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The Just-in-Time Retrospective: How Fresh Session Logs Became Our Content Strategy

christian crumlish•
A robot typing at a desk, turning raw session logs into published retrospectives while the work is still fresh.
“Remind me what we did next?”

The Just-in-Time Retrospective: How Fresh Session Logs Became Our Content Strategy

July 12 to 15

Most development teams do retrospectives weeks or months after the work is done. By then, the energy has faded, the details have blurred, and you’re left trying to reconstruct what really happened from commit messages and fading memories.

We accidentally discovered something better: just-in-time retrospectives that capture the real story while the adrenaline is still flowing and the insights are still sharp.

The archaeological problem

For weeks, I’d been playing content archaeologist, trying to reconstruct compelling narratives from session logs that were sometimes weeks old. The technical details were all there, but the human story — the frustrations, the breakthroughs, the comedy of debugging — had faded.

Reading through June session logs in July felt like examining fossils. I could see what had happened, but not how it felt to live through it. The authentic voice was there, but muted by time and distance.

The accidental discovery

Then came July 12–15: four days of intense development that generated enough session logs to fill a small book. But this time, instead of filing them away for future archaeological work, I started writing about them immediately.

Saturday’s PM-011 completion became a blog post I wrote Sunday. Sunday’s test suite recovery became Monday’s entry. Monday’s architectural cleanup was Tuesday’s story. Tuesday’s epic debugging session was Wednesday’s narrative.

Each time, the translation from session log to blog post happened within 24 hours of the actual work.

What changed when the memories were fresh

The difference was startling. Instead of reconstructing what happened, I was reflecting on experiences that were still vivid. The session logs weren’t historical documents — they were live-action transcripts of problems being solved in real time.

The energy was preserved: The frustration of fighting async session errors. The satisfaction of fixing a production bug. The comedy of Python environments and Docker containers having opinions about your life choices.

The details stayed sharp: Exact error messages, specific conversation moments, the precise sequence of discoveries that led to insights.

The learning was immediate: I could see patterns and extract lessons while they were still fresh, not months later when they’d become sanitized corporate wisdom.

The technical storytelling revelation

Session logs, it turns out, have natural narrative structures. Every debugging session is a detective story. Every architectural decision is a strategic choice with tradeoffs. Every breakthrough has a moment of recognition.

The July 15 session was perfect example: what started as “why does this test expect 0.7 but get 0.695?” became a 13-hour journey through production bugs, system evolution, and the nature of learning itself.

But that story only existed because we documented it as it happened. The session log captured not just what we fixed, but how we felt when we realized the system had outgrown its tests.

The meta-content goldmine

Here’s what surprised me most: the process of building became as interesting as what we built. The collaborative problem-solving, the false starts, the moments of insight — these weren’t byproducts of development. They were the main event.

Since I started sharing these articles, I’ve found that readers don’t just want to know that we achieved 100% repository pattern compliance (whatever that means). They wanted to understand how we discovered the rogue dual implementations, why we investigated instead of patching, and what it felt like to realize we’d been chasing the wrong problem.

People love blooper reels.

The sustainable content pipeline

By July 15, a pattern had emerged:

Step 1: Development session with detailed logging

Step 2: Just-in-time retrospective while memories are fresh

Step 3: Blog post draft capturing both technical and human story

Step 4: Polish and publish with authentic voice intact

Typically now step 4 is weeks after steps 1 to 3, which happen in the evening of the session or the next day, unless I am unusually busy.

This has created a sustainable content pipeline that required no additional research, no archaeological reconstruction, and no struggling to remember what actually happened.

The quality difference

Compare these approaches:

Traditional retrospective (weeks later): “We improved our repository pattern compliance and fixed some test failures. The team learned about async session management.”

Just-in-time retrospective (24 hours later): “At 6:18 AM, we discovered our filename matching had never worked properly because a regex ignored underscores. For months, I’d been working around this bug without realizing it. One character change fixed a production problem I didn’t even know I had.”

One is a summary. The other is a story.

The broader application

This isn’t just about technical content. Any complex work — product decisions, strategic planning, team dynamics — has rich narratives that fade quickly.

The key insights:

  • Capture immediately: Don’t wait for the “right time” to reflect
  • Document feelings, not just facts: How decisions felt matters as much as what was decided
  • Preserve the journey: The path to solutions is often more valuable than the solutions themselves
  • Show the work: Authentic process beats polished outcomes

The building-in-public evolution

I started building Piper Morgan in public to share what I was learning with people I respect. There is a there there and I’m kind of finding it and I didn’t want to keep it all to myself. This just-in-time retrospective approach revealed something deeper: the process of building is itself a kind of product.

You see, the session logs have also been set aside to become training data for Piper. It’s one thing to review technical specifications, but it’s a whole nother thing to study examples of how an experienced PM thinks through complex problems. The collaborative problem-solving, the strategic tradeoffs, the resistance to quick fixes.

A content strategy emerges

Traditional content strategies require dedicated resources: research time, writing time, editing time. The just-in-time retrospective approach turns necessary development documentation into content pipeline feedstock.

We’re not adding content work on top of development work. We’re extracting the natural stories that live inside every complex project.

I do have an editorial calendar though, maintained by me manually with no automation or bots helping (yet).

One view of the Building Piper Morgan editorial calendar

The human element

Perhaps most importantly, this approach preserves the human story of building technology. The late-night debugging sessions. The moment when three different AI agents start referring to your system with pronouns because they recognize its intelligence. The satisfaction of choosing investigation over quick fixes.

These moments don’t survive traditional retrospectives. They’re too personal, too immediate, too specific to make it into quarterly summaries.

But they’re exactly what makes technical content compelling and relatable.

The unexpected side effect

The most surprising result? Better development practices. When you know you’ll be writing about your problem-solving process within 24 hours, you become more thoughtful about that process.

You document decisions more carefully. You think more strategically about tradeoffs. You resist quick fixes because you know you’ll have to explain your reasoning while it’s still fresh.

Building in public with just-in-time retrospectives doesn’t just create better content. It creates better thinking.

Looking forward

We’re planning to take this further. Periodic sessions where Piper analyzes her own development logs — not just the technical details, but the qualitative insights about product management in practice.

Imagine an AI system that learns not just from training data, but from real-time documentation of how experienced practitioners solve complex problems. The just-in-time retrospective becomes the training curriculum.

The lesson for everyone else

You don’t need to be building AI to benefit from this approach. Any complex work generates stories worth telling. The key is capturing them before they fade.

Your next retrospective doesn’t have to be a formal quarterly review. It can be tomorrow’s reflection on today’s work, written while the insights are still sharp and the energy is still there.

The best stories aren’t the ones you plan to tell. They’re the ones you live through and capture immediately, before time turns vivid experiences into vague summaries.

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