Technical Deflation

The is a great point that wasn't included in the original article. Thank you.

In general, we should focus more on what endures over what changes. Focus less on the times and more on the eternities. People very often drown in the noise of passing fads and fashions and ephemeral tech. Can you become really skilled at using some piece of tech? Sure. Is it worth becoming really skilled? It depends on the circumstances and the particular person, but in most cases, probably not. It usually is a waste of time (but given the kinds of SFVs that people publish or hobbies people have, people are generally quite good at frittering away their lives on stupid shit).

Incidentally, this is how you can distinguish between a good CS curriculum from a bad one. A good one focuses heavily on principles; the particular technical trappings are mostly just a medium, like Latin used to be in academia, now replaced by English. You pick up what you need to do to the job.

As someone building AI infrastructure, this deflation idea shows up very differently for us. Application founders can afford to say they will wait for the next model, but infrastructure founders cannot. The value we create is not in shipping features faster. It is in absorbing the volatility that sits underneath the entire AI stack.

Models keep getting cheaper and more capable every few months. However, the underlying compute economics do not deflate at the same rate. GPU provisioning, inference orchestration, bandwidth constraints, latency guarantees, regulatory requirements, and failure handling do not become magically simple because a new model improved its reasoning. In reality, each improvement on the model side increases pressure on the infrastructure side. Bigger context windows, heavier memory footprints, more parallel requests, and more complex agentic workflows all increase the operational burden.

For infrastructure teams, waiting does not help. The surface area of what needs to be built only grows. You cannot delay autoscaling, observability, scheduling, routing, or privacy guarantees. Applications will always demand more from the infrastructure, and they will expect it to feel like a commodity.

My view is that technical deflation applies much more to application startups than to infrastructure startups. App founders can benefit from waiting. Infra founders have to build now because every model improvement instantly becomes a new expectation that the infra must support. The baseline keeps rising.

The real moat in the next era is not the speed of feature development. It is the ability of your infrastructure to absorb the increasing chaos of more capable models while keeping the experience simple and predictable for the user

I take great pride in my role as a user of HN. This includes never reading the article and always positing very opinionated tasks without qualification.

You're forgetting what people do if deflation is expected to continue indefinitely, and can also expect for their notes to be written off: They stick that extra money under the mattress.

This is basically what a bunch of people did during and following the Great Depression. Deflation was continuing and the money they had lent to the banks was being written off in bank defaults. And so an entire generation learned to just stick it under the mattress (or stick it in T bills, which reliably didn't default).

Also, it's not just a literal increase of money that causes inflation, an increase in money velocity also increases inflation. Debt write-offs decrease velocity, while debt issuance increases velocity. IANAE.