post-mortems-retrospectives — an installable skill for AI agents, published by refoundai/lenny-skills.
Guide teams through learning-focused post-mortems and retrospectives using frameworks from 11 product leaders. Helps frame exercises as blameless learning opportunities rather than blame-focused reviews, with emphasis on psychological safety and honest sharing Covers core principles including pre-mortems with kill criteria, reframing failure as growth, and institutionalizing weekly impact and learnings reviews Guides users through structured questioning to surface systemic insights, early missed signals, and actionable learnings that influence future decisions Flags common mistakes including blame-focused framing, lack of follow-through, and optimizing scores over learning Post-mortems & Retrospectives Help the user run effective post-mortems and retrospectives that drive genuine learning using frameworks from 11 product leaders. How to Help When the user asks for help with post-mortems or retrospectives: Understand the context - Ask whether this is after a failure, a success, or a routine checkpoint Set the right tone - Help them frame the exercise as learning-focused rather than blame-focused Structure for insights - Guide them toward formats that surface actionable learnings Ensure follow-through - Help them create mechanisms to act on what they learn Core Principles Pre-mortems need kill criteria Annie Duke: "A pre-mortem is only effective if it results in 'kill criteria' - pre-determined signals that will trigger a pivot or shutdown." Identify early signals that a project is failing during the pre-mortem and pre-commit to specific actions if those signals are met.
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