HyperTeamsAgents — the loop that runs itself
What you will learn How agents differ from tool use, why autonomy cuts both ways, and how to decide how much to hand over.
Using once versus repeating
Tool use in the previous chapter had this flow:
A person asks once and gets one answer. An agent is different.
It takes a goal and repeats on its own until it is done.
graph TD
A["Receive a goal"] --> B["Decide what to do now"]
B --> C["Run a tool"]
C --> D["Check the result"]
D -->|"goal not met"| B
D -->|"done"| E["Report the final result"]Within a single request this loop can turn dozens of times.
What it actually looks like
Take the request "summarise how last month's revenue did against target."
Nobody directed each step. Turn 3's "I should look at why" was its own judgement. That is what "autonomous" means.
Autonomy cuts both ways
| Upside | Downside |
|---|---|
| A person need not attend every step | it goes just as hard in the wrong direction |
| It finds paths you did not expect | it also causes incidents you did not expect |
| You can hand over long-running work | long-running also means more cost |
The most important property
An agent goes just as hard in the wrong direction.
Give it the wrong goal and it will take dozens of steps towards that wrong goal. Tool use wrong once is wrong once; an agent keeps building on a false premise.
So the human's job moves earlier.
| What the human does | |
|---|---|
| Tool use | asks each turn and looks at the answer |
| Agent | states the goal precisely and sets the stopping points |
Deciding how much to hand over
In practice you set autonomy in levels. HyperTeams uses a representative split.
| Level | Behaviour | When |
|---|---|---|
| Plan only | shows how it would do it, does not execute | first handover, risky work |
| Partly automatic | proceeds with reversible things, confirms the rest | a sensible working default |
| Fully automatic | runs to the end without stopping | verified, repeated work |
Run it a few times on "plan only" first. Seeing what it intends and then widening beats opening it wide and cleaning up afterwards.
Setting the stopping points
An autonomous loop may not stop on its own. So you bound it from outside.
The last matters most. Put a human in front of anything irreversible — as we saw in tool use, the system does the executing, so approval can be inserted in between.
In HyperTeams
- HyperTeams (your machine) runs Claude Code as the agent. The working directory is the agent's area of operation, and you choose an autonomy level when handing over a task.
- Connect (your team) keeps several agents in a workspace and gives each of them different tools.
Common misconceptions
"Is an agent always better than tool use?"
No. It is overkill for simple work. Using an agent where one lookup would do only adds cost and time. Use it for work with several steps and judgement in the middle.
"Nice — I don't have to watch it."
The front end gets harder. Instead of watching and correcting each turn, you have to state the goal precisely at the start. Give it vaguely and it goes dozens of steps in a vague direction. The next chapters are about stating it precisely.
Check yourself
1. What is the core difference between tool use and an agent?
Answer
Repetition. Tool use calls once and stops; an agent takes a goal and repeats, judging for itself, until it is complete. So a person does not direct each step.
2. What does "an agent goes just as hard in the wrong direction" mean in practice?
Answer
Give it the wrong goal and it stacks dozens of steps on a false premise. Tool use wrong once is wrong once; an agent accumulates. So the human's job moves forward, from "check each turn" to "state the goal precisely and set the stopping points."
3. What four limits should be imposed on an autonomous loop from outside?
Answer
Maximum turns, maximum cost, maximum time, and actions requiring human approval. The last matters most — put a human in front of anything irreversible.
What "stating the goal precisely" means, starting with the vessel it goes in → The context window