Ai First Engineering
This captures the operating model shift when AI agents are writing most of your implementation code. It's honest about what changes: planning and evals matter more than typing speed, code review focuses on behavior over syntax, and you need architectures with explicit boundaries instead of implicit conventions. The hiring signals section is smart, emphasizing decomposition and acceptance criteria over raw coding ability. Use this when you're setting up processes for a team that's actually shipping with Claude or similar tools doing heavy lifting on implementation, not just autocomplete. The testing standards are appropriately higher since generated code needs more explicit coverage.
- skills.sh installs
- 5.5K
- GitHub stars
- 300.3K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add affaan-m/ecc --skill ai-first-engineering --agent claude-codeInstalls into .claude/skills of the current project.
Files
AI-First Engineering
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
Sponsors
Agent CaffeineSponsoredClose your lid, come back to finished work
SnugSponsoredThe clipboard manager for the AI eraPromote your product hereReach 125k+ visitors monthly
WaxSponsoredBlock anything with supervision, without erasing your iPhonePromote your product hereReach 125k+ visitors monthly
knobsSponsoredSee your site on any phone, any day, in any languageDetails
- Repository
- github.com/affaan-m/ecc
- Category
- AI & Agent Building
- First seen
- Jul 14, 2026
More from affaan-m/ecc
All 263- Prisma Patterns5.5K
- Continuous Agent Loop5.5K
- Continuous Learning5.5K
- Agent Eval5.5K
- Exa Search5.5K
- Agent Sort5.5K
- Product Lens5.5K
- Iterative Retrieval5.5K
- Skill Stocktake5.5K
- Benchmark5.5K
- Healthcare Emr Patterns5.5K
- Homelab Network Setup5.5K
- Ios Icon Gen5.5K
- Kotlin Ktor Patterns5.5K
- Api Connector Builder5.5K
- Safety Guard5.5K
- Csharp Testing5.5K
- Skill Scout5.5K
- Customs Trade Compliance5.5K
- Research Ops5.5K
- Crosspost5.5K
- Videodb5.5K
- Click Path Audit5.5K
- Skill Comply5.5K
Recommended
More AI & Agent Building
continuous-agent-loopaffaan-m/eccPatterns for continuous autonomous agent loops with quality gates, evals, and recovery controls.5.5Kskills.sh installsagent-sortaffaan-m/eccBuild an evidence-backed ECC install plan for a specific repo by sorting skills, commands, rules, hooks, and extras into DAILY vs LIBRARY buckets using parallel5.5Kskills.sh installsregex-vs-llm-structured-textaffaan-m/eccDecision framework for choosing between regex and LLM when parsing structured text — start with regex, add LLM only for low-confidence edge cases.5.5Kskills.sh installsenterprise-agent-opsaffaan-m/eccOperate long-lived agent workloads with observability, security boundaries, and lifecycle management.5.4Kskills.sh installs