The AI Throughput Illusion: Why Expensive Models Don't Equal Shipped Code

The AI Throughput Illusion: Why Expensive Models Don't Equal Shipped Code

Noah Labhart - Startup Founder & CTO

Related Episode

S12 E28: The AI Throughput Illusion: Why Splurging on Expensive Models Fails to Ship Code and How to Measure Real Engineering Output with Emilie Schario, Co-Founder & Head of Product & Engineering at Kilo Code

In this episode, Emilie Schario, Co-Founder and Head of Product & Engineering at Kilo Code, challenges the conventional wisdom that splurging on the most expensive AI models is the path to faster development. She shares how Kilo is redefining what it means to measure real engineering output in the age of AI coding assistants.

Key Takeaways

  1. Model Freedom Beats Model Lock-In
    The real competitive advantage isn’t being tied to one AI provider. Kilo’s approach of offering access to 500+ models—from OpenAI and Anthropic to open-source alternatives like DeepSeek and Grok—lets teams choose the right tool for each task, not just the most expensive one.

  2. The MVP Goalposts Keep Moving
    In AI tooling, what counts as a minimum viable product changes every few weeks. What seemed cutting-edge two months ago (single-turn prompts) is now table stakes, and new expectations (like agentic loops) emerge constantly. Stay flexible or get left behind.

  3. Engineering Is No Longer the Bottleneck
    With AI doing more of the heavy lifting, the real constraint shifts from “can engineers build this?” to “does this feature build a sustainable business?” Product managers need to focus on what customers will actually pay for, not on managing engineers’ capacity.

  4. Sometimes You Have to Kill Features to Win
    Kilo’s decision to sunset the App Builder—despite users loving it—shows mature product thinking. When resources are limited, shipping a subpar experience is worse than being honest about what you can’t support. Make the hard calls early.

  5. Daily Standups Beat Long-Term Roadmaps
    In a space evolving this fast, traditional six-month and five-year plans are fiction. Kilo sets ambitious daily goals and factors in enterprise needs, community feedback, competitor moves, and team energy. Agility and responsiveness matter more than rigid planning.

  6. Your Power Users Should Be Your Team
    The best way to know if your product is working? Build it with your own product. Kilo’s engineers use Kilo to build Kilo every day, which means product feedback flows naturally and dogfooding catches problems fast.

  7. Small, High-Bar Teams Punch Above Their Weight
    Kilo operates with just 35 people globally, but they’re structured to move fast: product engineers with autonomy, daily goal-setting, and a relentless focus on hiring A-players. No politics, no bloat, just execution.

Want to hear Emilie dive deeper into how Kilo navigates the chaos of building in the AI era, why her team’s on-call process nearly broke when Kilo went down, and what it takes to compete against well-funded incumbents? Listen to the full episode now.