Your Agents Shipped. Who Runs Them?
A named team running the maintenance cadence on your production agents: drift triage, eval regression gates, prompt versioning, inference-cost bounds, and incident response.
Deployment is the starting line, and most teams treat it as the finish. Agents drift, tools rot, credentials decay, and the invoice creeps, while nobody owns the system day to day. We run the operating cadence we published and use on our own products and our banking agent at ~500K actions a month, on systems we built or ones we took over.
- DAILY Automated: error rates, cost per run, eval spot-checks, flagged trajectories queued
- WEEKLY Human review, 30-60 min: eval trend, drift triage, flagged runs read by an engineer
- MONTHLY Structured, 2-4 hrs: cost attribution, credential rotation, eval-set refresh
- QUARTERLY Half-day: model upgrades, policy review, access audit, rollback rehearsal
- ANNUAL Decommission review: retire what stopped earning its run cost
What Drift Looks Like in Production
Agents do not crash; they decay. These are the drift types that accumulate quietly in systems nobody owns day to day, named in our operating playbook and seen across production takeovers.
Behavioral Drift
Model updates and prompt edits change behavior one release at a time. Without an eval trend, quality erodes silently until customers notice, and nobody can name the release that caused it.
Cost Creep
Token spend grows with retries, longer contexts, and quiet prompt bloat. Post-call dashboards report the bill after it lands; the creep compounds for weeks before anyone attributes it.
Tool Rot
APIs change shape, endpoints deprecate, and schemas drift while the agent keeps calling them. The failure surfaces as confident answers built on stale tool responses.
Policy Staleness
The guardrails were written for the system as it shipped. New tools, new tenants, and new use cases walk past policies nobody revisited since launch day.
Credential Decay
Agent credentials accumulate permissions nobody audits and secrets nobody rotates. They become dark matter: broad access, expired ownership, no rotation cadence.
Nobody Owns the System
The build team dissolved into the next project. When drift surfaces, the incident lands on whoever notices first, and the fix waits for someone to claim it.
What the Retainer Operates
Six operational surfaces, each run against the cadence below. Every item comes from running our own agent systems in production, not from a services catalog.
The operations surface
- Prompt & config versioning: the five-component manifest tracked per release, with canary rollout and roll-forward
- Eval regression gates: golden-set runs per release; a dropping score blocks promotion
- Model routing & upgrades: provider changes and model versions tested against your eval set before they ship
- Inference-cost governance: pre-call bounds, per-tenant attribution, monthly cost review
- Credential lifecycle: scoped permissions, rotation cadence, quarterly access review
- Incident response: severity tiers, scripted first five minutes, semantic forensics, eval-set closure
This Is What "Managed" Actually Means
Most retainers sell availability. Ours runs a published operating rhythm: what gets checked, by whom, and how often, straight from the maintenance cadence we run on our own systems.
Automated Checks
NO HUMAN NEEDEDError rates, cost per run, eval spot-checks, and flagged trajectories queue themselves. Automation watches; humans review.
Human Review
30-60 MINAn engineer reads the eval trend, triages drift signals, and reviews flagged trajectories. The week’s anomalies get a name and an owner.
Structured Review
2-4 HRSCost attribution by feature and tenant, credential rotation status, eval-set refresh with the month’s failure cases, and capacity trends.
Deep Review
HALF-DAYModel upgrades evaluated against the golden set, policy and guardrail review, access audit, and a rollback rehearsal so the procedure works before it is needed.
Decommission Review
RETIRE OR RENEWEvery agent justifies its run cost or gets retired through the six-step decommissioning checklist, so dead agents stop accumulating access and spend.
Agent Incidents Are Not Server Incidents
A downed endpoint is easy. An agent confidently executing the wrong actions for six hours is the incident that matters, and it needs a different playbook.
Severity Tiers
Tiers calibrated to agentic failure: wrong actions executed, data touched, money moved, records changed. An agent that answered 400 users with bad data ranks differently than a 500 error.
First Five Minutes
A scripted playbook: contain the action surface, preserve the trajectory before it rotates out, classify the failure. Containment means scoping what the agent can do, not pulling a network cable.
Semantic Forensics
The trace tree shows which span produced the bad behavior: the retrieval, the tool call, the prompt, or the model. Closure requires the eval set updated with the failing case, per close criteria and EU AI Act Article 73 timelines.
Why Our Ops Starts Running Day One
Most ops engagements invent the runbook as they go. Ours starts from the operating layer that already runs PASSR, DOCKR, TESTR, and our banking agent in production.
What the cadence carries
- Eval cadence: golden-set runs with regression gates per releaseEVERY RELEASE
- Drift triage: five named drift types with owners and thresholdsWEEKLY
- Cost bounds: pre-call reservation, per-tenant attribution, monthly reviewCONTINUOUS
- Credential rotation: scoped access, rotation cadence, quarterly auditQUARTERLY
- Incident runbooks: severity tiers, first-five-minutes playbook, semantic forensicsALWAYS ON
- Canary & roll-forward: staged releases with eval gates, not big-bang deploysEVERY RELEASE
- Feedback loop: incidents and overrides feed the eval setCONTINUOUS
- Decommissioning: ordered retirement checklist for agents past their valueANNUALLY
What the Retainer Produces
Operations you can inspect. Every review leaves artifacts, so the cadence is auditable rather than a promise.
