AI Agents Are Just Finite State Machines 🤖

LangGraph forces you to view the architecture of LLM applications as a directed graph (State Machine).

The whole essence boils down to three things:
1️⃣ State — shared memory. A regular TypedDict that is passed around. It's just a dictionary.
2️⃣ Nodes — functions. One node calls the LLM, another makes a database query, a third writes a log.
3️⃣ Edges — transition logic. If the code has a bug — go to the refactoring node. If OK — go to the release node.

The most important thing: the LLM no longer controls the system. The LLM simply returns JSON or a string, and where to go next is decided by your hardcoded Python code in the graph router.

You suddenly get what was so lacking in AI development: predictability, debuggability, and proper logging of each step.

🗓May 15 at 18:00 Moscow time at Tochka Sborki we will build such a basic system.

The broadcast and recording will be available to participants. Access is arranged through the bot: https://t.me/TScompiler_bot