Thread by @_avichawla

5 levels of Agentic AI systems, clearly explained (with visuals):

Agentic AI systems don't just generate text; they can make decisions, call functions, and even run autonomous workflows.

The visual explains 5 levels of AI agency, starting from simple responders to fully autonomous agents.

Let's dive in to learn more!

1️⃣ Basic responder

- A human guides the entire flow.
- The LLM is just a generic responder that receives an input and produces an output. It has little control over the program flow.

See this visual👇

2️⃣ Router pattern

- A human defines the paths/functions that exist in the flow.
- The LLM makes basic decisions on which function or path it can take.

Check this visual👇

3️⃣ Tool calling

- A human defines a set of tools the LLM can access to complete a task.
- LLM decides when to use them and also the arguments for execution.

Check this visual👇

4️⃣ Multi-agent pattern

A manager agent coordinates multiple sub-agents and decides the next steps iteratively.

- A human lays out the hierarchy between agents, their roles, tools, etc.
- The LLM controls execution flow, deciding what to do next.

See this visual👇

5️⃣ Autonomous pattern

The most advanced pattern, wherein, the LLM generates and executes new code independently, effectively acting as an independent AI developer.

Here's a visual to understand this👇

To recall:

1) Basic responder only generate text.
2) Router pattern decides when to take a path.
3) Tool calling picks & runs tools.
4) Multi-Agent pattern manages several agents.
5) Autonomous pattern works fully independently.

Here's the visual again for your reference👇

That's a wrap!

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