OLD SCRIPT DETECTED
“Everyone remembers me as the outage guy”
Try this response:
“The system failed through conditions I didn't control alone. I'm a contributor, not the root cause.”SEE THE PRACTICE
Build a response for this thought—and one move to prove it.
THE THOUGHT
“Everyone remembers me as the outage guy”
YOUR RECORDED RESPONSE
“The system failed through conditions I didn't control alone. I'm a contributor, not the root cause.”
ONE PRIVATE MOVE
Open the incident channel. Find one incident with your name. Read only the system failure section—the actual root cause. Notice whether the cause is something you alone decided to do, or a condition that existed. Write down the condition. Close the document.
The Incident Channel, Six Months Later
The Moment You Refresh the Thread
You're waiting for a build. Muscle memory takes you to the incident channel. You scroll past the timestamps—March, early April—and there it is. Your name, three times on the same day. The outage lasted four hours. You were on call. The Slack thread is archived now, but you've read it enough times that you know the exact sequence: the alert, the rollback decision, the all-clear message signed by someone else. Nobody has written anything new in months, but you're still there in the history, tied to the timestamp when things broke. You close the tab.
The Cost of Staying Sidelined
Next sprint, there's a high-leverage feature that needs ownership. It touches core systems—exactly the kind of work that builds credibility. Your manager mentions it in passing. You find reasons not to volunteer. You tell yourself the junior engineer needs the experience, or the scope is unclear, or you'd rather finish smaller tickets first. The real reason lives in your chest: if that feature breaks in production, your name gets added to another thread. The outage guy strikes again. So you pick safer work. Smaller blast radius. Tickets that fail quietly, if they fail at all.
One Incident Reread That Doesn't Feel Like a Verdict
Open the incident channel again. This time, read past your name. Find the section that describes what failed in the system—not who was on call, but what the conditions were. A config timeout. A missing circuit breaker. A deployment that assumed an old database schema. Notice that those failures are not your biography. They are not graded. They are observations. Your name is in the channel because you were the human who was present, not because you designed the fragility. That is context, not conviction. If you can read your name in that thread without the story changing—without it becoming your character instead of the system's…
TRACE · 01/04
How this script runs you
- You reread the incident channel months later, checking if your name still stings.
- A bug assigned to you lands like a grade, not a ticket.
- You avoid risky, high-leverage work because another incident would 'confirm' the story.
SOURCE_LOCATED · 02/04
The hidden rule underneath
The Incident Ledger
My name is attached to every failure, permanently. The system broke, but the narrative has filed it under my identity instead of under the conditions that caused it. Each incident is proof. Each mention is a permanent mark on what I'm known for.
FORGING_REPLACEMENT · 03/04
Replacement lines (record these)
- The system failed through conditions I didn't control alone. I'm a contributor, not the root cause.
- A postmortem is about the system. My name in it is context, not a conviction.
- Bug count measures the code I touched, not the engineer I am. Zero bugs means zero shipping.
Generated per person in the app — these are the flavor, not your script. Yours is built from your exact words.
INSTALL · 04/04
The protocol, on one card
When I think
“Everyone remembers me as the outage guy”
I say
“The system failed through conditions I didn't control alone. I'm a contributor, not the root cause.”
Then I do one thing
Open the incident channel. Find one incident with your name. Read only the system failure section—the actual root cause. Notice whether the cause is something you alone decided to do, or a condition that existed. Write down the condition. Close the document.
STATUS: READY_TO_INSTALL
Wipe this thought4 minutes. Your voice. Free.
The wipe protocol
- Write the thought exactly as it plays: "Everyone remembers me as the outage guy". Word for word — the wipe targets the sentence, not the vibe.
- Trace the rule and the avoided action. What does this thought conveniently excuse you from doing?
- Record the replacement lines below in your own voice. Speak like you mean it — no recording, no install.
- Run the loop: play it every morning and night, log one proof action a day for 7 days.
Straight answers
Why does seeing my name in the incident channel feel different than seeing someone else's?
The script says: your name proves you're the problem. Other people's names in the same thread prove the system had vulnerabilities. You're reading the same document two different ways. One way, you're a villain. The other way, you were present when conditions failed. The text doesn't change. The story you attach to it does.
If I keep avoiding high-stakes work, won't that actually protect me from being 'the outage guy'?
No. It guarantees it. The outage guy in memory is the person who shipped risky work and failed. But the person who never shipped it at all becomes known for something worse: the engineer who stayed safe. Either way, you've written the ending yourself. The difference is whether you built anything while you were waiting to fail.
How do I know if a postmortem is about the system and not about blaming me?
A blameless postmortem asks: what conditions were true before the outage? A blame postmortem asks: what did the person do wrong? If you're reading your name as the answer to the second question, you're writing a different story than the document contains. Reread it as if you were not involved—what would you conclude about the system?
Related old scripts
Related self-checks
Related science
Researchers to explore
Related mechanisms
The research behind this script
- Postmortem Culture: Learning from Failure — Google SRE, Google SRE Book, 2016
- Invisible Labor in Open Source Software Ecosystems — Champion et al., arXiv, 2024
- Stack Overflow 2025 Developer Survey: Trust in AI at an All-Time Low — Stack Overflow, 2025
- A Mosaic of Perspectives: Understanding Ownership in Software Engineering — arXiv, 2025