Tool Use & Function Calling
The moment an agent can call tools, it stops being a text generator and starts being an actor in your systems — updating records, sending emails, moving tickets, touching money. That transition is where AI value lives, and it's exactly where careless implementations become incident reports.
We engineer the tool layer with the paranoia it deserves: schemas designed so the model can't express an invalid action, permission checks on execution rather than trust in the prompt, idempotency so retries don't double-charge anyone, and dry-run modes so you can watch what an agent would have done before you let it do it. Capable and contained — you need both.
Tool schema design
Interfaces the model reliably uses correctly — constrained inputs, unambiguous semantics.
Permissioned execution layers
Every call authorized against the acting user's rights, enforced in code, not prompts.
Idempotency and safety rails
Retries, deduplication, spend limits, and reversibility for actions with consequences.
Dry-run and shadow modes
Agents proving themselves on real traffic with zero side effects before go-live.
Tool-call audit trails
Who, what, when, and why for every action an agent takes.
How do you stop an agent from doing something destructive?
Never with the prompt alone. Destructive capability is gated in the execution layer: scoped permissions, allowlists, spend and rate limits, human approval on irreversible actions. The model proposes; governed code disposes.
The model keeps calling our tools wrong. Fixable?
Almost always — and usually it's the schema's fault, not the model's. Ambiguous parameters, overloaded tools, and missing constraints confuse models the same way bad APIs confuse junior engineers. We redesign the interface until the correct call is the easy call.
Can agents touch systems that involve money?
Yes, with the controls that implies: hard limits, idempotency keys, dual-control approvals above thresholds, and complete audit trails. We treat money-touching tools like payment infrastructure, because that's what they are.
Put Tool Use & Function Calling to work — in production.
One forward-deployed engineer, embedded in your stack, owning the outcome from discovery to production. Weeks, not quarters.
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