From Idea to Green CI

Every great side-project starts with a spark of inspiration… and then stalls at an empty ~/code directory.
We copy boilerplates, nudge ChatGPT, splice together prompts—but still waste evenings stitching plans, repo structure, and tests into something coherent.

This post distills five principles we refined while building Buildable, the MCP-powered task engine. Follow them and you can move from concept to a passing CI build in a fraction of the usual time.

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Principle 1 — Start with a Detailed Plan, Not a Prompt

Before you open VS Code, generate a phased backlog:

• Break the idea into releases and high-value milestones
• Map dependencies so you never block on “waiting for X”
• Assign rough time estimates to spot scope creep early

Why it matters: Prompting an LLM without a roadmap leads to “prompt ping-pong.” A living plan lets you regenerate just the affected phase when scope changes, instead of rewriting a wall of text.

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Principle 2 — Lock In Architecture & Repo on Day One

A blank repo is momentum’s biggest enemy. Spin up the folder structure, CI workflow, lint rules, and a README immediately—even if you’ll iterate later.

Benefits

• CI turns green on the first commit, guarding quality from the start
• File paths in tasks point to real locations—crucial for AI assistants
• New contributors (or future-you) ramp up faster

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Principle 3 — Keep Plan, Code, and Tests in One Loop

When your backlog lives in Notion, your code in GitHub, and your tests “somewhere in QA,” context vanishes.
The fix is simple: surface task status directly from CI and attach every decision to the card it affects.

Key practices

• Link each task to exact file paths and test names
• Use webhooks so CI success moves the card to Done automatically
• Store architecture notes in the repo next to the code they describe

Result: fewer “what broke?” Slack threads and more focused coding sessions.

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Principle 4 — Feed AI Assistants Structured Tasks, Not Wall-of-Text Prompts

Long, human-style prompts invite hallucinations and balloon token costs.
With the Model-Controller-Prompt (MCP) protocol, tasks are short JSON payloads an assistant can execute deterministically.

{
  "id": "T12",
  "title": "Create /api/products POST endpoint",
  "targetFiles": ["api/products.ts"],
  "commands": ["pnpm test", "pnpm biome"],
  "successChecks": ["tests pass", "Biome clean"]
}

One task → one branch → one green PR. No copy-paste required.

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Principle 5 — Iterate With Metrics, Not Gut Feel

A plan is alive. Use measurable feedback to evolve it:

Metric	What it tells you
Cycle time	Are tasks sized correctly?
Failed-build rate	Are tests & lint catching issues early?
Scope-creep delta	How much the backlog expands per phase

When a metric drifts, regenerate the affected phase or tighten acceptance criteria—without rewriting the entire plan.

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Quick Recap Checklist

• Generate a phased plan before you write code
• Scaffold the repo and CI on day one
• Keep plan, code and tests in one visible loop
• Serve structured MCP tasks to your AI assistant
• Track cycle-time and regenerate phases as data dictates

Pin this list next to your desk (or share it with your favorite chatbot) and you’ll never stare at a blank repo again.

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Ready to Turn an Idea Into a Passing CI Build?

We built Buildable so solo devs and small teams can spend their evenings shipping features, not rewriting prompts or shuffling tickets.

➡️ Start your seven-day free trial at bldbl.dev 🎥 Have feedback or a cool demo? Tweet us @BuildableDev, we’d love to see what you ship!