The Missing Step in Vibe Coding Is Verification — How to Make 'Done' Provable

AI can build a working prototype in minutes. That does not mean it built what you asked for.

The problem that has long affected software development is showing up in AI-assisted coding: requirements get translated into something that looks right, get marked complete, and never get properly verified. The result is missing functionality, incomplete logic, or a system that works differently from what was specified.

The answer is simple: verify what actually shipped. Define how each requirement will be tested before the work begins, then check the live result against that standard. The principle applies equally to vibe-coded tools, technical SEO fixes, and the results you report to clients.

AI can build it. You still have to verify it

Use the AI. Prompt the prototype. Run the crawl in whatever tool you trust. None of that is the problem. The problem is stopping there and calling it done.

Donna Rougeau, founder of Protected By ALFIE, calls the alternative vibe and verify: use the tools, but verify the result against a standard you set before you started.

Whether you are shipping an AI visibility platform, running technical audits, or advising clients on how AI systems retrieve and cite their content, you are making claims someone else will rely on — often to spend money. Ownership does not come from running the tool or forwarding the ticket. It comes from being able to show that the result matches what you intended.

When 'done' wasn't done

Rougeau describes auditing her own platform's code line by line against the specification she had written. Not a status meeting — an actual read of the code.

What she found: a core component responsible for scoring and evaluating content trustworthiness was described in documentation, referenced in client-facing materials, and absent from production. Not partially built. Not buggy. Absent.

The root cause was mundane. She had built working prototypes of that logic months before handing engineering off. The files existed the whole time but were never ported into the live platform. The gap sat underneath eight months of status updates that never mentioned it.

A second version of the same failure surfaced: something the backend computed was being reported as something the client received. Those are not the same claim. Once she asked whether the result actually reached the client's eyes rather than just the server, two more gaps turned up.

None of it was caught by asking "is it done?" It was caught by refusing to accept the answer without evidence.

Why this is not somebody else's story

We are now applying the same shortcut to software through vibe coding: prompt an AI directly, skip the developer handoff, get a working product faster.

But removing the handoff does not remove the underlying problem. A vague specification handed to AI produces the same drift as a vague specification handed to a developer. The difference is that the AI will not necessarily flag the ambiguity or tell you something fell through the cracks.

Vibe coding is genuinely useful for mocking up a dashboard, visualizing a prototype, or testing an idea before you invest real money. Once customers depend on what you have built, the standard changes. You need someone who can confirm the end product is what you specified, not just something that looks right in a demo.

An SEO audit is not a specification

You run a crawl. It flags broken canonicals, missing hreflang, orphaned pages. You copy the output into a ticket and hand it to the dev team. In your head, you have told them exactly what is wrong and what to do.

Have you?

The tool told you what it detected. It did not tell your developer why it matters, what "fixed" actually looks like on this specific site, or how you will verify the fix once it ships. A scanner's flag is no more a specification than a wish list is.

Not every flagged issue even deserves a ticket, which makes it more important that the ones you do send are exact. If the ticket does not say what to check, on what page, with what expected result, you get the predictable outcome: something gets marked "resolved," and six months later the issue — or a cousin of it — is still there.

Do not forward the tool's output. Translate it into your own specification, with your own verification step attached, before it reaches a developer.

Vibe and verify: a working checklist

Before calling anything done, fill in four fields. Not yes/no. If you cannot fill in a specific answer, that is the finding.

For the person specifying the build

• Problem — what is actually broken or missing, in the system's own terms. Not "this should work better."
• Solution — the specific change that closes the gap, and what the finished state looks like in concrete, checkable terms.
• Verification — the test you will personally run against the live system. Not the status update you will accept.
• Money tie — what this component's absence or failure costs in dollars, hours or client trust if it is never verified.

For a technical SEO finding

• Problem — the actual mechanism, not the tool's generic label. Not "page speed issue," but which metric (TTFB, DOM content loaded, LCP, a render-blocking script) on which URL, template or scope.
• Solution — the specific change at the right level (server config, template, page, CDN rule), precise enough that two developers would build the same fix.
• Verification — the tool, metric, threshold and recheck date, so "fixed" has a number attached rather than a feeling.
• Money tie — the traffic, conversion or crawl-budget cost the issue is actually causing, priced out — not assumed because the tool flagged it red.

For client or executive reporting

• Problem — the specific outcome you were hired to move, not the activity you performed.
• Solution — the specific action that produced the result, traceable to a date and a change, not a general trend.
• Verification — the source in the client's own analytics or accounting, not your dashboard, that confirms it happened.
• Money tie — what it is worth in the client's own numbers: their conversion rate and margin, not an industry benchmark.

For an AI-prompted (vibe-coded) tool

• Problem — the specific capability needed, precise enough that "looks like it works" and "works" would produce different answers.
• Solution — what was actually built, and whether it matches that capability or something adjacent to it.
• Verification — the test run against real conditions, real data and real load — not the demo path — reviewed by someone who can catch a failure.
• Money tie — what it costs if this fails in production: refunds, downtime, security exposure, lost trust, and whether that is acceptable for something nobody verified.

In client reporting, verification ends at ROI

When reporting to a client, verification ultimately has to answer the question that matters most: show me the ROI.

The industry is split on whether ROI is even the right frame for SEO. But the discomfort usually comes from not having verified the connection between the work and the outcome in the first place, not from ROI being the wrong question. To the average executive, unverified SEO looks exactly like vibe coding that did not produce the promised result — indistinguishable from work that was never checked.

Closing that gap means tying every claim to a number that connects to money:

• Instead of "we improved your ranking for 40 keywords" → show the traffic delta on those pages, then convert those visits to dollars using the client's own conversion rate and order value.
• Instead of "your technical issues are resolved" → show the re-run crawl paired with the revenue that was actually at risk.
• Instead of "your AI visibility improved" → show the captured citation and connect it to the bookings or form fills that came through the tracked link, priced the way a paid channel would be.
• Instead of a report full of activity → tie every line to the dollar or lead it produced, and say plainly when a line produced nothing.

An honest zero, priced out, builds more trust than ten vague wins. Verification is not complete until it is converted into the same currency the executive is asking about: dollars in versus dollars out.

Make 'done' something you can prove

Write specifications that describe evidence, not just outcomes. For every component, define the exact test that would prove it exists and works before calling it done.

Run that verification yourself, on a cadence, not just once at launch.

When a gap appears, treat it as data about where the specification left room for drift, not as a failure of the person who implemented it.

The shift is from "did you build what I asked for?" to "show me the proof, in a form I defined in advance."

This does not require replacing developers with AI or finding some mythical better class of developer. It requires writing specifications that cannot quietly go unbuilt without someone knowing. Whether you hand work to a developer, an agency or an AI tool, the fix is not finding better people — it is tightening what you hand them in the first place.

The practical read for marketers

The same logic governs performance reporting. Unverified claims eventually become promises nobody can keep, and the structural reason is laid out in Why 'Guaranteed AI Visibility' Doesn't Exist in AEO and GEO.

And once you start verifying, what usually surfaces is not a missing tactic but deferred homework. Most AI Visibility Gains Are Just Technical Debt Repayment reaches the same conclusion from a different direction.