Name: Agentic Engineering
Author: affaan-m

Use this skill for engineering workflows where AI agents perform most implementation work and humans enforce quality and risk controls.

Operating Principles

Define completion criteria before execution.
Decompose work into agent-sized units.
Route model tiers by task complexity.
Measure with evals and regression checks.

Eval-First Loop

Define capability eval and regression eval.
Run baseline and capture failure signatures.
Execute implementation.
Re-run evals and compare deltas.

Example workflow:

1. Write test that captures desired behavior (eval)
2. Run test → capture baseline failures
3. Implement feature
4. Re-run test → verify improvements
5. Check for regressions in other tests

Task Decomposition

Use this skill for engineering workflows where AI agents perform most implementation work and humans enforce quality and risk controls.

Operating Principles

Define completion criteria before execution.
Decompose work into agent-sized units.
Route model tiers by task complexity.
Measure with evals and regression checks.

Eval-First Loop

Define capability eval and regression eval.
Run baseline and capture failure signatures.
Execute implementation.
Re-run evals and compare deltas.

Example workflow:

1. Write test that captures desired behavior (eval)
2. Run test → capture baseline failures
3. Implement feature
4. Re-run test → verify improvements
5. Check for regressions in other tests

Agentic Engineering

Operating Principles

Eval-First Loop

Task Decomposition

Agentic Engineering

Operating Principles

Eval-First Loop

Task Decomposition

Model Routing

Session Strategy

Review Focus for AI-Generated Code

Cost Discipline

When to Use This Skill

Integration with Other Skills

Sessions

Docker Patterns

Autonomous Loops

Kotlin Patterns

Eval Harness

Golang Patterns