incremental-coding

SkillAI & models

Build in verifiable increments. Never implement more than can be tested right now. Ship partial working systems over complete broken ones.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the incremental-coding skill

What this skill tells your AI

The instructions your AI receives, as published by developersglobal/ai-agent-skills in skills/incremental-coding/SKILL.md and read by ahel’s review.

Overview

The biggest risk in software development is building a lot of code that doesn't work. Incremental coding limits this risk: build a little, verify it works, build more. At every step, the system is in a known-good state.

When to Use

  • Any implementation that will take more than 2 hours
  • When building in a complex domain you're uncertain about
  • When multiple components need to integrate

Process

Step 1: Define the First Increment

  1. What is the smallest possible thing you can build that provides value and can be verified?
  2. It doesn't have to be feature-complete — just correct and verifiable.
  3. Example: "Add the endpoint skeleton with hardcoded response" before adding business logic.

Verify: The first increment can be verified in under 5 minutes.

Step 2: Build → Verify → Commit

  1. Build only the first increment.
  2. Run tests. Verify manually if needed. Confirm it works.
  3. Commit this working state.
  4. Repeat for the next increment.

Verify: There is a working commit after each increment.

Step 3: Integration Continuously

  1. Integrate with the real system as early as possible — not at the end.
  2. Test against real dependencies (DB, API, etc.) as early as possible.
  3. Fake integrations (mocks) should be replaced with real ones by the end.

Verify: By completion, all mocks replaced with real integration.

Common Rationalizations (and Rebuttals)

ExcuseRebuttal
"I need to build it all to know if it works"No. Build the first piece and test it. Uncertainty is always reducible.
"Integration is at the end"Integration pain is proportional to time since last integration. Integrate continuously.

Verification

  • Implementation built in verifiable increments
  • Working commit exists after each increment
  • No long stretches of "broken" state in git history
  • All mocks replaced with real integrations by completion

References

Signals

GitHub stars
66
Forks
9
Last commit
May 2026
Advanced
Catalog kind
skill
Gateway key
incremental-coding
Source
github.com/developersglobal/ai-agent-skills