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Delivery Isn’t Free - All Things Product Podcast with Teresa Torres & Petra Wille

Delivery Isn’t Free - All Things Product Podcast with Teresa Torres & Petra Wille

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Everyone's saying it: "Now that AI makes delivery free…" But is it? In this episode of All Things Product, Petra Wille and Teresa Torres pull apart one of the most repeated claims in product right now.

They dig into why building a single feature has gotten dramatically cheaper — while building a real, production-quality product has not. Teresa breaks down what happens when teams treat coding agents as "free": spaghetti code, Frankenstein data models, feature bloat, and the maintenance nightmare waiting three weeks down the road. Along the way, they unpack the crucial difference between build to learn and build to earn, why the last 30% of a product is where the real work lives, and why AI products (not just AI-assisted code) are far harder to ship than the demos make them look.

If you've been tempted by the "delivery is free, taste/discovery is all that matters" narrative, this conversation is your reality check. Delivery got cheaper. It did not get free — and it never will.

Show Notes

  • Petra Wille and Teresa Torres take on the popular claim that AI has made software delivery essentially free — and explain why that framing falls apart the moment you care about shipping something real.
  • Why "building a single thing" getting cheaper doesn't mean delivery is cheaper — especially when teams respond by building far more things
  • The three-week feature spiral: how "free" delivery quietly produces Frankenstein data models, duplicated code in 17 places, and tanked performance
  • Why you still need a skilled engineering team observing and steering what AI produces — and why architecture decisions can't be outsourced to a coding agent
  • Build to learn vs. build to earn (via SVPG): throwaway prototypes for discovery are dirt cheap and great — as long as you actually throw them away
  • The app store paradox: apps released are spiking, but apps actively used stay flat — and how users are getting sharper at sensing "AI app slop"
  • Why AI products are a different beast than deterministic code — error analysis, evals, LLM-as-judge, prompt and orchestration iteration all take real time
  • A candid behind-the-scenes look at building AI-generated opportunity solution trees with Vistaly, and the quality issues only a domain expert can catch
  • The 60–70% trap: getting to a good-looking prototype is fast; closing the last 30% to a trustworthy product is months to years of work
  • The real hidden sentence: "Delivery is free" is almost always followed by "…so taste is all that matters" or "…so discovery is all that matters." Both are wrong. Delivery and discovery both matter — forever.

Notable Moments

"I don't think delivery is free. I don't think delivery will ever be free."

"By the time you're getting to feature 15, your data model looks like a Frankenstein strategy."

"The first 60 to 70% is easy. It's a prototype… Closing that last 30% is months to years of work."

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