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Stage 4 · Advanced

Agents in Production

Context, memory, cost guardrails and the workspace an autonomous coding agent needs.

You'll be able to: Run agents that stay sharp over long tasks, stay on budget and hand back reviewable work.

0 of 5 done
  1. 1 Cinematic deep dive 7 min Failure mode + fix Context Engineering for AI Agents An agent is only as smart as its context window: treat the window as a budget, and write, select, compress and isolate what goes into it at every step.
  2. 2 Cinematic deep dive 6 min Failure mode + fix Building Memory for AI Agents Useful agent memory is a small, scoped, revisable set of evidence: capture what matters, retrieve it when relevant, and retire it when the world changes.
  3. 3 Cinematic Short 52 sec Failure mode + fix The Runaway Agent An agent loop with no step cap and no budget can retry a failing tool all night, and because every call resends a growing context, the bill grows faster than the number of steps.
  4. 4 Deep dive 4 min Failure mode + fix Autonomous Coding Agents An autonomous coding agent is a controlled loop: it reads a bounded task, observes a real repository, makes small changes, proves them with tests, and hands a reviewable pull request back to a human.
  5. 5 Cinematic deep dive 5 min Failure mode + fix Why AI Agents Act Twice Recover recorded progress, reuse the business action identity, and enforce deduplication where the effect happens.
  6. Coming soonPrompt Injection in AI AgentsAnnounced at the end of an episode in this track. Subscribe to catch it.
  7. Coming soonWhen RAG Leaks Private DocumentsAnnounced at the end of an episode in this track. Subscribe to catch it.
  8. Coming soonLLM GatewaysAnnounced at the end of an episode in this track. Subscribe to catch it.
  9. Coming soonPrompt Injection Through ToolsAnnounced at the end of an episode in this track. Subscribe to catch it.
  10. Coming soonAgent memory: what should survive?Announced at the end of an episode in this track. Subscribe to catch it.
Next stage AI Security