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AI Architect Program

CI

A public development program from engineering leader to Head of AI / CAIO (product/tech track), aimed at enterprise and regulated / government environments. Learning in the open (build in public): a knowledge base plus capstones with measurable quality and governance.

Principle: not the path of an execution engineer, but leader-grade depth — enough depth to make architectural decisions, hire and evaluate engineers, and answer to the board and the regulator.

Competency map (13 areas → AI Architect)

# Area Level Progress
01 LLM Architectures BUILD
02 Context Engineering BUILD
03 RAG Frameworks BUILD
04 Agentic Architectures BUILD
05 Service Management LEAD
06 Safety & Reliability BUILD ×2
07 Observability & Testing BUILD ×2
08 Scalable Production LEAD
09 Development Essentials LEAD
10 Optimized Deployment LEAD
11 Multimodal Mastery selective
12 Ecosystem Adaptation habit
13 Career / Build in Public in parallel

Progress: ⬜ not started · 🟧 in progress · ✅ closed (the area's checklist is complete).

The decisive layer on top of the map

Governance, Risk & Compliance — EU AI Act, NIST AI RMF, OWASP LLM Top 10, model risk, data residency. The main differentiator for a regulated / government role.

Capstones (portfolio) — assembled ✅

# Capstone Areas Launch Status
01 Enterprise RAG assistant 01–03, 06, 07, 09 make up && make seed && make test (requires key+Postgres) code + full code review in docs/CODE_REVIEW.md
02 Multi-agent workflow 04, 05, 06, 07, 08 make eval · make test (offline, no key) eval gate PASS: 90% block-rate, 100% tasks
03 Self-hosted / VPC deployment 10, governance make check · make decide (offline) residency-checker PASS/FAIL + TCO break-even

Quick start without a key or DB (capstones 02 and 03 run offline):

cd capstones/02-multiagent-guardrails && make eval   # attacks + tasks + latency gate
cd capstones/03-self-hosted-deployment && make check # data-residency verdict
make test-all                                         # tests for all capstones

CI (GitHub Actions) runs tests across all three capstones and the offline eval on every push.

Repository structure

knowledge-base/   13 areas: theory, examples, exercises
governance/       risk/compliance layer + a small in-house framework
capstones/        flagship projects with evals and a governance passport

How to use

  1. Go through the areas in tier order (BUILD 01–04, 06, 07 first).
  2. For each area, complete its readiness checklist in the README.
  3. Put exercise results in examples/, and the numbers in the README.
  4. Take the area's quiz (quiz/QUIZ.md, scored 0–100) — a score ≥ 80 closes the area (✅ in the table above). See self-assessment.
  5. Finish each capstone with a governance passport and a retrospective (area 13).

What is intentionally missing

Regional requirements (e.g. language) are omitted — the focus is on transferable competencies.

License: MIT. Sensitive/confidential data is not committed to the repository (see .gitignore).

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