premortem

The opposite of a postmortem: instead of understanding what went wrong after the failure, you imagine it has already failed and figure out why, before you start. Gary Klein's method (HBR); Kahneman called it his most valuable decision-making technique. Mechanism: "this is dead, explain how" → the brain generates specific and honest causes, while "is this a good plan?" → produces complacent answers. It breaks the LLM's default agreeableness.

When (and when not)

Yes: a product/feature to build, a launch with money/reputation on the line, a pricing/model change, an assumption, a positioning pivot, a partnership/deal, any commitment where being wrong is costly. No: vague ideas with no plan (help plan first), questions with one answer, feedback on a draft (that's editing), decisions already made and irreversible (a premortem only helps if you can still change course).

Minimum context threshold (mandatory)

A premortem is only as good as its context. Before launching one you need 3 things — look for them first in context (conversation, AGENTS.md, memory/vault, cited files), then ask only for the single most important missing piece, one question at a time:

1. What is it? (describable in one sentence)
2. For whom / who does it impact? (failures depend on who's involved)
3. What does success look like? (failure is inverted success)

Session

1. Explicit frame: "It's 6 months from now. [The plan] has failed. It's over. Let's look back and understand what went wrong." — this is the psychological mechanism, don't skip it.
2. Raw premortem: generate every genuine reason it died — specific, anchored to real details, a true threat (not an edge case). However many are real: 4 or 9, no padding.
3. Parallel deep-dives: one subagent per reason, all in parallel — whatever the host calls its delegation tool (Copilot task, Claude Agent), issued as a single message with multiple tool-use blocks. Model/effort/context come from [[model-selection-policy]], never typed from memory: these are mid-class executors on medium effort, default context; frontier needs a written reason. Each agent gets the full context + its reason and produces: (a) failure story (2-3 paragraphs, like a real case study), (b) underlying assumption (1 sentence), (c) early-warning signal (1-2 observable/measurable signs). <300 words, no hedging.
4. Synthesis (this is the product):
   • Most likely failure (to focus on first)
   • Most dangerous failure (most damage if it happens, even if less likely)
   • Hidden assumption (the biggest one the user hasn't questioned — often where the value lives)
   • Revised plan — concrete changes, each mapped to a failure ("test pricing at $X with 20 people before launching it," not "consider pricing")
   • Pre-launch checklist (3-5 things to verify/put in place, each one preventing/detecting a failure)

Output

• ~/.roberdan-os/reports/premortem-<slug>-<date>.md — full transcript (context, raw reasons, deep-dives, synthesis). Host-neutral home — a single CLI's own directory is not where a cross-host skill writes.
• Optional visual HTML report (dark, scan-friendly, one card per failure) if the user wants to see one.
• In chat: 3 sentences max — most likely failure, hidden assumption, most important revision.

Notes

• Always parallel subagents (sequential wastes time and contaminates results). Always the "it's already failed" frame. Thorough but not padded. Don't sugarcoat — say the uncomfortable things before reality does. Concrete revisions, doable this week.
• Composes with @board (multi-perspective red-team now) and with [[problem-validation]] (where the premortem is the "would solving it work?" stage). Different mechanism, different output.
• Respects human gates: the premortem informs the decision, it doesn't make it.