AI Agents Development

Task-executing agents wired into your real tools — with tool contracts, evaluation harnesses and hard limits on what they are allowed to do.

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Overview

What this actually involves

An agent is only as good as the tools it can call and the tests that hold it honest. We define a narrow tool surface, write the contracts, and build an evaluation suite from your own historical cases before a single agent runs against production data.

Permissions, spend limits, retry policy and escalation paths are part of the build, not an afterthought. Agents that cannot complete a task hand it to a person with the full context attached.

Process

How we deliver it

01Process traceTwo weeks inside the work: every step, exception and handoff, timed and costed. The output is a map — automate, keep human, delete.Process map, business case, delivery plan

02Architecture & evaluation designSystem design, tool contracts and the evaluation set built from your historical cases. The release bar is agreed before code is written.Architecture note, golden set, success criteria

03Vertical slice buildOne complete workflow at a time, in production, used by real people. Weekly demo, fortnightly release.Working software in production

04Evaluation & hardeningAdversarial testing, confidence calibration, escalation tuning and load behaviour under real volume.Evaluation report, tuned thresholds

05DeploymentInfrastructure as code, progressive rollout, rehearsed rollback and cost attribution per feature and tenant.Reproducible environments, runbooks

06Operate & improveOn-call, drift monitoring and a monthly cycle that feeds production traces back into the evaluation set.Monthly operations review

Benefits

What you get out of it

Evaluated before releaseGolden sets built from your historical cases gate every deploy.

Bounded authorityExplicit tool contracts, spend caps and approval steps for irreversible actions.

Graceful escalationFailed tasks arrive with a person with the full trace attached.

Continuously improvedProduction traces feed back into the eval set every sprint.

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