The difference between a chatbot and an agent isn't intelligence – it's the loop

We build Octomind, so read this with that in mind.

We wrote a definition of "AI agent" we think survives the hype: an agent is a model that uses tools in a loop to pursue a goal. It plans, acts, observes, and repeats until the goal is met or it can't progress. The chatbot answers. The agent does.

The difference isn't intelligence — it's the loop. Ask a chatbot to fix a failing test and it describes the fix. An agent reads the file, runs the tests, sees the failure, edits the code, runs them again, sees green, and stops. Each turn is a fresh model call informed by what actually happened, not what it predicted. A chatbot's ceiling is the model's first guess. An agent's ceiling is that guess plus the ground truth of the world it acts on.

Four capabilities decide which one you're using:

1. Tools — functions it can call. Without them it's a chatbot whatever the packaging says. MCP went from proposal to industry default in about a year.
2. State — persistent sessions. An agent that re-reads the same file every turn isn't looping; it's hallucinating progress.
3. Grounding in results — real test output, real exit codes. An agent that "verifies" by generating plausible success text is a chatbot with extra steps. The best agent work comes from harnesses that feed hard results back and let the model be wrong out loud.
4. Termination judgment — done, blocked, or diminishing returns. A system that runs until your token budget dies isn't an agent; it's a space heater with a model attached. Spend caps belong in every setup, because judgment fails and budgets shouldn't.

Agents are good at bounded tasks with verifiable outcomes: make the tests pass, migrate this module, find why this endpoint is slow. They're weaker at vague goals like "improve the codebase", or at one catastrophic wrong action with nothing catching it. Both are harness problems, not model problems — sandboxes, permission rules, human checkpoints.

Be suspicious of any demo that hides the verification step. Before buying anything calling itself an agent, ask: real tools or a prompt template? does state persist across turns? are the observations real tool results or generated text? does it stop on its own judgment or only when the budget runs out?

Which of the four do you see missing most in the agents you've used?

https://octomind.run/blog/what-is-an-ai-agent