Why Your Expertise Just Became Your Superpower
How AI turns hard‑won experience into on‑demand solutions and real leverage
We’re living through one of those rare moments when the fundamental rules of how things get built are changing. I recently dove into an a16z Enterprise piece about greenfield strategies for AI startups and their thinking on distribution versus innovation, and it got me thinking about something bigger: we’re not just watching AI disrupt existing markets, we’re witnessing the birth of an entirely new category of problem-solving.
From filing cabinets to AI artifacts
Think about the journey we’ve been on. First, everything was physical: filing cabinets, paper records, manual processes that required human hands to touch every step. Then came digitization, where we scanned those papers with OCR, stored everything in databases, and suddenly could search through archives that would have taken weeks to manually review.
Now we’re in the AI phase, and it’s fundamentally different. AI doesn’t just store and retrieve our digitized information, it reads, understands, and connects dots across all that data to solve actual workflows. It’s not just finding the needle in the haystack; it’s weaving the needle into exactly the thread you need for the specific problem you’re trying to solve.
What fascinates me about this progression is how each stage has democratized access to capabilities that were previously exclusive. Physical filing systems require dedicated staff and physical space. Digital systems need IT departments and database administrators. But AI-powered solutions? They’re starting to respond to natural language descriptions of problems.
The greenfield opportunity hiding in plain sight
The a16z Enterprise article by
and talks about startups using greenfield strategies to capture customers at transition moments, when they’re moving from small startup to large enterprise, for example. These transition points create new needs that existing solutions weren’t designed to handle, opening opportunities for new players to step in.But here’s what I think there may be an even larger opportunity: the biggest greenfield opportunity isn’t just about startups unseating incumbents. It’s about individuals and small teams creating solutions that didn’t exist before because they couldn’t exist before.
I keep coming back to this scenario: you’re a subject matter expert in your field. You understand a problem deeply because you’ve lived it for years, maybe even that hard won 10,000 hours that creates real expertise. Previously, if you wanted to solve that problem with software, you had limited options: find an existing product that kind of fits or invest significant time and resources into a full development cycle. For many smaller problems or highly specific workflows, the juice wasn’t worth the squeeze.
Now there’s a third option: describe your problem to an AI interface and watch it build you an artifact that solves it.
When everyone becomes a builder
This shift is profound because it changes who gets to be a creator of solutions. We all carry around incredibly specific knowledge in our heads, knowledge earned through experience and refined through repetition. Most of this knowledge falls into two categories: stuff everyone knows (like basic geography or common sense about the world around us) and stuff that requires real expertise.
The common knowledge is becoming commoditized by AI, but the specialized knowledge? That’s becoming more valuable than ever. The difference is that now you can take that specialized knowledge and rapidly prototype solutions for those edge cases and specific workflows that previously sat in the “too small to build” category.
I think about this in practical terms all the time. A marketing manager who deeply understands customer segmentation could describe their ideal attribution model and have an interface build them the exact dashboard they need. A product manager who has spent years thinking about feature prioritization could create a custom scoring system that reflects their hard-won insights about what matters.
These aren’t hypothetical future scenarios. They’re starting to happen now, and the pace is only accelerating.
The wisdom premium
Here’s what I find most interesting about this trend: as AI handles more of the routine problem-solving, human wisdom becomes the premium differentiator. There’s a difference between knowledge (which can be learned and increasingly replicated) and wisdom (which comes from lived experience and often can’t be easily articulated).
Some of the most valuable decisions we make aren’t based on logic trees we can trace step by step. They’re based on intuition built from years of seeing patterns, making mistakes, and developing that gut feeling about what works and what doesn’t. This kind of multifaceted, experienced-based insight is exactly what AI can’t replicate but can amplify when combined with the right tools.
Think about it: the ability to quickly spin up solutions means the value shifts to knowing which problems are worth solving and how to solve them in ways that matter to people. That requires the kind of contextual understanding that only comes from being embedded in real workflows and real pain points.
Experienced-based insight (wisdom) is exactly what AI can’t replicate but can amplify when combined with the right tools.
The self-service future
I keep imagining what this looks like when it’s fully developed. You open an interface, describe a problem you’re facing (like how you’d search Google), and after some quick refinement, you get back a working solution. Yes, this exists now, but I’m talking about the simplest bare bones interface you can imagine. Maybe it’s a custom workflow, maybe it’s a purpose-built interface, maybe it’s something we don’t even have words for yet.
The key insight is that this isn’t about replacing existing software. Most of the tools and platforms we use today will continue to be valuable because they solve common, well-understood problems at scale. This is about filling in the gaps, solving the edge cases, addressing the problems that are too specific or too niche for traditional product development cycles.
What excites me most is how this expands the universe of problems that can actually get solved. Right now, there are countless workflow frustrations and process inefficiencies that never get addressed because they’re not quite big enough to justify building a product around, but they’re real enough to cause daily friction for the people who experience them.
In a world where solutions can be created on-demand, those problems suddenly become solvable.
What this means for how we work
This transformation is already changing how I think about product development and business strategy. If your customers can increasingly build solutions themselves, what’s your role as a product company? If individuals can create custom workflows using AI interfaces, how do you compete with infinite customization?
I think the answer lies in understanding that expertise and wisdom become your core differentiators. The companies and individuals who thrive will be those who combine deep domain knowledge with the ability to leverage these new creative tools effectively.
We’re heading toward a world where the barrier to testing ideas and solving specific problems drops dramatically. We’re heading toward a world where everyone can be a creator of solutions, and the most successful creators will be those who combine technical possibility with deep understanding of real human problems.
What problems are you uniquely positioned to solve that you’ve been putting off because they seemed too complex or too niche to tackle? The tools to build those solutions might be closer than you think.