Quick challenge: paste your current project plan into Claude or ChatGPT right now. Then add this prompt:
“Assume it is 6 months from now and this project has failed completely. List the 5 most likely points of failure and how we could have patched them.”
Read the output. If nothing stings, your plan is solid. If something does, you just caught a blind spot before it cost you weeks. Most people skip this step entirely. They write the plan, feel good about it, and jump straight into execution. Then they hit a wall at week three that they could have seen coming on day one.
This prompt takes about five minutes. The wall takes weeks to get around.
🧠 Why This Works
There’s a thing called Optimism Bias. You wrote the plan, so your brain filters out the bad news. You’re too close to the thing to see the holes.
The Pre-Mortem flips that. Instead of asking “will this work?” you ask “how did this already fail?” That shift unlocks completely different reasoning, from you and from the AI.
The technique comes from psychologist Gary Klein, who used it with NASA engineers and military teams before it became a standard tool in product strategy. The idea is simple: mentally travel to a future where everything went wrong, then trace back what caused it. When you approach a plan as a post-mortem instead of a pitch, your brain stops being a cheerleader and starts being a detective.
The AI adds a layer that’s hard to get from your own head. It has no ego investment in your plan. It doesn’t care that you spent three weeks building it. It will point out the obvious things you missed, and sometimes the non-obvious ones too, if you push it. That combination of zero attachment and broad pattern recognition is genuinely hard to replicate with a human reviewer who wants to be supportive.
⚙️ How to Run It
- Write out your plan, rough notes are fine, no need to polish it first
- Paste it with the prompt above
- Read each failure point without defending yourself, that part matters
- For each one: patch it now, put it on your watch list, or consciously accept the risk
- Update your plan before you start building anything
A few things that help. Be specific in what you paste. “Launch a new product” gives you vague output. “Launch a SaaS tool for freelance designers, targeting $500 MRR in 90 days, with no existing audience and a $200 marketing budget” gives you something sharp and actionable. The more context you give the AI, the more precise the failure modes it surfaces.
Also, do not skip step three. The instinct when you read failure point two is to immediately argue with it in your head. Notice that instinct and do the opposite. Sit with each failure mode for thirty seconds before you respond to it. The ones that trigger a defensive reaction first are usually the ones worth investigating the most.
📊 What the Output Actually Tells You
If the AI surfaces obvious stuff you already knew, your plan is probably solid. If something surprises you or stings a little, that’s the real signal. Go deeper on those.
Run this before you write the first line of code or send the first email. Once you’re in motion, the pre-mortem loses half its power.
Here is what the signal types actually mean. If the AI lists things like “insufficient budget” or “unclear target audience” and you have already solved both, that is confirmation your plan is reasonably built. But if it says something like “the core assumption that users will change their existing behavior has no validation step,” and you realize you have no plan to test that assumption before you build, that is weeks of wasted work you just avoided. If three of the five failure points cluster around one theme, like unclear ownership or dependency on a third party you don’t control, that theme is your highest risk area. Build a mitigation plan before you move on.
💡 Extra Tips
- Run it with two different models. Claude and GPT-4 tend to catch different failure modes
- Go deeper on anything that surprised you: “Expand on failure #3. What specifically causes it and give me three concrete ways to prevent it.”
- Use it for decisions too, not just projects: “Assume this hiring decision turned out to be wrong. Why?”
- Re-run it at every major pivot point, not just at the start. If your plan changes significantly, the failure modes shift with it. Two minutes to re-run beats two weeks going in the wrong direction.
- Try it on a past decision you already regret. It is a useful calibration exercise to see whether the AI would have caught what actually went wrong. Most of the time, it would have.
🎯 Your Move
Pick one thing you’re planning right now, a project, a campaign, a launch. Run the Pre-Mortem on it before end of day.
You’ll either feel more confident about your plan or catch something that saves you weeks of backtracking. Honestly, both outcomes are worth the five minutes.
The ‘Pre-Mortem’ Project Killer.
by u/Significant-Strike40 in PromptEngineering