Vom Prompt zum Loop: Die Evolution der KI-Steuerung · Part 6 of 8
Anatomie eines perfekten Loops
Abbruchbedingungen, Kontextmanagement und Memory in autonomen Schleifen
Stop conditions, context rotation, memory and a human emergency stop: what keeps an autonomous loop safe.
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About this audiobook
An agent loop with no exit is an expensive way to produce nothing. Part 6 dissects what a robust loop needs: clear stop conditions, protection against reward hacking, and context management through rotation and pruning so the model keeps working on the right thing.
It contrasts stateful and stateless agents, explains memory and fallbacks, and shows where monitoring and a human emergency stop are non-negotiable.
Published in German, 36 minutes. For developers running agents on real tasks.
Chapters
- Die Gefahr der Endlosschleife
- Abbruchbedingungen und Kontextpflege
- Zustand, Fallbacks und menschlicher Notaus
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See the courseVom Prompt zum Loop: Die Evolution der KI-Steuerung
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1. Das Handwerk der WorteRoles, few-shot examples, chain of thought and system instructions: prompting as a craft, not a guessing game.
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2. Kontext ist KönigHow to give a language model the right knowledge: context windows, memory and retrieval-augmented generation.
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3. Die Entstehung der AgentenFrom answering machine to actor: tool use, function calling, ReAct and the Model Context Protocol.
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4. Das Harness und die UmgebungThe environment decides whether an agent is production-ready: guardrails, sandboxes and automatic evaluators.
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5. Die Geburt von Loop EngineeringPlan, execute, observe, refine: why autonomous work cycles beat single prompts on every long task.
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7. Verifizierung und Self-CorrectionA model must not grade its own work: generator-evaluator loops, hard tests and fallbacks for AI you can trust.
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8. Das autonome ÖkosystemTeams of specialised agents, hierarchy versus swarm, and the human as architect, auditor and conductor.