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Agent Operations Retainer

Your agent gets better every month — or we tell you why it isn't.Agents drift. Models update. Tools change. Your business evolves. This retainer keeps your deployed agent sharp: weekly eval review, drift monitoring, prompt tuning, tool additions, monthly cost optimization, and a written report so you know exactly what we did and what changed. Cancel any month.

price

from $600

timeline

Monthly · cancel anytime

cadence

monthly/mo

scope

Monthly retainer / cancel anytime

Eval reviewDrift monitoringPrompt tuningCost optimizationTool additionsMonthly report
// compare the flagship suite

Compare flagship offers

Five engagements. Pick what matches your situation.

See all services
EngagementPriceTimelineModeBest forAction
AI Implementation Consulting
from $1,0002 weeksAuditDon’t know where AI fitsView
AI Agent Development
from $2,6004 weeksBuildRepetitive ops work eating your weekView
AI Voice Agent
from $1,8003 weeksBuildMissed inbound callsView
AI Lead Engine
from $2,2004 weeksBuildTargeted outreach without spamView
Agent Operations RetainerYou’re here
from $600/moMonthlyOperateAlready shipped — keep it sharp
01// why this exists

Your agent has an on-call team. That team is us.

AI agents fail in slow, quiet ways: a vendor changes a tool API, a model gets updated, eval scores creep down, costs creep up, edge cases stack up. Without monitoring you find out from a customer. We watch eval pass rates, spend trends, and the activity log every week. We tune prompts, add test cases, ship guardrails, and write a monthly retro you actually want to read. Cancel any month — no annual lock-in.

BYOK

Pay LLM providers direct — no markup on tokens

Eval harness

Regressions caught in CI before they reach production

Spend cap

Hard ceiling you set — no surprise OpenAI invoices

Human-in-loop

Approval queue on every action that touches money or customers

02// how it works

The architecture, end to end.

No black boxes. Here's the actual shape of the system you get — with the guardrails, eval loops, and human approvals where they belong.

What we monitor every week

A real ops loop, not a dashboard you forget about.

feeds backEval pass ratetrend · regressionsSpend trend$ / task driftError logtool failuresWeekly reviewus, with youPrompt tuneprove with evalsNew test casesedge cases capturedMonthly retrowhat changed · why
inputcoreoutput
// where this fits

Real use cases we ship.

  • 01

    You shipped the agent, now what?

    Production AI is a moving target. Models update, APIs change, edge cases stack up.

  • 02

    No internal AI team yet

    Buy ops capacity by the month instead of hiring a $180k role for a part-time job.

  • 03

    Multi-agent stack

    Voice + ops + lead engine all running? Coordinated tuning so they don’t fight each other.

  • 04

    Compliance-sensitive industries

    Documented changes, eval evidence, and audit-ready retros every month.

04// what you walk away with

The outcome, not just the output.

  • 01Agent quality stays high — or you find out exactly why it dropped
  • 02New tools and workflows added as your business grows
  • 03Monthly cost optimization (model swaps, prompt compression, caching)
  • 04Drift detection so you catch problems before customers do
  • 05Written monthly report — what we did, what changed, what's next
// agent flow

How the agent thinks.

The decision graph behind the engagement. Inputs, branches, and the point where a human stays in the loop.

Agent Operations Retainer CycleA cyclical operations loop: monitoring (latency, eval, cost) → drift detection → eval harness → patch deploy → reporting, with arrows returning to monitoring.1 · Monitoringlatency · eval · cost2 · Drift Detectiondistribution shift · regressions3 · Eval Harnessgolden set · A/B4 · Patch Deploycanary + rollback5 · Reportingweekly · monthlysignalrerunship fixrecordrollupCONTINUOUSmonthly retainerCYCLE · arrows clockwise · feedback never stops
// your command center

The dashboard you actually use.

Every flagship engagement ships with a control panel — live activity, eval pass rate, spend cap, and an approval queue you can act on from your phone.

Live · Production

Agent Ops — This week

Sample retainer report. You get this every Monday.

Eval pass rate
96%
+1pp vs last wk
Spend / task
$0.041
−8%
Tool failures
4
3 fixed
New evals added
+7
edge cases
Live activity
last 5 min
  • MonTuned quote-drafting prompt: cut hallucinated SKUs from 3% to 0% in evals
  • TueAdded 4 test cases from this week’s approval-queue rejections
  • WedAnthropic API change — updated client lib, no agent downtime
  • ThuSpend cap raised $500 → $750 (you approved) — reflects 30% volume growth
  • FriSent monthly retro: 3 wins, 1 close call, 2 changes for next month
Eval pass rate96%
42 / 44 test cases passed · last run 12m ago
Monthly spend$612 / $750
Auto-pause at cap. Slack alert at 80%.
Awaiting approval1
  • Refund request > $250 — review
  • Outbound email batch — 12 ready
  • 1 more queued
05// methodology

How the engagement actually runs.

Concrete phases, concrete artifacts. You always know where we are and what comes next.

  1. Week 1 of month

    Eval review + drift check

    Sample 20–50 real agent runs. Score against eval criteria. Flag anything that drifted. Review cost trends.

    Eval scorecardDrift reportCost trend chart
  2. Week 2

    Tuning + improvements

    Apply prompt + tool fixes based on eval findings. Add new tools or workflow expansions. Re-run evals to measure improvement.

