Core Architecture & Primitives
The course is built around the modern engineering reality that system-level performance is heavily driven by orchestration. You will cover:
- Component Deconstruction: How to separate tangled agent logic into clean, file-addressable layers (including system prompts, tool implementations, middleware, reusable skills, and multi-agent routing configurations).
- Context Engineering & Compaction: Designing data delivery systems that feed the agent exactly what it needs to know without overwhelming its context window or blowing through token budgets.
- Tool Design & the Model Context Protocol (MCP): Crafting explicit action surfaces, secure runtime execution layers, and connecting agents to external environments like CI/CD pipelines, deployment logs, and sandboxed terminals.
- Closed-Loop Observability Systems: Transitioning from basic logging to multi-layered evaluation setups (Component, Experience, and Decision observability) to automatically track, trace, and even allow an outer-loop agent to programmatically test and evolve its own scaffolding.
Who This Masterclass Is For
- AI Engineers & Framework Builders: Developers building production-ready autonomous coding agents, support agents, or corporate automation tools who need to move past standard “vibes-based” prompting.
- MLES / DevOps for AI: Engineers responsible for setting up secure sandboxes (like E2B or dockerized runners), state persistence, and verification loops.
- Advanced Software Architects: Those interested in how systematic infrastructure design, deterministic linters, and structured guardrails can swing agent benchmark success by significant margins without altering the underlying LLM.
