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 and the CEO of Mironov Consulting, where he has advised more than 200 software companies over a 40-year career in Silicon Valley product management, including 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. BuilderWithin covered his related argument that faster AI coding concentrates product work rather than shrinking it three weeks ago.

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 list under “commercially deployable software” covers the unglamorous work AI-generated code skips by default: handling traffic and outages reliably, controlling who can access what data, a working test suite, a way for customers to get help when something breaks, and watching for the AI model’s answers drifting away from what customers expect as it keeps running. 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 coding tools have compressed the “executable code” tier from weeks to hours for a lot of prototypes, which is exactly why Mironov’s framing lands now. 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. AI just made it more visible by removing the excuse that code was the bottleneck.

What it means for builders

If you’re building with AI and a demo is working, resist treating that as “almost done.” Before you promise a launch date to a boss, a board, or yourself, walk your own project through Mironov’s three tiers and be honest about which one you’re actually in. A working prototype answers “can I build this.” It doesn’t answer “will someone pay for this,” and AI speed doesn’t shrink that second question at all.

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