Incident Response Workflow

PagerDuty goes off at 2am. By the time you're at your laptop, half the response is already in motion.

Updated 2026-04-18
Tycoon solution

AI CTO + AI Customer Support run the incident response shell so you focus on the diagnosis. Alert triage + severity classification within 60 seconds. Status page auto-updated. Customer comms (Twitter, email to affected users, Discord) drafted with one-click send. Status updates every 15 minutes during incident. Postmortem auto-drafted within 24 hours with timeline, root cause, and action items.

How it runs

  1. Alert triage + severity

    PagerDuty/Sentry alert hits. AI CTO classifies severity within 60 seconds: P0 (total outage, revenue impact), P1 (degraded service, many users), P2 (partial degradation), P3 (minor). Looks at error volume, affected endpoints, customer impact from logs, similar past incidents. Severity drives the rest of the workflow.

  2. Status page update

    For P0/P1, AI CTO immediately updates your status page (Statuspage, Instatus, or custom). Initial post: 'We're investigating elevated error rates on checkout. Started at 2:07am PT. More updates in 15 minutes.' No need to wait for you to remember.

  3. Customer comms draft

    For P0/P1: draft comms for Twitter, Discord, and email to affected users (identified from logs). You approve and ship, or let AI Customer Support ship after severity threshold (configurable per channel). Comms are specific, not 'we're working on it' — 'checkout is failing for ~15% of users; we've identified the cause (new deploy rolled back); ETA 30 minutes for full resolution'.

  4. War room setup

    Slack incident channel auto-created (#inc-2026-04-18-checkout). On-call, relevant owners (by CODEOWNERS), and you are added. Incident commander role assigned (usually you for solo founders; AI CTO acts as scribe + timekeeper). Links to Sentry, logs, and affected dashboards posted.

  5. Status updates every 15 min

    During the incident, AI CTO posts status updates to the incident channel + status page every 15 minutes: what's been tried, what's working, current hypothesis, ETA. Prevents 'radio silence' that makes customers panic. You focus on fixing; the comms layer runs itself.

  6. Resolution and all-clear

    When you mark the incident resolved, AI CTO: updates status page to 'resolved', posts all-clear comms to Twitter/Discord/email (including what was fixed), closes the incident channel, and kicks off the postmortem workflow.

  7. Postmortem draft within 24 hours

    AI CTO drafts a blameless postmortem in Notion: timeline (auto-generated from incident channel + logs), impact (users affected, revenue lost, duration), root cause (5 whys), action items (each with owner + deadline), related past incidents. You edit in 30 minutes instead of writing from scratch.

Who runs it

  • hire/ai-cto
  • hire/ai-customer-support
  • hire/ai-coo

What you get

  • Alert-to-first-comms time drops from 30 min to <5 min
  • Status page always accurate, no 'all systems operational' during outages
  • Customer comms shipped in real time, not in 2-hour batches
  • Incident channel has full context for anyone joining mid-response
  • Postmortem drafted within 24 hours, not 2 weeks later
  • Action items tracked — past incidents don't repeat
  • Founder-on-call can focus on diagnosis instead of ops juggling
FAQ

Frequently asked questions

Clear answers about wallet credit, usage, subscriptions, and how Tycoon charges for work.

I'm a 1-person technical founder. Do I need incident response workflows at this stage?

Yes, more than at 20 people. At 20 people, you have ops teammates who catch the gaps; at 1 person, a 2am alert means you forget to update the status page, you miss the email to affected users, and the postmortem never gets written. Tycoon's main value for solo founders is being the ops shell while you're deep in diagnosis — the comms layer runs without needing your attention. Most solo technical founders set this up after their first major incident, wishing they'd had it for that one.

What about false-positive alerts — PagerDuty goes off for non-incidents all the time. Does this create noise?

AI CTO learns your false-positive patterns over 2-4 weeks. Alerts that historically resolved in <5 minutes without action get a lower severity (P3) and skip the customer-comms workflow entirely — they still create an incident record for tracking but don't update the status page or draft comms. This dramatically reduces alert fatigue. True incidents get the full workflow; false positives get logged and ignored. Over time, the alert-quality improvements (tuning thresholds, deleting noisy alerts) compound because you're seeing the patterns clearly.

Our customers are enterprise with SLAs. We can't send 'we're working on it' tweets; they need formal RCAs.

Enterprise mode. AI Customer Support drafts customer-account-specific communications: direct email to the customer's primary contact with incident details, impact on their account specifically, and a formal RCA within the SLA window (typically 5 business days). Parallel public comms still run for transparency but the enterprise path is first-priority. For multi-tenant platforms, AI Customer Support identifies which enterprise accounts were affected vs not and only notifies affected ones — no false-positive panic emails.

How does this handle partial outages — some users affected, not all?

Precise targeting. From your logs + error tracking, AI CTO identifies the exact affected cohort (e.g., 'users on Chrome 120+, with checkout feature flag enabled, in us-east-1 region'). Status page updates note the partial impact. Customer comms go only to affected users (not a panic email to your whole list). Comms copy reflects the specific symptom the affected cohort experienced, not generic 'service degradation'. This prevents the common mistake of over-communicating (alarming unaffected users) or under-communicating (affected users feel ignored).

Postmortems are only useful if action items actually get done. Does this track completion?

Yes. Each action item gets a Linear/Jira ticket with owner + deadline auto-created from the postmortem. AI CTO tracks completion and reports in the weekly engineering digest: 'action items from 4 past incidents: 7 closed, 2 in progress, 1 overdue'. Overdue items escalate to you. The compounding effect: teams with this workflow typically see P0 incident frequency drop 40-60% over 6 months because the action items actually ship, not because the team gets magically better at writing code.

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