02 of 7 in AI
Agent Harnesses
Orchestration, tooling, evals and guardrails for agents at scale
Start a projectIn short
An agent without a harness is a liability with an API key. The harness is the layer around the model: orchestration, tool permissioning, evaluations, observability, and the human checkpoints that make an agent safe to run in production. This is for teams already past the prototype stage who need their agents trustworthy enough to scale.
Deliverables
What you get.
Everything listed here is a thing you can hold: a document, a system, a working piece of software. Not hours, not effort.
- 01Orchestration design: how agents, tools and humans hand work to each other, and in what order
- 02Tool permissioning and sandboxing, least privilege by default
- 03Evaluation suites that catch regressions before your users do
- 04Observability: per-run traces, cost tracking and audit logs you can actually read
- 05Human-in-the-loop checkpoints placed where the stakes demand them, not everywhere
- 06Failure design: timeouts, retries, rollback paths and a kill switch that works
Capabilities
What we can take on.
The concrete jobs this service covers. Yours is not listed? Ask anyway: the honest answer is often a sibling service.
- Tool wiring: the systems an agent may touch, and nothing more
- Memory and context, so the agent knows the job and not just the prompt
- Human approval checkpoints at the steps that carry risk
- Audit logs on every action, so nothing the agent does is a mystery
- Kill switches and rollback for when something looks wrong
- Evaluation suites that run in CI, not in a demo
Process
How we work.
Four stages, one line. The order never changes; the depth does.
- 01Inventory the blast radiusEvery tool the agent can touch, ranked by what a mistake there costs you.
- 02Build the rails before the enginePermissions, logging and the kill switch exist before the agent gets more capable.
- 03Red-team itWe try to make the agent misbehave: prompt injection, malformed data, adversarial inputs.
- 04Operate and tuneThresholds and checkpoints get adjusted against live traces, not gut feel.
The working model
The harness, drawn.
Four stages, narrated, with captions. Sound is off until you ask for it.
Why Web Fortuners
Three reasons, checkable.
- 01
Our harness patterns come from systems that survived real users
A production assistant built this way fields legal enquiries on a live client site today.
- 02
Safety is scoped as a deliverable, not a slide
You get the kill switch, the logs and the eval suite as working software.
- 03
One team builds the agent and its rails
Nothing falls into the gap between two vendors when the same people own both.
FAQ
Questions, answered.
The things people ask before they write to us. Yours is not here? Ask it directly.
Yes, that is the most common starting point. We keep what works, wrap it in permissioning, evaluation and observability, and tell you honestly which parts of the prototype have to go.
Real tasks from your business, with known-good answers. The suite scores every model or prompt change against them, so a regression gets caught in testing instead of in a client email.
No. The harness sits between your agents and the model providers, so swapping a model is a configuration change plus a re-run of the eval suite, not a rebuild.
Fixed scope, quoted in writing before work begins. Harness work scales with the number of tools and checkpoints, which we map in the scoping session.
Proof
The pillar at work.
No case study credits this exact service yet. These credit its siblings in the AI pillar: same studio, same standards.
AI pillar
Agents that do, not chat.
Models put inside the workflow, with the harness, the evaluations and the human checkpoints that make them safe to run in production.
- 01AI AgentsAutonomous agents that execute real work, not chatbots
- 03API Integration & ImplementationLLM APIs, MCP servers and system integration done right
- 04Knowledge SystemsRAG and vector search over your company knowledge
- 05AI Strategy & EvaluationAdoption roadmaps, evals and safety for teams going AI-first
- 06Workflow AutomationEnd-to-end business processes automated with AI in the loop
- 07Conversational AgentsChat and voice agents that answer, qualify and book, around the clock