The Memory Problem Inside Product Teams
We talk endlessly, decide constantly, and record almost nothing—and it’s slowing us down.
These days, every company wants AI to make sense of its chaos.
We live in a world where AI tools pull from emails, chats, meetings, and documents to build a perfect map of how our business processes work and everything we’ve decided.
But most of what matters never makes it into those systems.
I’ve lost count of how many times a meeting has derailed with, “I thought we agreed on this last week.” We all pause—because no one actually remembers. The notes were never written, and the decision was never logged.
More than once, I’ve stopped mid-discussion to ask, “Is anyone taking notes?”
Silence.
So I share my screen, open a Loop page, and start documenting in real time—discussion points, trade-offs, outcomes. Everyone nods. The cycle repeats the next day or week.
We spend hours in meetings, yet very few of those hours turn into written memory.
We’re just speaking into the void. No synthesis. No record. No foresight.
📊 What the research shows
47% of employees spend between 1 and 5 hours a day searching for the information they need. (Cake)
54% of organizations rely on more than five different platforms to document or share knowledge. (Cake)
Even when tools exist, adoption is low—only 45% of employees in large companies use their knowledge management systems. (IDC)
Fragmented information directly reduces efficiency and process quality. (Han van der Aa, AMCIS study)
These numbers confirm what many of us see every day: teams lose time and judgment chasing information that should already be known.
I think better when I write.
Words on a page bring structure to chaos. They turn abstract ideas into something concrete enough to question, refine, and agree on. Clearly written words rarely lose context; they anchor the discussion.
Sometimes, when I want alignment, I’ll ask, “How would you phrase it? I want to capture it in your words.” That small act turns verbal agreement into shared understanding. It forces precision and creates ownership.
Years ago, in a previous role, I asked my team to keep our wiki up to date with priorities, the roadmap, the backlog, data, and key decisions.
It was a small team, which made setting expectations easier. To their credit, they followed through. Whenever someone asked for an update, we shared the wiki link instead of joining another meeting.
It saved us hours and taught others to find information on their own. That documentation became our single source of truth—a living record of our work, reasoning, and progress.
That discipline, though, fades quickly when people move on or when there is a change in leadership. Documentation starts to feel optional again. Context disappears. Teams begin rehashing the same things.
GenAI promises to stitch together information from everywhere.
The reality is that AI can’t synthesize what doesn’t exist. It can summarize, tag, and connect, but it can’t recover lost memory.
Most companies don’t have a reading or writing culture. Conversations live in chat threads, recordings, and hallway talks. Knowledge fragments and eventually vanish.
The real opportunity isn’t more tools, it’s rediscovering the discipline of writing things down. Writing is how teams think together.
AI will help us find and connect the written material. But it can’t fix what we don’t record.
Until we build cultures that value writing as much as talking, we’ll keep losing our most important work to the noise of our own conversations.
This reflection is part of an ongoing series on decision hygiene, knowledge flow, and product culture—how teams think, decide, and remember together.