AI AGENTS
Slack-Initiated Guided Playbook Runner
An engineer kicks off a named runbook from Slack, and an agent walks the playbook from Coda interactively.
How it runs
The automated pipeline, trigger to output.
- TriggerEngineer runs Slack slash commandSlack
- ActionFetch named runbook from CodaCoda
- LogicHold at each gated step for confirmation
- ActionRun confirmed steps via shellShell
- OutputWrite full session to Postgres incident logPostgres
What it does
Lets an on-call engineer start a remediation playbook on demand instead of waiting for an alert. The agent loads the named runbook, walks each step in the Slack thread, pauses at gated steps for confirmation, and writes a complete, queryable audit record to Postgres.
When to use it
Use it for planned or suspected issues where the human noticed something before monitoring did — running a capacity drain, rotating a credential, clearing a stuck queue — and wants the playbook guidance plus an audit trail without an upstream alert.
How it works
- 1An engineer triggers the workflow with a slash command naming the runbook.
- 2The agent fetches that runbook document from Coda.
- 3It walks each step in the Slack thread, marking gated steps that need confirmation.
- 4Logic holds execution at each gate until the engineer confirms in-thread.
- 5Confirmed shell steps run and their output is posted back inline.
- 6The full session — steps, approvals, outputs, operator — is written to a Postgres incident log.
Set it up
What you configure once, before turning it on.
- 1Connect SlackChannels, DMs, threads, mentions.
- 2Connect CodaDocs, packs, automations.
- 3Connect ShellRun sandboxed commands inside the workspace.
- 4Connect PostgresAny Postgres URL — query, write, migrate.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More AI Agents workflows
Custom Metrics Cardinality Spike Pager
A webhook from a Datadog monitor fires when custom-metric cardinality jumps; an agent pinpoints the offending metric and tag, estimates the added cost.
Sentry-to-Confluence Runbook Updater
When a Sentry issue is resolved, the agent finds the matching Confluence runbook page and proposes an inline update with the verified fix.
Stale Doc-PR Chaser for Runbook Gaps
On a daily schedule the agent finds runbook doc PRs that were opened from resolved incidents but never reviewed, summarizes what each one fixes.
Resolved Incident to Public Troubleshooting Doc
For customer-facing errors resolved in Sentry, the agent drafts a sanitized troubleshooting entry and opens a PR to your ReadMe documentation.
On-Call Runbook Gap Closer: Resolved Sentry Issues to Doc PRs
An agent reads each newly resolved Sentry issue, compares the actual fix against your existing runbook, and opens a GitHub PR adding the missing remediation steps.
Weekly On-Call Doc-Gap Digest
Each week the agent reviews every Sentry issue resolved in the last 7 days, ranks the ones whose runbook coverage is missing or thin.
Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
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