Agenthub

Solutions / Engineering

Not the code. Everything around it.

The incident is over. Now the write-up, the duplicate tickets, the CVE nobody owns. Agenthub puts agents on that queue — and stops short of anything that ships, merges or goes public.

interrupt load

Fewer interrupts reach a person.

Four reports of one bug become one issue with four threads. What's left is what actually needed an engineer.

after the page

The write-up starts before you do.

Timeline, graphs, the deploy that went out at 14:02 — gathered while it's still fresh. The doc is an edit, not an archaeology project.

the line

Nothing ships or goes public alone.

The sev call, the deploy, the merge and the status-page post stay human decisions. Agents stop at the step that's hard to take back.

A Tuesday after a bad night.

An ordinary morning — one thing stopped because it is about to be read by customers.

Six jobs that never make the sprint.

None of this is writing your code — you have tools for that, and they're fine. This is the operational work that surrounds it: manual, repetitive, interrupt-driven.

  1. Incident comms, while it's still burning

    The comms lead is usually the person who should be debugging. An agent keeps the timeline and drafts the status-page post. It does not declare the severity or publish it.

    Slack-native · Approval gates · “Who did this?”

  2. The write-up, from evidence not memory

    Deploys, alerts, dashboards, the PR that shipped at 14:02. The agent assembles the timeline from the systems that recorded it, then files the action items and chases them next month.

    Data connectors · AI indexing · Operations board

  3. Triage across three trackers

    The bug is a Sentry issue, a support escalation and a Jira ticket. The agent merges the duplicates and routes it to the team that owns the service.

    Work routing · Data connectors · Verified success rates

  4. Alert noise and flaky tests

    The queue of “is this real?”. An agent correlates the alert against deploys, reruns the failing job, and says which it is — with the evidence. Flakes get quarantined, not silenced.

    AI supervisors · Learning from feedback · Failure patterns

  5. The bump nobody owns

    Automated update PRs are easy to generate and expensive to absorb. The agent works out which services pull the affected version, finds the owner and chases the ticket. It never merges anything.

    Data connectors · Company guardrails · Browser agents

  6. The paperwork with a deadline

    Release notes a customer can read, drafted from what merged. The compliance drag — control tickets, access reviews — collected as it happens. Nothing is quietly marked compliant.

    Describe the work · Access control · Version history

What matters in engineering work.

Four reasons engineers distrust this category — and the mechanism behind each one here.

“Almost right” is the expensive failure mode

Agents are checked, not trusted: AI supervisors stop a run that starts guessing, every run is verified and scored, and a triage change can be simulated first.

The irreversible step keeps a human

Deploys, merges, production access and anything published to customers sit behind approval gates — set once as a company-wide rule. Version history and rollback put a bad change back.

The clock belongs to someone else

Under NIS2, a significant incident needs an early warning within 24 hours and a notification within 72 — evidence-gathering under time pressure. The live board shows what's moving, and the audit log records what was gathered.

Your logs are full of customer data

Stack traces carry emails, payloads carry order history. Agenthub runs in the EU, with open models on our own European infrastructure. How we handle your data →

The same action item, in three postmortems. It was never anybody's Monday.

First agent in a month.

  1. Day 1We sit down with you

    Half a day with the tracker and a quarter of incidents open. We pick the highest-volume, lowest-risk job — usually triage and dedup.

  2. Day 7Platform installed

    Connected to Slack, the issue trackers and the alerting tool. Read-only where read-only is enough. Where a vendor console has no API, the agent gets a login.

  3. Day 14First agents at work

    One agent, one job, proposing only: every label, merge of duplicates and comment waits for a person. Your team's corrections become part of the agent.

  4. Day 30Live in production

    Triage runs unattended because a month of scored runs earned it. Deploys, merges, the sev call and anything customers read still stop for a named person.

Bring last month's incidents. We'll do the write-ups.

Thirty minutes, your channel history and your tracker. The interesting part is watching where the agent stops.