GuidesChoosing a modelProfessionals and small teams tempted to let a model run a whole task from start to finish
Handing a multi step job to an agentic model, safely
For Professionals and small teams tempted to let a model run a whole task from start to finish.
The newest flagships, Astra and Fable among them, are built to take on longer jobs that involve several steps rather than a single answer. That is powerful and worth using, but the more a model does on its own, the more it matters that you scope it, watch it and keep the reversible parts reversible.
When to use this
You have a job with several steps, gather these, compare them, draft that, update the tracker, and you are wondering whether to let the model run the whole thing rather than doing it one prompt at a time.
- Breaks a larger job into ordered steps and works through them without a fresh prompt for each one
- Carries context from one step to the next, so it does not forget what it found two steps ago
- Keeps going on the routine middle of a task while you stay free for the parts that need you
Workflow
Write down the whole job as a short list of steps before you hand any of it over
Mark which steps are safe to run freely and which must pause for your approval first
Ask the model to work step by step and to show you its plan before it acts on anything that matters
Let it run the reversible, low stakes steps, and hold the gate on anything costly or hard to undo
Check the real result at the end, the actual file, message or record, against what you asked for
Prompts to try
Use it, adapt it, and make it your own.
I want you to handle this multi step job: [describe the whole job and its steps]. First show me your plan as a numbered list and wait for my go ahead. Then work through it step by step. Before any step that sends a message, spends money or changes a saved record, stop and ask me. Tell me clearly what you actually did at each step, not just that it is done.
Human lens
- You scope the job and set the limits: what it may do, what it must ask you before doing, where it must stop
- You keep a checkpoint before any step that spends money, sends a message or changes a real record
- You watch what it actually did, not just its summary of what it did, since the two can differ
What to avoid
- The more autonomy you give, the further a wrong turn travels before you notice, so scope it tightly at first
- A tidy summary of what a model did is not proof it did it, so check the real output
- Never let an agent send messages, make payments or change records unsupervised until you have seen it work on small, safe runs