Agents that take real actions — with a hand on the brake.
An agent that only chats is a demo. An agent that books, routes, updates and escalates inside your client's systems is a product — and it needs guardrails, because the failure mode is no longer a bad sentence, it is a bad write to production.
Scope this with us“Can it just handle the whole intake process without someone doing it manually?”
One agent, a defined set of tools and one approval workflow fits a 14-day sprint. Multi-agent orchestration across several systems is a two-sprint scope.
Tool calling against real APIs
The agent operates your client's existing systems through their actual endpoints — no parallel data store to keep in sync.
Human-in-the-loop where it counts
Anything that writes, spends or contacts a customer can be gated behind approval. You choose the threshold with the client.
Traces for every run
When the client asks why it did that, you open the trace and answer instead of guessing.
Safe failure behaviour
Timeouts, retries and fallbacks defined up front, so a provider outage degrades the feature rather than breaking the app.
The parts that decide whether it survives contact with users.
- Structured tool and function calling with validated arguments, so malformed calls fail loudly instead of silently
- Approval gates and dry-run modes on any destructive or outbound action
- Bounded loops and step limits — an agent that cannot terminate is an agent that bills forever
- Idempotency on writes, so a retry does not double-book or double-charge
- Model routing: a cheap fast model for extraction, a stronger one for reasoning, chosen per step
- Run-level observability with cost and latency per step, so you can price the feature accurately
- Give an agent unrestricted write access and hope the prompt holds
- Build a five-agent swarm where one well-scoped agent would do
- Leave retries undefined until a provider outage takes the client's app down
- Ship without traces, then debug production by re-reading the prompt
Before you scope it.
How do we stop it doing something expensive or embarrassing?
Approval gates on the actions that matter, step limits, and dry-run mode during rollout. We agree with you which actions are autonomous and which need a human before any of it goes live.
Do you use a framework or build from scratch?
Both, depending on scope. LangChain and similar frameworks save real time on standard patterns; when the logic is specific enough that the framework fights us, direct SDK calls are cleaner to maintain. We pick based on what your team will have to support afterwards.
What if the client's APIs are old and badly documented?
Common, and workable. We treat the integration layer as part of the scope and surface it during the day 1 to 2 scope lock, so it is priced rather than discovered.
Want to stop turning down AI projects?
Bring the scope you’re unsure about — an RFP, a client request, a half-quoted project. We’ll tell you what’s buildable, what it takes, and whether it fits in one sprint. No charge for the call.