Tag
#principal-and-staff-engineer-mastery
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# Agentic Ai Projects And Mastery
All Agentic Ai Projects And Mastery notes →1. Technical Strategy for AI
Covers writing a multi-year technical strategy for AI adoption inside an engineering org, including how to sequence platform investment against product-team AI feature demand.
2. Build vs Buy Decisions
Covers the decision framework for build-vs-buy on AI platform components (vector DB, agent framework, evaluation tooling), with a worked cost/lock-in/velocity comparison a Staff engineer would present to leadership.
3. AI Platform Roadmaps
Covers translating an AI technical strategy into a quarter-by-quarter platform roadmap with explicit dependency sequencing and the trade-off calls a roadmap forces onto paper.
4. Architecture Reviews
Covers running or presenting in an architecture review for an AI system - the review rubric, common objections a review board raises to agentic designs, and how to defend a proposal under scrutiny.
5. Engineering RFCs & ADRs
Covers writing RFCs and ADRs specifically for agentic-system decisions, where the reversibility and blast radius of a decision (e.g., granting an agent write access) changes how much rigor the document needs.
6. Organizational Design for AI Teams
Covers the organizational design trade-offs between a centralized AI platform team, embedded AI engineers per product team, and a hybrid model, and how ownership boundaries shift as the platform matures.
7. AI Governance at Scale
Covers scaling AI governance across an enterprise - model approval workflows, audit logging requirements, and policy-as-code enforcement for what agents are allowed to do in which environments.
8. AI Economics & ROI
Covers building the cost model and ROI narrative for an AI platform investment in the form a CFO or VP Engineering would actually accept — which benefits are measurable, which are hand-wavy, and how build-vs-buy economics change the answer.
9. Interview Case Studies (L6/L7)
Walks through full mock L6/L7 system-design interview transcripts on agentic-AI topics, with the interviewer's follow-up probes and what separates a passing answer from a borderline one.
10. The Future of Agentic AI
Closes the book with a forward-looking synthesis of where agentic AI architecture is heading (standardized protocols, autonomous operations, agent-to-agent economies) and which of today's patterns are likely to age well.