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The unit economics of SaaS create a predictable organizational structure: ARR compounds through new bookings and net retention, so companies optimize ruthlessly around those metrics. This means the roadmap becomes a sales tool—every feature maps to a deal or a churn save. The best orgs maintain product integrity while doing this. The median org ships the top 10 feature requests from their biggest customers and calls it a strategy. From Ben Thompson's excellent interview with Bret Taylor:

Broadly speaking, sales and marketing matter a lot in enterprise software companies and tend to be the gravitational center... Because at the end of the day, annual recurring revenue is an annuity, it throws off cash every year, you basically need to add to that annuity by signing new recurring revenue contracts or adding to them, and you subtract attrition. That's just how software as a service works.

With that, when you stop growing, the business model breaks down. That's where things like the Rule of 40 come from, where your growth rate and your EBITDA margin sort of need to be in lockstep. You can grow very profitable with that business, when you stop growing, no one wants to work at one of those companies.

As a consequence, you end up with a really customer-centric, go-to-market-centric orientation, and product serves that. The best enterprise software companies, that voice of the customer dictates their product roadmap, and they can really meet that demand.

The worst ones stop innovating on the product and hold your feet over the fire in the sales process. Depending your level of cynicism, all enterprise software companies have been guilty of each at different points.

Another interesting thing about this is how the business model shapes culture. When you're growing 80%, product can lead and sales follows. When you're at 15%, sales leads and product follows. It's hard—the companies that stay interesting are the ones that maintain product velocity even as they scale GTM.

I used to think network effects would win out, and we'd end up with just one or two stables, but I don't believe that anymore. Cross chain swaps are getting more efficient by the day, as is intra-chain inter-stablecoin swapping. In a year or two, I think many intermediaries in crypto will just show your deposits as generic "dollars" or "dollar tokens" (rather than USDC or USDT) and they'll guarantee you redeemability in a stablecoin of your choice.

Already we are seeing this with a lot of the fintechs and neobanks that are product rather than crypto first. They care most about UX and would rather offer clients the best experience instead of honoring crypto traditions. So they just show your balance in USD and manage the reserves on the back end.

2026 will be a pivotal year for the widespread integration of AI into the economy:

• Models will be able to autonomously work for full days (8 working hours) by mid-2026.
• At least one model will match the performance of human experts across many industries before the end of 2026.
• By the end of 2027, models will frequently outperform experts on many tasks.

Early GDPval results show that models can already take on some repetitive, well-specified tasks faster and at lower cost than experts. However, most jobs are more than just a collection of tasks that can be written down. GDPval highlights where AI can handle routine tasks so people can spend more time on the creative, judgment-heavy parts of work. When AI complements workers in this way it can translate into significant economic growth.