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Demos look great. Production systems look different.
People call everything an agent today. A chatbot with memory is an agent. A script with a loop is an agent. This creates engineering mistakes. You end up over-engineering simple tasks and under-engineering hard ones.
An agent must have an objective. It must decide what to do next. It must handle failure. It must know when it is finished.
Check your system:
- If a human tells it every step, it is a chat interface.
- If it recovers from a failed tool call, it is an agent.
- If it breaks a goal into subtasks, it is a real agent.
Real deployments are narrow. They do one thing well like document extraction or code review. They are not general reasoning engines.
The best teams focus on three things:
- Tool design: How clean is the interface?
- Failure handling: What happens when a tool returns nothing?
- Observability: Can you trace why an agent made a decision?
Stop swapping models and expecting better results. If you change the model but keep the same bad logic, nothing improves.
Frameworks like LangChain or CrewAI matter less than patterns. Use these patterns instead:
- Plan then execute: Separate the reasoning step from the execution step.
- Separate retrieval from reasoning: Fetching context and using context are different jobs.
- Explicit handoffs: Use structured logs when one agent passes work to another.
RAG is standard, but chunking is often broken. If your RAG returns useless results, your problem is the chunking or metadata. It is not the embedding model. Try overlapping windows or semantic chunking.
The real challenge is not chasing benchmarks. It is building systems you can trust. Focus on governance, observability, and reliable tool use.
The engineers who matter will be those who build systems other people can maintain. This is systems design, not model research.
What are you building? Share your experience in the comments.
Source: https://dev.to/aibughunter/what-happens-when-you-run-10-ai-agents-at-once-in-a-real-codebase-26ii
Optional learning community: https://t.me/GyaanSetuAi