Rich Mironov keeps having the same conversation twice. A solo builder waiting for customers to show up. A CEO who promised the board that faster development means faster revenue. Both are mixing up two different things: code that runs, and a product that sells.

In a post extending his earlier “Code Isn’t Product” argument, Mironov writes: “I had two more discussions this week with folks confusing ‘code’ with ‘product.’” He splits the gap into three tiers. “Executable code does something and runs without crashing,” he writes. “Commercially deployable software is executable code that also meets the reasonable expectations of paying customers.” And “Revenue-ready product is commercial-deployable software plus everything else we need to generate an ongoing revenue stream.”

Who Mironov is

Mironov is a product management consultant who has advised more than 200 technology companies. His experience includes six startups and 15 interim VP or Chief Product Officer roles. He wrote The Art of Product Management and publishes the newsletter Rich Mironov’s Product Bytes. His related argument is that faster AI coding concentrates product work rather than shrinking it.

What he gets right, and where it’s incomplete

Mironov’s three-tier split names a real, specific failure mode: teams that measure progress by “did the code ship” when the actual goal is “did revenue show up.” His “commercially deployable software” tier covers work a functioning prototype may not include:

  • Handling traffic and outages reliably.
  • Controlling data access and testing expected behavior.
  • Helping customers when something breaks.
  • Monitoring AI answers as inputs and customer needs change.

His “revenue-ready” tier goes further: pricing and packaging, a sales process, contracts, renewals, and legal and compliance sign-off.

Where the post is thinner is on prioritization. Mironov lists the ingredients but doesn’t say which ones are true blockers for a first paying customer versus which can wait months. A single-founder tool doesn’t need the same crisis-response procedures as an enterprise platform on day one. Builders reading his full list need to triage it, not treat it as a fixed order of operations.

Why it’s notable

AI tools can shorten prototype development. Mironov’s question is what then becomes the next obstacle to revenue. When the code part gets dramatically faster and the other parts don’t, the gap between “it runs” and “it sells” becomes the thing that actually decides whether a build succeeds. That gap always existed. Faster coding makes it easier to see the next bottleneck.

What it means for builders

If you’re building with AI and a demo is working, resist treating that as “almost done.” Before promising a launch date, identify which requirements in Mironov’s tiers your project has met and which remain. A working prototype answers “can I build this.” It doesn’t answer “will someone pay for this,” and faster code alone does not answer that second question.

End of article