AI-First Engineering
SkillAI & modelsYour AI can work according to an engineering operating model built for teams where AI agents generate a large share of the implementation. The ai-first-engineering skill comes from the aurixagent repository on GitHub. It is aimed at teams organizing their work around agents doing much of the building.
Available today. Use it from your connected AI after setup.
No other account needed.
After adding the skill, ask your AI to work using the ai-first-engineering model. Then hand it your engineering tasks and let it apply that model to them.
Then ask your AI: use the AI-First Engineering skill
What your AI can do with it
- Apply an engineering operating model designed for teams where agents produce much of the implementation
- Structure engineering work so AI agents handle a large share of the building
- Carry out your engineering tasks in line with this way of working
- Explain how the model organizes work when agents generate most of the output
What this skill tells your AI
The instructions your AI receives, as published by dekaprayoga/aurixagent in skills/ai-first-engineering/SKILL.md and read by ahel’s review.
Use this skill when designing process, reviews, and architecture for teams shipping with AI-assisted code generation.
Process Shifts
- Planning quality matters more than typing speed.
- Eval coverage matters more than anecdotal confidence.
- Review focus shifts from syntax to system behavior.
Architecture Requirements
Prefer architectures that are agent-friendly:
- explicit boundaries
- stable contracts
- typed interfaces
- deterministic tests
Avoid implicit behavior spread across hidden conventions.
Code Review in AI-First Teams
Review for:
- behavior regressions
- security assumptions
- data integrity
- failure handling
- rollout safety
Minimize time spent on style issues already covered by automation.
Hiring and Evaluation Signals
Strong AI-first engineers:
- decompose ambiguous work cleanly
- define measurable acceptance criteria
- produce high-signal prompts and evals
- enforce risk controls under delivery pressure
Testing Standard
Raise testing bar for generated code:
- required regression coverage for touched domains
- explicit edge-case assertions
- integration checks for interface boundaries
Signals
- GitHub stars
- 63
- Forks
- 11
- Last commit
- Aug 2026
ahel recommends instead
Advanced
- Catalog kind
- skill
- Gateway key
ai-first-engineering-dekaprayoga- Source
- github.com/dekaprayoga/aurixagent