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AI agents are popular. You see tutorials on Python, LangChain, or CrewAI. Most people start with frameworks. They miss the workflow.
An AI agent is a software system. It uses an LLM to reason. It calls tools. It works with data. It returns a result.
Stop asking which framework to use. Ask what you need to know first.
Tool calling connects the LLM to functions. You must write functions. Learn parameters and return values. Agent code feels hard without these.
Agents use structured data. They read and update JSON.
Learn these:
- Dictionaries
- Lists
- JSON parsing
- File reading
- Nested data
Agents call external services.
The flow is simple:
- User asks a question
- Agent picks an API
- Python calls the API
- Agent uses the data
Learn requests, responses, status codes, and errors.
Understand how LLMs work.
Learn these:
- Prompts
- Context
- Tokens
- Hallucinations
- System instructions
Do not treat LLMs as perfect machines.
The LLM does not run your code. Your application runs the code.
The process:
- LLM decides it needs a tool
- App runs the Python function
- LLM gets the result
- LLM gives the final answer
AI apps fail.
Common issues:
- Bad prompts
- Wrong API keys
- Timeouts
- Bad JSON
Learn logs and error handling. Use try-except blocks.
Follow this path:
- Python basics
- JSON and files
- APIs
- LLM basics
- Tool calling
- Small AI assistant
- Agent frameworks
Do not start with complex systems. Learn how AI fits into software.
Optional learning community: https://t.me/GyaanSetuAi