Open the content feed of almost any venture capital fund right now and you’ll notice something.
Everyone sounds smart.
Everyone sounds current.
And almost no one sounds different.
That’s not an accident. In fact, it’s the direct result of a tool that every fund now has equal access to, and the predictable thing that happens to a market when a formerly scarce resource suddenly becomes free.
For years, producing competent financial content took real effort. A team, a process, a writer who understood the space well enough not to embarrass the fund. That effort and required investment was itself a kind of filter. Firms that didn’t invest in it simply didn’t publish much, and the firms that did stood out by default, because most of the field was quiet.
AI removed the filter.
Now any fund can generate a fluent, well-structured, plausible-sounding post on any topic in minutes. The bar to produce content has collapsed to nearly zero. And when the cost of producing something falls to zero, the market response is entirely predictable: everyone produces more of it, and the value of any single piece of it falls with the supply.
This is not a controversial economic idea. It is, in fact, an old one, and it explains exactly what’s happening in venture and financial content at large right now.
What’s actually being commoditized
AI has commoditized fluency. Correct grammar, a confident tone, a well-organized argument, the surface texture of expertise. Ten years ago, fluency alone was a mild signal of competence. A poorly written post suggested a fund that didn’t have its act together. Today fluency signals nothing, because the machine produces it by default, whether or not a real idea sits behind it.
What AI has not done, and structurally cannot do, is generate a genuine point of view. A model trained on the aggregate of what’s already been said will, by construction, tend toward the median of what’s already been said. It is extremely good at sounding like consensus. It is not designed to disagree with consensus in a way that’s actually correct, because it has no position in the market, no proprietary deal flow, no scar tissue from a bet that didn’t work, no argument it’s willing to be wrong about in public.
That is precisely the thing your best content used to signal, and it’s the thing that’s now conspicuously absent from most of what’s being published.
The evidence is right there
Look closely at any single venture category, side by side, and the pattern shows up immediately.
We recently mapped the public content of several funds investing in food-tech and alternative protein; a mature, well-funded category with real competition for LP attention. The pattern was there.
Most of the published content across the category was announcement-driven: new cohorts, new partnerships, new portfolio hires. Useful information, but not real arguments. Where content did try to make a broader case, it mostly converged on the same handful of mission statements about sustainability and impact, language that has become so standard across the category it no longer differentiates anyone who uses it.
One piece broke the pattern. A fund published a genuinely structural argument, not a recap of what they’d funded, but a specific claim about why the category’s next phase would be defined by infrastructure rather than novelty, and why that shift required alignment across science, regulation, and capital that most players weren’t yet positioned for. Right or wrong, it was a real position. It reflected a point of view. It was the only piece in the entire category that read like someone had thought something through rather than restated the field’s consensus.
That’s not a coincidence. In a landscape flooded with fluent sameness, the one piece making an actual argument was also the most memorable thing out there that we could find.
Why this raises the value of judgment instead of lowering it
The fear is that AI threatens anyone who makes a living from words. The more accurate read, at least in a market like finance, is closer to the opposite.
When production was expensive, mediocre content could still hold a job, it filled a slot, it satisfied “we should probably be publishing something.” That job no longer exists. Mediocre content is now instantly, structurally worse than free, because free versions of it are everywhere and indistinguishable from it.
What can’t be produced for free is judgment: the ability to read an entire category, notice what’s actually being said versus what only sounds like it’s being said, and construct an argument specific enough that it could only have come from genuine expertise in the position it’s arguing from.
That is a widening gap, not a shrinking one. Every fund that keeps publishing AI-fluent, consensus-shaped content is quietly making the case, by contrast, for the rare fund that publishes something real. The flood doesn’t erase the value of a real point of view. It manufactures the scarcity that makes one valuable in the first place.
What this means in practice
If you run a fund and you’re weighing whether to lean into AI-assisted content production, the honest answer is that speed and fluency were never your differentiator to begin with, and they’re worth even less now that they’re free for everyone. What was always worth paying for, and is now worth more than it’s ever been, is the thing a model can’t manufacture on its own: a specific, defensible, occasionally uncomfortable argument that could only have come from a firm that actually knows something the rest of the category doesn’t, or won’t say.
The firms that understand this early have a real window. Not because the market has changed permanently in their favor, but because most of the field hasn’t noticed the shift yet, and is still competing on a dimension, fluent output, that stopped being scarce the moment everyone got the same tools.
The scarce thing was never the words. It’s whether there’s a real idea behind them.