A production agent for one job
A bounded task — drafting, sorting, summarizing, routing — with typed inputs and outputs. Not a general chatbot. Something that reliably does one thing.
Spire Coast · AI Agents
Let software do the busywork.
Custom agents for specific, recurring jobs — drafting, sorting, summarizing, routing. You approve anything that goes out the door. You know the monthly cost before we start.
§ 01 · What this produces
One agent. One job. Fully traced.
An eval harness you keep
A set of test cases that represent the real work. When a model is swapped or a prompt is tuned, you can see — numerically — whether it got better or worse.
Cost cap and traces on every run
A hard monthly cap enforced on the agent. Traces of every call — inputs, outputs, model, cost. If something goes sideways, you can read it like a stack trace.
§ 02 · How scoping works
Three options, clear cost trade-offs.
The plan comes back with three model / capability options — triage, standard, and deep — each with monthly cost estimates against your expected volume. We recommend one based on the task, but the call is yours.
Direction A
Fast and cheap. High volume.
A triage-class model (Haiku-tier). Right when the task is high-volume, the cost of being wrong is low, and you want near-instant turnaround. Examples: inbox classification, lead routing, first-pass content moderation.
Direction B
The workhorse. Most agents live here.
A standard-class model (Sonnet-tier). Drafting, summarizing, orchestrating multi-step work. Balanced on cost and quality. The default unless the task demands otherwise.
Direction C
Deep reasoning. Fewer runs, better thinking.
A deep-class model (Opus-tier). Long-reasoning tasks, proposal generation, architecture analysis. Expensive per call, priceless when mistakes are expensive. Often paired with standard-tier for preprocessing.
§ 03 · How we approach it
Production-shaped from day one.
Approval in the loop by default
Nothing gets sent to a customer without either your review or a pre-approved template. We turn that up or down per agent — never to zero without an explicit, written decision.
Traces and evals, not vibes
Every run is logged, scored, and replayable. When someone says 'it's getting worse,' we pull up the eval and check. 'It feels off' isn't a metric.
Role names, not model IDs
We never hardcode a specific model. Agents address models by logical role — triage / standard / deep — mapped to a current model via environment variable. When a new flagship ships, one env var changes.
Monthly cost cap enforced
A hard ceiling on per-agent monthly spend, enforced in code. Alerts before the cap. No surprise bills, no runaway loops silently draining the budget.
§ 04 · What affects scope
Priced per engagement, after discovery.
A narrow, pre-approved, one-integration agent is a very different scope from a multi-step agent that touches four systems and needs a review queue. Scope and price land in the written plan after discovery.
- How narrow the task is (a bounded job is always cheaper than a broad one)
- Integrations the agent touches (CRM, inbox, database, tools, web)
- Volume and latency requirements (per-request SLA, monthly throughput)
- Historical examples available to seed the eval set
- Review mode — fully automated, pre-approved templates, or human-in-the-loop
- Security and privacy (PII handling, data residency, regulated data)
§ 05 · Start here
Tell us about the task.
The intake form captures the task boundary and the data the agent would touch. Discovery digs into the edge cases. The plan comes back with three options and realistic monthly cost estimates.