Why Most AI Projects Stop at v1

Building got easy. Running didn't. Most AI assistants die within 90 days, killed by a question nobody asked before launch: "who's maintaining this?"

Building got easy. Running didn't. Most AI assistants die within 90 days, killed by a question nobody asked before launch: "who's maintaining this?"

The demos impress. Budgets get approved. POCs have been multiplying across marketing teams for eighteen months.

Then the v1 becomes a tombstone. Still live, still billed, less relevant every week. Nobody dares touch it.

The technology didn't fail. It's the after-launch that nobody planned.

The Disposable POC

Industry reports converge: 60 to 70% of enterprise AI initiatives never make it past the pilot phase. Not for lack of ambition. For lack of infrastructure to operate a conversational system over time.

The disposable POC always follows the same script. An agency delivers in six weeks. The demo convinces. It goes live. Then user feedback arrives, the offer changes, a better model ships, and there's no owner, no tooling, no budget to iterate.

The budget covered the build. Nobody budgeted the operation. A conversational experience isn't a deliverable you sign off on: it's a living product you run.

Three Frictions That Turn v1 Into a Tombstone

First: the prompt belongs to engineering. Changing the assistant's behavior requires a ticket, a developer, a deployment. So even when user feedback is unambiguous, nothing moves.

Second: nobody sees anything. Without conversation metrics, there's no way to know whether users are asking unanswered questions, or whether a conversion path is broken somewhere. You're flying blind, which means you're not flying at all.

Third: no governance. Who changed what, when? Without history, every modification is a leap of faith. The assistant becomes a black box nobody dares touch. Six months post-launch, it answers exactly like day one, same mistakes included.

This isn't an LLM problem. The problem isn't GPT-4. It's zero context, zero scenario, zero memory, and zero loop to fix any of it.

Run It, Don't Re-Deliver It

At Scenaro, the premise is the opposite: a conversational experience is a living product, and the infrastructure must make iteration mundane.

In the Cockpit, every publication generates an immutable version. You publish to staging, then production. You compare two versions. You roll back when something breaks. It's "git for conversations", but usable by a marketing team, no tickets, no deployments. That's the concrete answer to "who's maintaining this?": the team that knows the customers, autonomously.

On visibility, conversations are analyzed automatically: unanswered questions, recurring topics, and drop-off moments surface every week. Iteration stops being intuition and becomes a loop fed by reality.

That's the difference between Club Français du Vin, Urbansider, or Lupi, production experiences that keep evolving, and the POCs that fade out in silence.

And there's a reason to build this muscle now rather than in two years. Every brand will soon talk directly with its customers, just as mobile apps forced everyone to "think mobile," the next design reflex will be thinking conversation-first. Teams learning to run conversational products today will be three years ahead of those still re-delivering POCs.

Building...

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The full article lives on Scenaro: Why Most AI Projects Stop at v1

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