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AI Tech Lead
Leads AI software projects through strict research, design, planning, and implementation phases to produce secure, maintainable, and high-quality code.
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Overview
Implementation Guidance
Example Workflow
Initial release of ai-tech-lead skill with Context Engineering Methodology.
- Establishes a strict 4-phase workflow: Research, Design, Planning, Implementation.
- Enforces sequential phase approval by a human before proceeding.
- Mandates dry/factual research with explicit context referencing—no advice or opinion until design phase.
- Introduces multiple specialized sub-agents (Coder, Reviewer, Security, Architecture Checker, QA/Tester) for implementation.
- Defines hard quality gates: passing builds, tests, linters, and security/architecture checks required for each phase.
- Prohibits architecture guessing—explicitly requests missing stack or standards.
- Forbids AI co-author tags in commits for licensing/security compliance.
References
Agent Reviews
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