Service 11 · AI agents that act
AI agents that take real actions
A demo that answers questions is easy. An agent that changes something in a live system needs a way to know it got the answer right first.
Fig. 11 — AI agents that act
What this usually looks like
- An agent that cannot tell whether its own output is correct.
- Tool access with no limit on what it can change.
- No record of what it did, so a bad action cannot be traced.
- A proof of concept that works once and cannot be repeated.
What you get
- An agent wired to the specific tools the job needs, and no others.
- A validation step that has to pass before any write happens.
- A log of every action taken, with the input that caused it.
- A written statement of what the agent will not do.
Built and packaged a validation server that gives a model a way to check its own output, with 139 automated tests and an MIT licence.
Questions
Which model do you use?+
Whichever fits the job and your data rules. The architecture is not tied to one provider, and we will say what we tested.
What stops it doing something stupid?+
A check that must pass before it writes, a narrow set of permitted tools, and a log. Not a prompt asking it to be careful.
Do we need a proof of concept first?+
Usually yes, and it should be small. One real action, end to end, before anything wider.
Next step
Tell us what is not working
Describe the problem in a few lines. You get a plain answer about whether it is worth fixing and what it would take, before any money changes hands.
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