Modeling software after SaaS

Software will be bigger, more complex, and lower margin

Last week I wrote about the big SaaS sell-off in public markets and the doom it might spell for pure application software companies. My central claim is that AI undermines the three historic pillars of software businesses:

1. Zero marginal cost of reproduction (same code, infinite users). Inference introduces real CoGS.

2. Non-ephemeral value (software doesn’t depreciate like media, so you keep selling across time). Shorter lifetimes as tooling improves faster.

3. High switching costs (mission-critical or highly differentiated products drive retention and willingness to pay). Software becomes less differentiated/easier to replicate, and easier to switch between when it’s an agent not a person using it.

So even if SaaS isn’t dead (and again, it’s not and the public names won’t all get wiped despite the correction), the economics are getting permanently worse. Every line of the income statement gets hit.

The threat to software is not demand destruction. It’s inference costs, competition, and commodification. There will be some marginal TAM compression from seat-based pricing erosion and homebrewed software. But the biggest source of pain will be the contribution margin challenges posed by less efficient S&M (owing to both competition and channel decay), inference (baseline assumptions should no longer be zero CoGS), and shorter LTVs (easier to swap out tools when they become agent end points).

It’s not all doom and gloom. I remain very enthusiastic about the potential to decommodify software to drive high switching costs and earn high margins even if pure SaaS has a challenging future. And more optimistically, as software can do more, the end markets will get much bigger.

The big trade in software will be size for simplicity.

You can get into bigger TAMs with larger contracts if you can tolerate more complex operating models, higher cost structure, and lower margins. Scaled, successful software companies won’t default to pure SaaS but they will be bigger and throw off more cash (in absolute terms) than the prior generation.

You can also run a bootstrapped or vibe-coded software business very profitably on a per-employee basis but likely not at scale. This is the other side of the trade: cash flow for size instead of size for margin. Numerous, easy to start, usually not very big, little or no need for outside capital at inception. A perfectly valid path that looks more like a traditional small services business or consultancy in terms of earnings and terminal value.

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Vertical AI / BPO Replacement (from VSaaS)

The bull case for vertical AI is basically the BPO replacement trade whereby you can earn your way into much bigger TAMs/contracts because you sell into a services/headcount line rather than a software line item.

Slow port cos Phoebe, Superdial, and Ando are doing this really well by building toward a combination of nfx and high liability workflows. Each starts/started with high liability “single player” workflows that open up opportunities to get into two sided businesses that are hard to dislodge or replicate. That’s a key feature of this upside case: doing something valuable out of the box to earn access and build defensibility over time. Remember, startups almost definitionally can’t have moats early or they couldn’t start themselves!

But more broadly, vertical AI is an undifferentiated business in its default state. You have little pricing power because you’re selling commodity labor replacement and replicable code. Not a lot of long-term margin in that unless you can command higher prices through leverage elsewhere in the business.

This is probably the most challenging/tenuous option because this will be the easiest to compete with on a pure (vibe) code basis. Without some combination of NFX or “sin-eating” (doing something dirty/risky/liability generating that people want off their hands), you will trend to look more like the SaaS bear case from last week.

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Services to differentiate software (forward deployment)

The forward-deployed model uses services as a loss leader to earn the right to bigger, longer-term software contracts. You don’t really make money on the services even if there’s revenue in it for you.

The point of forward deploying (often but not always engineers) will be unlocking/earning bigger and more retentive contracts at high margins (even if still a bit lower than today’s baseline because of inference). It’s reasonable to think of this as re-allocated, margin-generating marketing for the software business. And because you’re selling something clearer (”we’ll do the thing for you and it’ll work”) and you’re ultimately responsible for success, not them, the sales cycle is more efficient per dollar of revenue even though it’s consultative.

There’s some financial juggling in these businesses where product and sales headcount functionally gets reallocated into CoGS (note: Palantir doesn’t report this way and instead pushes CoGS into G&A and R&D). But the net effect is higher ACVs, higher LTVs, and a bigger albeit more complicated business.

In aggregate the business earns better because the services piece creates switching costs and value to customers that pure software can’t.

And of course the bear case here is that you just wind up as a consulting company doing custom work with no repeatability, no long-term contracts, and no real durable enterprise value. This is a big risk right now in the diffusion trade (hiring AI researchers to do custom work and calling it a lab).

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Vertically Integrated Services (software differentiating services)

This is the inverse of the FDE model. You start with a services business and invest heavily in software to make the services line more profitable. Easy to say and hard to do.

The baseline is a services company with low gross and net margins. If you can build a product/product org that radically transforms the margins, you can bear that new corporate cost, afford to aggressively invest in growth, and own all the upside from this transformed P&L. GM expansion is the main thing and requires you to fundamentally be a product company.

You can build these companies either organically (from zero) or inorganically through acquisitive means, a growth buyout (GBO) where you buy services companies and transform them with software while owning the upside. The inorganic version may ultimately look the same at steady state/scale but with more balance sheet complexity along the way (debt to borrow and service, integration, etc.).

Here the bear case is simply that you fail to pull off the economic transformation. The best way to mitigate that risk is by building product first, in both the organic and inorganic case. Jumping straight to providing services before you can do it in a differentiated way is a capital intensive way to own an undifferentiated asset you have to run forever.

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Other options

Left unexplored here is the hardware + software model that creates margin and differentiation through supply chain, physical switching costs, proprietary data via sensors and devices. It’s very much in vogue right now as investors look for the downside and durability of industrials with the upside of software. That’s basically the entirety of American dynamism: defense, industrials, robotics. Claude is not going to go start building houses or tractors.

There’s also a whole host of companies that will also have radically different income statements by investing preposterous sums in data centers and/or foundation models. The foundation model companies exemplify the size for simplicity trade by being bigger than we thought possible but very obviously lower margin, especially when you factor training into CoGS, which you obviously should since the models depreciate so quickly.

I’m not specifically modeling NFX here either because that’s a feature of many businesses, not a business model or company structure unto itself. You can/will see network effects in each of the types above (including hardware and AI capex companies).

What else do you think I might be missing?

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Conclusion

The SaaS era trained everyone to value simplicity; SaaS was “the best business ever conceived” in no small part because it felt/was so easy to model and understand. Zero marginal cost, high margins, retentive revenue, clean P&Ls. The next era of (application) software, as the code itself commoditizes, rewards the opposite trade. The biggest opportunities belong to companies that decommodify their code to access TAMs and ACVs that pure software never could.

Software will be more important over the next decade than it’s been over the last: cheaper to produce, more powerful to use, responsible for orchestrating and accelerating more GDP.

The income statements will look “worse” by SaaS standards and better by every other standard. The software companies that succeed in this brave new world won’t be pure application software and they certainly won’t be traditional SaaS. But they will be bigger and throw off huge amounts of cash to their shareholders... at permanently lower margins.