The operating record
- Ops readiness audit: drift map, ownership gaps, instrumented-surface inventory
- Weekly review notes: eval trend, flagged trajectories, drift triage outcomes
- Monthly ops report: cost attribution, credential status, eval-set changes
- Quarterly review: model upgrade evaluations, policy review, access audit results
- Incident reports with semantic forensics and closure evidence
- Versioning manifest history and canary rollout records
- Runbook updates as the system and its failure modes evolve
- Decommission decisions documented with cost and risk rationale
Audit First, Then Operate
The readiness audit maps what you have and prices the retainer. Operations starts on a fixed monthly fee with a named team.
Ops Readiness Audit
Maps what your system emits, where it drifts, and what nobody owns today. Ends with an instrumented-surface inventory and a scoped retainer price.
Close the Gaps
If the audit finds blind spots, an observability build instruments them first, since a cadence cannot watch telemetry that does not exist.
The Operations Retainer
The cadence runs on your live systems: daily automated checks, weekly human review, monthly structured review, quarterly deep review, incidents included.
Retainer pricing depends on system surface and severity obligations, scoped in the audit. The monthly fee is fixed once agreed.
DIY Ops, Classical MLOps, and Agent Operators
Operations splits between teams that improvise, vendors built for models you train, and teams that run live agents. The difference shows up in the first month after launch.
Whoever notices the problem first.
Training pipelines, model registries, retraining jobs.
Live agents: prompts, tools, evals, cost, credentials, incidents.
Ad hoc, when something breaks loudly enough.
Drift and retraining triggers for owned models.
A published daily/weekly/monthly/quarterly rhythm with artifacts.
A support ticket and a guess.
Uptime alerts that miss behavioral failure.
Severity tiers, scripted containment, semantic forensics, eval closure.
The invoice is the monitoring.
Training compute budgets.
Pre-call bounds and per-tenant attribution, reviewed monthly.
Hope.
Case studies from a different stack.
~500K agent actions/month operated inside PCI-DSS.
| Dimension | DIY Ops | Classical MLOps | FLYTEBIT |
|---|---|---|---|
| What gets operated | Whoever notices the problem first. | Training pipelines, model registries, retraining jobs. | Live agents: prompts, tools, evals, cost, credentials, incidents. |
| The cadence | Ad hoc, when something breaks loudly enough. | Drift and retraining triggers for owned models. | A published daily/weekly/monthly/quarterly rhythm with artifacts. |
| When an agent fails | A support ticket and a guess. | Uptime alerts that miss behavioral failure. | Severity tiers, scripted containment, semantic forensics, eval closure. |
| Cost control | The invoice is the monitoring. | Training compute budgets. | Pre-call bounds and per-tenant attribution, reviewed monthly. |
| Proof | Hope. | Case studies from a different stack. | ~500K agent actions/month operated inside PCI-DSS. |
Match the Tool to the Question
Operations runs what is already live and instrumented. If that is not your question, one of these fits better.
Frequently Asked Questions
What do LLMOps services cover?
The ongoing operation of production LLM systems and agents: prompt and config versioning, eval harness runs with regression gates per release, model routing and provider upgrades, inference-cost governance, credential lifecycle management, drift triage, and incident response. It is the cadence of keeping a live AI system correct, affordable, and accountable over time.
How is LLMOps different from MLOps?
MLOps manages models you train: feature pipelines, training jobs, model registries, retraining triggers. LLMOps manages systems built on models you do not control: prompt and config versioning instead of weight versioning, semantic evals instead of accuracy metrics, inference-cost bounds instead of training budgets, and agent incident response instead of uptime monitoring. If your stack trains models, you need MLOps; if it calls foundation models and agents, you need LLMOps.
How is this different from your observability services?
Observability is a build: a 3 to 6 week engagement that instruments your agents so every run is a readable trajectory. LLMOps is a cadence: a retainer where a named team acts on that telemetry every day, week, and month. Observability produces the traces; operations is what you do with them. Most engagements run observability first, then operations on top.
Can you take over operations of a system already in production?
Yes, takeovers are common. The readiness audit maps what the system emits, where it drifts, and what nobody currently owns, then we instrument any gaps and start the cadence. The system does not need to be one we built.
What does the retainer include?
A named team running the published cadence: daily automated checks on error rates, cost, and eval signals; a weekly human review of eval trends and flagged trajectories; a monthly structured review of cost attribution, credentials, and eval-set refresh; and quarterly deep reviews covering model upgrades, policy, and access audits. Incident response runs inside the retainer with defined severity tiers.
What happens when an agent incident occurs?
Incidents run on severity tiers calibrated to agentic failure modes, not generic uptime. The first five minutes follow a scripted playbook: contain the action surface, preserve the trajectory, and classify the failure. Semantic forensics then trace which span produced the bad behavior, and closure requires the eval set updated with the failing case so the same failure gets caught next time.
How much do LLMOps services cost?
The retainer is priced by system surface: number of agents, workflows, and severity obligations. The ops readiness audit, which starts from $2K, produces the scoped retainer number. If the system needs instrumentation first, that build is scoped separately and priced fixed at kickoff.
Put the Cadence on Your Agents
Schedule a 30-minute working session with our expert team. We will look at who owns your production agents today and give you a straight answer on which drift is costing you most.