degrees of space, if you go fast in the wrong direction, you’ve just killed yourself.”
He warns against mistaking speed for progress:
“They will never stop. Who has ever made an engineering team stop?”
What product leaders can do: Create deliberate friction. When speed is free, focus becomes the scarcest leadership skill.
4. Human energy as the new competitive advantage (19:53)
Even as teams scale their capabilities with AI, Oji highlights how human energy becomes the ultimate differentiator:
“You can spend that capacity on refinement, making your product like a jewel. Every pixel looks beautiful. Every moment is a reward.”
But there’s a limit:
“Eventually those things get boring for engineers. What we really need to do is make the decision-making — the direction-finding — faster.”
What product leaders can do: Design systems that sustain energy and agency. The best teams will balance machine-level speed with human-level clarity and motivation.
Chapters
00:00: Introduction
1:21: Building Rocket Ships by Oji and Ezinne Udezue
1:55: What is the shipyard model in product?
5:20: The evolution of technology: Why AI is just a new technology level
7:50: The 5 flavors of AI
13:23: The limiting function of development is no longer the speed of engineering – but what is it now?
17:05: Solving the three-speed problem
21:32: Conclusion
Links
Resources
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