Andrew Rea with an interesting and increasingly familiar take about how AI will disrupt software-focused private equity:
Distribution and brand moats can protect your legacy products for a while (esp in enterprise) but eventually you get lapped by competitors with better products, service, pricing, etc. Software is too competitive and changes too fast for this model to work in 2024.
I think most of the takes around AI and software (c.f. Chris Paik’s thesis on the same thing) all center around the same few starting lemmata:
- Over the past twenty years, the fixed costs required to build and distribute software have gone down.
- AI purports to accelerate that trend: maybe significantly, maybe in totality. [1]
- Therefore, software qua software as an asset is going to round down to zero over time, and software companies will differentiate themselves on things outside of core functionality.
From there, they diverge into two main camps:
- This trend is good for incumbents, because incumbents have data, brand, process power, and other strategic assets that don’t get rounded down to zero. (I think this conversation between Des Traynor and Patrick O’Shaughnessy is a particularly good articulation of this thesis.)
- This trend is bad for incumbents, because incumbents rely too heavily on customer inertia and revenue capture and are systemically disinclined to innovate at the rate that a disruptor would. (See Andrew’s essay which opened this post.)
I think these conclusions are less contradictory than they appear. It is getting easier to write and deploy software en masse, which makes it harder for established organizations to stay differentiated on functionality alone; but those organizations can now, at least in theory, use and deploy their other assets for more interesting ends, and a lot of the capital expenditure inherent in significant engineering work suddenly becomes much easier to pencil out.
That being said!
I think it is very easy to look at rate of change and the speed and polish with which startups are building impressive bodies of work and...skip to the epilogue, where they’ve triumphed over the incumbents of the world who are more focused on cash flow extraction than customer value creation. The reality is: the number of industries where people are making retention/churn decisions based purely on functionality alone is smaller than you would think at first glance; the strategies deployed by Thoma Bravo et al (aggressive cross-selling, aggressive contract durations, rolling up to drive down unit economics) are already the right ones, insofar as we define “the right ones” as “the ones that maximize long-term enterprise value.”
Whether you’re an incumbent or a new market entrant, it’s very important to think about strategic long-term moat, points of customer acquisition, tail risks, and useful levers: which was also true in 2020, and 2010, and so on.
Any argument otherwise is science fiction: interesting and thought-provoking but rarely useful. (And remember to taste the kool-aid.)
Epistemic disclaimer: I think our distance from “instant, Matter Compiler-style AI-built software products” is so far away from the present that it doesn’t really warrant serious discussion ↩︎
