Your agents are running. Nobody knows what they’re doing.
You shipped. Things mostly work. But costs are unpredictable, ownership is fuzzy, and when something goes wrong you can’t explain it — not to your team, not to your board. This isn’t a code problem. It’s a control problem.
Most teams that adopt AI agents do it the right way for the wrong reasons: fast, iteratively, with strong product instincts. What doesn’t get built is the operating model — the governance, the observability, the cost controls, the clear ownership of what happens when an agent fails at 2am.
The technical debt is real, but it’s downstream of an organizational gap. Someone needs to map it, name it, and help you fix it.
How we work together
Three phases. You decide how far to go. The first one stands alone — it’s designed to.
Control Review · Entry point
We sit down together and map what you actually have.
Two to three days, working alongside your team. We look at your agent architecture, your cost exposure, who owns what, where observability stops, and what happens when things fail. You get a clear picture of the gaps — technical and organizational — and a written assessment you can act on. Fixed fee. No retainer required. Most teams find this alone is worth it.
Remediation
We fix it, together.
Hands-on, embedded work. We implement the guardrails, build out the observability layer, and establish the operational patterns your team needs to own the system long-term. The goal isn’t to make you dependent on us — it’s to leave you with a methodology, not just a patch.
Oversight
We keep an eye on it as you grow.
Periodic check-ins, async advisory, and a standing relationship as your agent infrastructure evolves. For teams that want a senior technical perspective without adding headcount.
What this actually covers
Governance. Who owns each agent. What it’s allowed to do. How decisions get made when behavior is unexpected.
Observability. Trace what your agents are doing, catch failures early, understand cost at the task level — not just the invoice level.
Guardrails. Rate limits, fallback logic, human-in-the-loop checkpoints, and cost controls that are enforced — not just documented.
Operating model. The process, roles, and habits your team needs to run AI systems responsibly as the stack grows.
What we bring
SRE and DevOps depth. We’ve done reliability engineering for distributed systems at scale. Agents are a new failure mode on familiar infrastructure patterns.
Observability fluency. Prometheus, OpenTelemetry, structured tracing — we know how to instrument things that misbehave.
Pattern recognition from the last wave. We were present when containers and Kubernetes outran engineering discipline across the industry. This problem rhymes.
No hype, no vendor agenda. ShippingBytes is an independent consulting firm. We don’t sell tools. We fix situations.
Start with the Control Review.
A paragraph about what you’ve built and what’s worrying you is enough to start.
info@shippingbytes.com · subject: "Control Review — [one line about your stack]"
We respond personally. No forms, no account managers.