How Do You Know
It's Done?
Your AI finishes every task with confidence. But “done” according to what? Without structured specs, you're taking the AI's word for it. With auto-verified specs, the system checks.
The verification problem
You prompt Claude Code: “Build me a blog page targeting ‘ai coding tools’.” Two minutes later it says done. The page renders. The code is clean. You move on.
But did it put “ai coding tools” in the H1? Is the keyword in the meta title? What's the density? Is the meta description under 160 characters? Did it add schema markup? You don't check because you didn't define what “done” means for these things.
AI doesn't say “I'm not sure about this.” It says “Done! I've optimized the page for SEO.” The output looks professional. The keywords sound plausible. Six months later, your analytics show why plausible isn't the same as correct.
You can't verify what you didn't specify. And if you did specify it, who checks?
How developers manage AI work today
Most people fall into one of these approaches. Each one handles the verification problem differently.
No spec (just prompting)
The most common approach. Prompt, look at the result, reprompt if something looks off. No record of what was intended. No way to verify anything beyond “does it look right?” No way to pick the work up next Tuesday.
Works for throwaway experiments. Fails for anything that needs to ship, rank, or be maintained.
Markdown specs (CLAUDE.md, TASKS.md, TODO lists)
Better. You write down what you want. The AI can read the file. But verification is entirely on you. Did the AI actually put the keyword in the H1? You have to go look. Did density hit threshold? You have to count. Most people skip the checking.
Specs also go stale. You update the code but forget to update the spec. Next session, the AI reads outdated instructions and builds the wrong thing confidently.
Good for simple, single-session work. No feedback loop. The spec doesn't know if it was followed.
Claude Code's internal planning
Claude Code auto-generates a plan and tasks when you give it complex work. This is helpful in the moment. It breaks the work into steps and executes methodically.
But the plan is ephemeral. It lives inside the conversation and disappears when the session ends. You can't review it tomorrow, share it with anyone, or come back to it next week. There are no acceptance criteria. Claude decides when a task is “done” based on its own judgment.
Good for tactical, single-session work. Not persistent, not verifiable, not shareable.
TDD (Test-Driven Development)
The gold standard for code correctness. Write tests first, code must pass them. Tests persist in the repo. CI fails the build when something breaks. This is automated verification done right.
But TDD verifies code behavior, not content quality. You can test that a page renders. You can't test that it targets the right keywords, has the right meta description length, or matches the search intent for your market. “Does the component render?” and “Will anyone find this page?” are different questions.
Essential for code. Blind to content, SEO, and market fit.
Rampify specs (structured, auto-verified)
Persistent specs with structured tasks and acceptance criteria. The spec survives across sessions. Come back next week, next month. Any AI session can read the spec via MCP and pick up where the last one left off.
After the AI builds, Rampify runs a deterministic audit. Keyword in title? Pass or fail. In the H1? Pass or fail. Density above 0.8%? Pass or fail. Not opinions. Concrete checks with specific fix instructions when something fails.
When quality drops later (someone edits the page, a keyword gets removed, density falls below threshold), the spec reopens automatically. You don't have to remember to check. The system catches it.
The only approach where verification is automated, not optional.
What each approach can verify
Code correctness and content quality require different verification. Most approaches only cover one.
| What gets checked | No spec | Markdown | Claude plans | TDD | Rampify |
|---|---|---|---|---|---|
| Code compiles, tests pass | |||||
| Keyword in page title | manual | ||||
| Keyword in H1 | manual | ||||
| Keyword density above threshold | |||||
| Meta description correct length | manual | ||||
| Schema markup present | manual | ||||
| Persistent across sessions | |||||
| AI can read the spec | |||||
| Performance tracked over time | |||||
| Reopens when quality drops |
“Manual” means you can write it in the spec, but nobody checks automatically. You have to verify it yourself.
Specifications without verification are just wishes
A TASKS.md file that nobody checks is a document that makes you feel organized. A Claude Code plan that disappears after the session is a thought you had once. Neither one closes the loop.
TDD proved something important: automated verification changes how people write code. When tests run on every commit, developers write different (better) code because they know it will be checked. The feedback loop is the point.
Rampify applies the same principle to everything TDD can't cover. Content quality. Keyword targeting. SEO compliance. Meta tag correctness. Schema markup. The things that determine whether anyone actually finds what you built.
They work together
- TDD for code correctness. Does it compile? Do tests pass?
- Markdown files for quick notes and context your AI should know.
- Claude Code plans for tactical, within-session work.
- Rampify specs for everything that needs persistent, auto-verified acceptance criteria connected to real data.
The feedback loop is the product. Build, verify, fix, verify again. That's spec-driven development.
Getting started
One MCP connection gives your AI access to spec creation, keyword research, content audits, and auto-verification. The same tools that check the AI's work also give it the data to do better work in the first place.
claude mcp add --transport http rampify \ https://www.rampify.dev/api/mcp \ --header "Authorization: Bearer YOUR_API_KEY"
Stop hoping. Start verifying.
Your AI does the work. Rampify checks the work. One MCP connection turns “done” from a guess into a fact.