Saanya Ojha, partner at Bain Capital Ventures, painted a vivid picture of how experience is essential to make the most of AI. In her analysis of Cowork, she writes:
“The scarce resource is no longer code - it’s conviction. Knowing which workflows matter, which abstractions users will trust, and where automation crosses the line into discomfort requires context, empathy, and long exposure to a domain.”
This directly mirrors my own experience: Long exposure to a domain.
The narrative around AI and age has been backwards. We’ve been told that AI favors the young: digital natives who grew up with technology, who can adapt quickly, who don’t carry “legacy thinking.”
Turns out the truth is exactly the opposite.
The Half-Life of Unproven Ideas Has Collapsed
Ojha makes a crucial observation about what’s actually changed:
“Product defensibility no longer comes from exclusivity of access or technical difficulty; it comes from sustained, compounding judgment applied at machine speed.”
Sustained, compounding judgment. That’s not what you get from a 27-year-old who’s great at prompting. That’s what you get from someone with direct experience, who’s made every mistake in the book and learned to spot patterns others miss.
When anyone can build anything in days, the bottleneck is knowing what’s worth building in the first place, not execution.
Why Experience Matters More, Not Less
AI doesn’t eliminate the need for judgment, it does increase the cost of poor judgment.
Before AI:
- Bad ideas took months to build
- Resource constraints forced prioritization
- Execution difficulty served as a natural filter
- You had time to course-correct
After AI:
- Bad ideas get built in days
- Everything feels feasible
- No natural constraints force hard choices
- You can waste months chasing the wrong thing at high speed
The person with 20 years of domain expertise looks at a problem and knows:
- Which customer pain points are real vs. imagined
- Which “obvious” solutions have been tried and failed
- Where complexity hides beneath simple surfaces
- When good enough beats perfect
- Who needs to be brought along and why
That pattern recognition is worth more than prompt engineering.
The Real Competition Isn’t Model Labs vs. Startups
Ojha frames the actual race perfectly:
“It’s not model labs vs app companies. It’s everyone vs time. Whoever can iterate fastest with taste wins.”
Iterate fastest with taste.
Speed without judgment is just expensive chaos. A junior team can now ship features at machine speed, then discover six months later they built the wrong thing for the wrong users with the wrong assumptions.
A senior team moves just as fast but in the right direction. They:
- Ask better questions upfront
- Spot second-order consequences
- Know which shortcuts will haunt you vs. smart trade-offs
- Understand how organizations actually adopt new tools
- Recognize which battles are worth fighting
The Window Is Closing
Here’s what should terrify companies making the wrong age-based hiring decisions:
“We’re in a brief window where judgment scales faster than institutions. New workflows are being invented before norms or categories exist. That window never lasts. It closes when interfaces stabilize, institutions catch up, and power reconsolidates around standards, platforms, and defaults.”
The organizations that will dominate the next decade are the ones pairing deep domain expertise with AI tools right now. Not after they’ve “restructured toward younger talent.” Not after they’ve “waited for the technology to mature.”
The window for defining new defaults is measured in months, not years.
What This Means for Experienced Professionals
If you’re over 45 and worried AI makes you obsolete, you’ve been reading the wrong headlines.
Your advantage isn’t what you can code. It’s:
- What you know is worth coding
- What mistakes you can help AI avoid
- What context you bring that no training data contains
- What questions you know to ask before starting
Saanya puts it clearly:
“Early access to and fluency with tools like this will radically increase leverage for a small subset of people.”
Don’t be late to fluency. But understand that fluency without experience is just fast incompetence.
The New Competitive Advantage
The future doesn’t belong to:
- The fastest coders (AI codes)
- The best prompt engineers (everyone learns prompting)
- The most “AI-native” generation (the tech, Claude Code, is three months old)
It belongs to people who combine:
- Deep domain judgment
- Fluency with AI tools
- Authority to act on insights
This is why the most valuable professionals in 2026 won’t be fresh graduates who are “AI-native.” They’ll be 50-year-old domain experts who got fluent with Claude in November.
What to Do About It
If you’re an experienced professional:
- Get fluent, now. Develop working literacy with AI tools.
- Focus on judgment, not speed. Your ability to ask the right question is worth more than generating fast answers.
- Document your pattern recognition. What you know intuitively is what AI needs most but has least access to.
- Push for tools, not replacement. The companies that win will be those that augment senior talent, not sideline it.
If you’re a leader:
- Stop age-biased hiring. The junior prompt engineer is not more valuable than the senior strategist who learns to use Claude.
- Pair experience with tools. Your best returns come from giving your most experienced people the best AI tools.
- Measure judgment, not activity. When AI handles execution, output volume means nothing. Direction is everything.
The Bottom Line
Saanya Ojha’s analysis of Claude Cowork reveals something most coverage missed: “The bottleneck is no longer engineering capacity, but judgment: what to build, how to scope it, and when to ship.”
That bottleneck doesn’t favor youth. It favors experience, as long as that experience comes with tool fluency.
The question isn’t whether AI makes senior professionals obsolete.
The question is whether senior professionals will adopt AI before their organizations make expensive hiring mistakes based on wrong assumptions about who AI actually favors.
The window is open. But as Ojha warns, it won’t stay open long.
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