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People know that enterprise software has never been that fancy, but that enterprise distribution is hard.
The first point is becoming clearer as software gets ever easier to build, but the distribution point means that the "incumbents can use Cursor too" argument should have legs. In other words, having the distribution apparatus built out should give incumbents massive advantage. But the market is obv. not buying that.
Two potential explanations:
1) it's actually becoming less difficult to distribute software and to understand what to build. Biggest story here is @OpenAI as a workflow intent aggregator that can route that intent to the apps/tools best suited to solve the problem in question. If the primary interface becomes an AI system that routes requests to various specialized tools, then distribution increasingly means being the tool that ChatGPT (or whoever wins that aggregation race) chooses to route to.
This advantages the orchestration layer/aggregators of course (see this interesting piece in the Diff for a fun theory there: thediff.co/archive/router…), but also means that startups should have a relative advantage in optimizing everything for this new paradigm/definition of distribution. This is somewhat analogous (with caveats) to how Google partially shifted distribution from being contingent on salespeople and brand ads to SEO/adwords, but even more extreme.
or 2) if you don't buy that, PE firms or these newish AI transformation firms (like Brain Co, GC's Percepta, SaxeCap, Palantir/Scale, Anthropic, etc.) will leverage their reputational capital, AI-native DNA, and/or ownership stakes to leapfrog both AI-native startups and incumbents by building and distributing/deploying tools themselves (the Bain anecdote).
Understanding how distribution dynamics/difficulty are trending feels like it should be very important if you want to have a sophisticated view on how software economics will eventually look, but it's pretty understudied imo. Especially relative to the question of how much easier it is becoming to build product.
1) taken to it's logical conclusion means that @OpenAI (or whoever wins) matches workflow intent to digital services/solutions as effectively as search/social match consumer intent to consumer goods. And that OpenAI/AI more broadly makes the production of digital services as automated/fossil-fueled as the production of physical goods.
If you are building/selling software this means you have two new/more powerful rent seekers than in the past: the aggregators/orchestration layer and the chip/infra layer. This sounds a lot like e-commerce market structure/economics to me. They also pay large rents to aggregators (meta, amazon, google, etc.) and infrastructure layer (manufacturers).
In e-commerce, moats exist in the form of brand, economies of scale (in certain instances), etc. but moats and margins in e-commerce are obviously weaker than moats and margins in enterprise software.
Folks like @cpaik have argued that AI will make the economics of software look more like the economics of media, which is sort of the maximalist take on vibecoding completely eliminating software moats.
But the reality IMO (at least for foreseeable future) will be somewhere closer to e-commerce. Software won't become completely free like a lot of media has, but just selling software will become less lucrative. Some solutions will commoditize significantly, like certain consumer goods did when mass manufacturing and search/direct response ads went live. Some will retain/command more pricing power as a function of true account/data gravity, regulation/compliance, end-to-end workflow complexity etc. (this is probably why you see vertical solutions outperforming).
In any case, I find it harder and harder to argue that the long run equilibrium isn't relatively bleak unless you're an aggregator, vertically integrated operating company (the AI-native opco/AI transformation approach), or NVIDIA.
would love thoughts @matt_slotnick, @sebkrier, @ChairliftCap, @MangotreeA, @huntermmonk , @yrechtman, @BucknSF
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