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Most AI demos on LinkedIn lie. There is a gap between a demo and a production system.
People call everything an agent. A chatbot with memory is not an agent. A simple script is not an agent. This causes engineering mistakes. You over-engineer simple tasks. You under-engineer hard ones.
An agent has an objective. It decides the next step. It handles failure. It knows when to stop.
- Human tells every step? It is a chat interface.
- Recovers from failed tool calls? You are close.
- Breaks a goal into subtasks? This is a real agent.
Real agents are narrow. They do one thing well. Think customer triage or code review.
Successful teams focus on these things:
- Tool design
- Failure handling
- Observability
The framework is scaffolding. The architecture is the building.
Use these patterns:
- Plan then execute.
- Separate retrieval from reasoning.
- Use explicit handoffs.
RAG is standard. Chunking is often wrong. This causes hallucinations. Fix your metadata. Fix your chunking. Do not blame the model.
Models get better. Costs drop. The hard part is trust. Build systems other engineers trust. This is systems design.
Tell me your experience in the comments. Interesting conversations happen in threads.
Source: https://dev.to/aibughunter/the-dirty-secret-behind-most-ai-agent-demos-you-see-on-linkedin-5ekf
Optional learning community: https://t.me/GyaanSetuAi