Context Engineering, часть 4- Контекстное окно, evals и безопасность AI-агента

In the fourth part of Context Engineering, I examine three elements without which an agent-based framework quickly becomes unmanageable: what the agent sees at the current step, how to accept its work, and where it cannot act independently. I demonstrate, using my agents, how to assemble a context window, separate roles, verify the actual result, set boundaries, and protect the framework from prompt injection. My resources: GitHub - completed projects and repositories: https://github.com/AlekseiUL SPRUT_AI - walkthroughs of AI agents and workflows: https://t.me/Sprut_AI SPRUT Chat - questions and discussions: https://t.me/+eH-qNIDmud8zNDZi AI OPERATING SYSTEM - here I collect key developments, completed projects, working files, guides, and detailed walkthroughs: https://t.me/tribute/app?startapp=sJyg Timecodes: 00:00 Context, result verification, and boundaries 01:05 How a coordinator assigns tasks to roles 02:03 What to put in an agent's context window 03:01 Why you shouldn't mix roles and sources 05:05 Compression and context isolation 07:15 How to accept agent results 09:00 Work trail: files, cards, and reports 10:00 Reference tasks and acceptance criteria 13:00 Security boundaries and rules 14:33 Prompt injection: data or command 15:06 Agent action levels 16:00 Control map and useful logs 18:35 From request to managed loop 19:17 Summary #ContextEngineering #AIAgents