A prototype is easy. An agent that is still accurate and affordable a year after launch needs a process, and ours has five phases: Understand, Design, Build, Deploy, Evolve. This is what each one contains and what you see as a client.
Why a cycle
A software project ends at delivery. An agent does not: models change, tools change, the business changes, and accuracy moves with them. So the agent goes through the phases, ships, and then keeps going round, evaluated and improved on a fixed cadence.
1. Understand
We map the process, the data, and the decision points. Where does the task start and end, which systems does it touch, and what does a wrong answer cost?
If an agent is not the right answer, we say so. Some processes need a simple automation, a form, or nothing.
What you see: a process map, a data inventory, a risk assessment, and a clear go or no-go.
2. Design
Architecture, tools, limits, and evaluation criteria, before any code.
We agree with you what "the agent did its job" means, in numbers: resolution rate, data accuracy, escalation behaviour, cost per resolved task. Those criteria become the eval harness that every later change is tested against. Criteria written after the fact tend to describe whatever the system happens to do; written first, they describe what the business needs.
We also write down the three lists every agent works within: what it does alone, what it asks you, and what it never does.
What you see: an architecture document, the limits for each action, and the evaluation criteria you will hold us to.
3. Build
Iterative development with working demos on your own cases from the start. Early on there is a working agent: narrow and supervised, but real. An agent touching your actual systems teaches more than another round of design documents.
What you see: regular demos on your data, with the eval results visible.
4. Deploy
The agent goes live with tracing, logging, and cost tracking from day one. Limits start conservative and widen as evaluations and production data justify it.
What you see: a production agent, an operations dashboard, and an escalation path your team actually uses.
5. Evolve
On a fixed cadence we re-run the evals, review production traces, add new failure cases to the datasets, test model and tool upgrades against the harness before adopting them, and tune cost. Without this phase, "production agent" is a snapshot that expires.
What you see: a recurring report with resolution rate, cost per task, incidents, and what we changed and why.
Each lap is also how a company moves up the levels of autonomy: one process at a time, on evidence.
To see the cycle applied to one of your processes, look at our work or book a call.
What goes on autopilot first?
Tell us how you work today. We will tell you where to start.
Book a call