Party School · Lane 03 · Go deeper

Into the deep end.

You live in these tools and you want the engineering, not the analogy. This lane takes the same five subjects down to the mechanism: token budgets and orchestration, context engineering, stack design by unit cost, automations that fail loudly instead of quietly, and the real economics of shipping with a model in the loop. Same sources as the rest of the school, read a layer deeper. Bring opinions.

Updated August 1, 2026 Five lessons · refreshed monthly Sources: Anthropic · OpenAI · Google · MCP
Lesson 01 · Architecture

Agents, taken apart.

Past the six parts: how the loop actually spends tokens, when one agent should become several, MCP under the hood, and how to tell if it's getting better. The engineering, not the analogy.

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Lesson 02 · Context engineering

Context engineering.

Prompting is context management. What to load into the window, what to keep out, retrieval versus memory, and how to test a prompt like it's code.

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Lesson 03 · Stack design

Build your stack on purpose.

Stop collecting tools. A stack chosen by role and cost-per-outcome, switching cost and lock-in, and the moment a subscription should become an API call.

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Lesson 04 · Reliability

Automations that don't break quietly.

The failure mode isn't a crash, it's a wrong thing done confidently at 3am. Scoping, blast radius, idempotency, the human gate, and watching the thing you built.

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Lesson 05 · Unit economics

Ship, price, and prove it.

The numbers under a thing that pays: what it costs to deliver with AI in the loop, what to charge, margin math, and the two-week test that tells you if it's real.

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