The Hidden Team Problem That's Killing Your AI Investment
"NASA forgot how to build space shuttles - not in a vague way where they could go and get it out of the library. They actually lost the knowledge," explains AI strategist Nate B Jones. "The teams that built the space shuttle disbanded, documentation got scattered, expertise walked out the door. The real knowledge existed in between, in the collective knowledge of the team."
This startling parallel between NASA's institutional memory failure and today's AI implementation challenges exposes a critical blind spot in how organizations approach artificial intelligence, writes End of Miles.
The Collective Intelligence Gap
Jones argues that our current AI obsession with individual productivity metrics overlooks a fundamental truth about how knowledge truly functions within organizations. The expertise that built humanity's most complex spacecraft didn't reside in any single engineer's mind or even in comprehensive documentation - it existed in the connections between hundreds of teams through thousands of small decisions.
"Everyone's obsessed over AI productivity, prompts, workflows, 10x your output. I've written some of that stuff and I am a big believer in individual productivity gains for AI - it's measurable. But I think we're missing something really big." Nate B Jones
That "something big" is how AI transforms team knowledge systems. While individuals readily adopt AI tools for personal workflows, the AI strategist observes that most organizations simply drop AI into existing team structures and expect magic to happen. It doesn't.
High-Performing Teams Do Something Different
Through extensive observation of various teams implementing AI, Jones has identified a critical divide emerging between high and low performers. The standout teams aren't just using AI individually - they're fundamentally redistributing their cognitive processes.
"The high-performing product teams that I have seen are doing something completely different. They're not just using AI individually, they're fundamentally distributing their cognition from the heads that are on the team now that are human to the AI as well." Jones
These exceptional teams develop specific AI rituals, maintain collective understanding of prompt effectiveness, comprehend evaluation as a unit, and rethink coordination mechanisms that previously required meetings. Most crucially, they operate with the assumption that team knowledge now lives partly in AI systems, not just between humans.
Why This Matters Beyond Productivity
The technology expert frames this challenge as historically unprecedented: "For the first time in human history, our intelligence isn't just living in human heads anymore. Parts of our thinking are starting to live outside our minds." This distributed cognition requires teams to actively manage shared context by deliberately feeding AI key decisions, refined outputs, and curated inputs.
When this collective approach fails, Jones observes increasingly common dysfunction - individuals feel productive creating AI-generated content 10x faster, but the overall work quality deteriorates because the team collaboration framework hasn't evolved. The strategist sees this gap widening as AI models grow more powerful, "supercharging the few teams that know how to use them well" while leaving most organizations behind.
"We're going to consistently underestimate the real potential of AI not because we don't understand the intelligence AI brings to the table, but because we don't understand how to make that intelligence social." Nate B Jones
The parallels to NASA's institutional knowledge loss highlight a critical warning: without reimagining how teams function with AI as collaborative partners rather than just tools, organizations risk losing their fundamental ability to create complex, valuable work - just as NASA lost its capacity to rebuild the very spacecraft that defined American technological prowess.
