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TechnologyNext-Gen AI14 m+200 XP
AI agent architecture: patterns that actually ship
Tool calling, memory layers, orchestration loops from first principles
An agent is just an LLM in a loop with access to tools. The loop: the model receives a task, decides whether to call a tool or respond directly, executes the tool if needed, observes the result, and repeats until the task is done. What makes it powerful: the model can plan, execute, adapt, and recover from errors — all without human intervention. What makes it fragile: context window limits, tool failures, and the model losing track of the original goal.
Key Points
- ▸Agent = LLM + tools + loop
- ▸The loop runs until the model decides it's done
- ▸Tool results go back into context
- ▸Failure modes: context overflow, tool errors, goal drift