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AI agents use LLMs to plan and act. They do more than answer questions. They take action in your software. You need a design for the loop, tools, and safety.
The agent loop is the core. The LLM gets a goal and a list of tools. It picks a step. It calls a tool. It sees the result. It repeats this until the job is done.
Tool definition matters. Use these rules:
- Simple names
- Simple descriptions
- Strict parameter schemas
Use examples in your prompt:
- Show successful tasks
- Show error recovery
- Show patterns for failure
Safety is a must for production:
- Use minimal access
- Require human approval for big changes
- Set step limits
- Log every action
Use structured reasoning. Chain-of-thought helps agents think step by step. Reflection loops let agents check their work.
Test your agents before you launch. Try edge cases. Test bad inputs. Track completion rates and error rates.
Source: https://dev.to/therizwansaleem/ai-agents-architecture-patterns-tools-and-orchestration-236k Optional learning community: https://t.me/GyaanSetuAi