Are Agents like Devin going to replace all developers?

No. Agents are currently very brittle. They can solve closed-scope problems (like fixing a specific bug in a specific file), but they lack the overarching architectural context to design and build massive, multi-repository enterprise systems from scratch.

How do Agents avoid Context Windows limits?

A standard codebase has 10 million tokens. An LLM context window is only 128k. Agents use RAG (Retrieval-Augmented Generation) and tools like `grep` to search the codebase and only read the specific files they need, rather than loading the whole project into memory.

Can I build my own Agent?

Yes. Frameworks like LangChain, AutoGen, and CrewAI make it very easy to build a `while` loop, define custom JSON tools, and connect an OpenAI API key to create your own autonomous script.

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Autonomous AI Agents

Learn the architecture behind Autonomous AI Software Engineers. Understand the ReAct loop, LLM Tool Use (Function Calling), and the critical safety protocols of sandboxing and Human-in-the-Loop.

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