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Engineering Teams

Conventions First

Rules, strong base technical knowledge, and architecture rules — the foundation everything else is built on. Without shared conventions, every engineer and every AI tool makes different decisions. Inconsistency compounds over time.

  • Naming, file structure, error handling patterns, testing scope — decide once, follow everywhere.
  • Conventions accelerate teams by removing decisions that should not be made per-task.

Knowledge Sharing Over Silos

IT evolves too fast for silos. Teams need to catch up together and form their own opinions.

  • Engineers need broader scope. Multi-area growth and multi-team experience matter more than deep single-area expertise.
  • A unified language (TypeScript everywhere) enables knowledge sharing and cross-project code review.
  • When frontend engineers can read backend code and vice versa, the team moves faster.

Problem-Solving Focus

Team members should spend most of their time on problem-solving, letting AI handle coding. If the team focuses on problem-solving, quality and speed follow naturally.

  • Engineers who enjoy understanding business problems and making tradeoffs will thrive.
  • Engineers who are only comfortable writing code will struggle.

Ship Fast with Quality

Not a contradiction when the team focuses on the right layer. Speed and quality multiply when architecture enables parallel work and conventions prevent mistakes.

  • Backend engineers must think about: mobile impact, frontend contracts, long-term evolution, business implications. Backend is not isolated. Backend is leverage.

Architecture Enables Org Scaling

Module ownership, clear boundaries, reduced change amplification. Architecture decisions are team decisions. Code structure should reflect team structure.

  • When architecture enables independent teams, fear of change drops.
  • When fear of change drops, shipping speed increases.

Metrics

  • Cycle Time: PR to release. Measures the entire pipeline, not just coding.
  • P50/P75 performance: real user experience, not synthetic benchmarks.
  • AI vs manual contribution ratio: how much work is AI-assisted.
  • Code review quality: depth of feedback, not speed of approval.

Evolution

  • Feb 2026 — rewritten in rule-oriented format from IDENTITY.md team philosophy.