    Updated promptsNew tool integrationsBefore/after eval delta
  3. Week 3

    Cost optimization

    Review model choice + prompt length + caching opportunities. Test cheaper alternatives where quality holds. Document savings.

    Model comparisonCost savings reportUpdated configs
  4. Week 4

    Report + planning

    Monthly performance report. Loom walkthrough of changes. Plan next month's priorities with you.

    Monthly PDF reportLoom walkthroughNext-month plan
// track record

Receipts, not promises.

Weekly
Eval review cadence · on real runs
2 new
Tools / mo included · or workflow expansions
Cancel any month
Commitment · no contracts
06// scope

Concrete artifacts you keep — and what we leave out.

Working code, written docs, dashboards your team owns. We also list what this engagement deliberately does not cover, so scope is honest before you sign.

// deliverables
  • Weekly eval review on a sampled set of real agent runs
  • Drift monitoring with alerts when quality scores drop
  • Prompt + tool tuning based on eval findings
  • Up to 2 new tool integrations or workflow expansions per month
  • Monthly cost optimization review (model choice, prompt length, caching opportunities)
  • Monthly performance report (PDF + Loom)
  • Slack channel with 1–2 business day response on issues
  • Quarterly strategy call to review trajectory
// not included
  • Brand new agent builds (use AI Agent Development)
  • Major architecture rebuilds (separate engagement)
  • On-call / 24/7 support (use Reliability Retainer for that)
// add-ons

Extend the engagement.

Additional agent

+$360/mo

Add a second agent under the same retainer scope.

On-call support

+$600/mo

24/7 pager for agent-down incidents with 1-hour response.

Sample deliverables

See the artifact, not the marketing.

Real shape, redacted content. Pick a tab to preview what ships.

Sample Audit Report

Twelve-page audit excerpt: scope, methodology, findings ranked by impact, and a prioritized fix list. Redacted.

Sample provided after intro call · ask sage@sageideas.dev

SAMPLE · REDACTED
How we reduce risk

Money-back if you're not happy in week 1

Reset the engagement before momentum builds. No invoices to dispute, no awkward email.

Async-first, weekly demos, no surprises

You see exactly what shipped each week. No status meetings to attend, no reports to chase.

Code is yours from day 1 — no lock-in

Your repo, your infra, your accounts. We work in your stack. You can take the work in-house at any time.

07// questions

Honest answers.

01Why do agents need ongoing operations?
Three reasons: (1) Models change — what worked on GPT-4-0314 may not work on GPT-5. (2) Your business changes — new tools, new processes, new edge cases. (3) Drift is real — without monitoring, quality degrades silently. The retainer makes this someone's job.
02What if I built my agent with someone else?
We can take over operations on agents we didn't build, but we need a 1-week onboarding to map the architecture and stand up our eval harness if you don't already have one. Onboarding is included in the first month at no extra cost.
03Can I cancel?
Any month, no commitment. We give you the playbook and dashboard access on the way out so your team can take it over.
04How does this compare to hiring an AI engineer?
An in-house AI engineer costs $8–15k/mo loaded. This is a fraction of that, with a tighter scope (agent ops only). If you have multiple agents and need broader engineering, hire an engineer. If you have one or two agents and need them maintained well, this is the play.
// engage

Ready to scope Agent Ops?

Book a 30-minute discovery call. No pitch deck. We'll either confirm fit and send a proposal, or tell you straight that this isn't the right move.

automation system

From offer to operating system.

Agent Operations Retainer is presented as a real engagement, not a generic service page: the surface, backend shape, delivery artifacts, and conversion path are all visible before the first call.

Scope Agent Ops

price

from $600

timeline

Monthly · cancel anytime

tier

flagship

Living architecture

Scope ⇄ Ship

The page now exposes how the engagement moves from buyer pain to production artifact, then into measurement and next-step routing.

Scope Agent Ops
  1. 01Eval review + drift checkSample 20–50 real agent runs. Score against eval criteria. Flag anything that drifted. Review cost trends.
  2. 02Tuning + improvementsApply prompt + tool fixes based on eval findings. Add new tools or workflow expansions. Re-run evals to measure improvement.
  3. 03Cost optimizationReview model choice + prompt length + caching opportunities. Test cheaper alternatives where quality holds. Document savings.
  4. 04Report + planningMonthly performance report. Loom walkthrough of changes. Plan next month's priorities with you.

Conversion path

  1. 01

    Diagnose

    Confirm the real automation constraint, current surface, and business goal before writing code.

  2. 02

    Design the system

    Turn the offer into screens, data, workflows, ownership boundaries, and a measurable delivery plan.

  3. 03

    Ship the artifact

    Deliver Agent Ops as working code, docs, dashboards, or launch assets your team can actually use.

  4. 04

    Route the next move

    Decide whether the work becomes a one-time delivery, a care plan, or a larger product build.

Proof assets

Agent Operations Retainer service visual

Asset slot

Service proof visual

Add a real screenshot, deliverable preview, or dashboard capture from a shipped engagement when approved.

pending real proof
Jason Teixeira, founder of Sage Ideas

Verified asset

Founder/operator photo

Real founder photo reinforcing principal-led delivery.

live

Asset slot

Client quote or logo

Add only permissioned testimonials or logos tied to this service category.

pending real proof
livebuild 81e8c8e2026-07-28 06:02Z
// solo studio// no analytics resold// every commit human-reviewed