8d • General discussion
AI agents are not just about calling tools.
The real power comes from the loop:
Thought → Action → Observation → Final Answer
That is the foundation of the ReAct architecture.
Instead of following one fixed plan, a ReAct-based agent observes what happens after every step and decides what to do next.
This is why it works well for messy, unpredictable tasks where the path is not clear upfront.
For AI builders, this is one of the most important patterns to understand before moving deeper into agentic AI.
ReAct is not perfect. But it is still the default “good enough” pattern for many real-world AI agents.
What do you think is the biggest challenge with building reliable AI agents today?
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AI agents are not just about calling tools.
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