These days, you can't scroll a page on any social platform without someone saying that, "Claude Code just killed X", "Clawdbot just killed Y", or some such thing.
Meanwhile, Dario Amodei, the CEO of Anthropic, can't stop grabbing a mic anywhere he goes only to say how the concentration of power in the AI industry and the fact that most software engineering jobs will be gone in the next 12-18 months are making his stomach churn.
Buddy... if it's making you that uncomfortable, just stop releasing new models.
"Please make somebody stop us before it's too late...," appears to be the predominant sentiment that AI company execs are leaking right now through their media appearances and lengthy X posts. Is that to maintain plausible deniability when things really go sideways? Maybe.
Jokes aside, if you're experimenting with frontier AI models, you've probably felt that underneath all the hand-wringing and click-baiting, there's a kernel of truth.
What is the "post-software era"?
Until recently, making software used to be a hard, time-consuming, and expensive prospect. In addition, there used to be a wide but stable scale of value x quality, depending on the skill, experience, and location of the engineering talent you needed to hire to build the product.
That equilibrium was obliterated when newer AI models started shipping with 1M token context windows and enough training data to reproduce code in any language across the stack. Most engineers that I know are using these tools and have a love/hate relationship with them. It's like watching a surgeon wield a scalpel they know can fold inward at them at any moment.
A bigger issue is what non-engineers are doing. Anyone who ever had any entrepreneurial aspirations (including me) is out there setting up terminal coding agents, IDEs, GitHub, issue trackers, developer accounts, and shipping working products off into the world.
Marc Andreessen saying that "software is eating the world" was a moment. That was the era of software. And that era is now over. Software ate too much and is now throwing up... software. The post-software era means a time when the ability to develop functional software is commoditized to an extent that it completely loses its differentiation and market value.
How screwed is SaaS?
As someone who went from taking 2 weeks to write the C code for a CS50 assignment to building an iOS task management app using Swift, a working Chrome extension, and a browser-based game with 8K lines of code—my personal opinion is that SaaS is very screwed.
Take this post for example. In the pre-GenAI era, I would've written it in WordPress. Now, I'm writing this in a markdown editor on my desktop, which will push a commit to GitHub, auto-deploy on Cloudflare, and render on a custom-built site. Running this stack costs me $0 and is well beyond my, let's say—"standard skillset."
Even if SaaS is screwed, the screwing will not be uniformly distributed.
Winners and losers
Winners:
- Selling proprietary data that can't be "generated"
- Craft-obsessed with a loyal following, e.g., Linear, 37signals, PostHog
- Solving foundational AI problems, e.g., Cohere, Blackboard.io
- Using AI to solve foundational problems, e.g., Simile AI, Evidenza
- Enterprises operating on trust, scale, and reliability, e.g., Shopify, Stripe
Losers:
- Anyone whose product is just a UI bolted on open-market LLM APIs
- Any late lookalike in a category, e.g., a Replit or Lovable alternative
- Any product whose only distinguishable moat is being software
If software isn't the edge, what is?
Novelty of ideas
This is the true Achilles' heel for generative AI. It can execute great ideas with speed, but you'll have to supply the idea. This is implicit in how token prediction works. All you get is a regurgitation of ideas already in its training corpus. You can't get an original tune by remixing.
Speed-to-market
The entire premise of AI coding is unlocking 10x speed. If you're not running a multi-agent RLHF loop in a Docker container overnight... you're falling behind. Or at least this is what I'm sensing based on what people keep posting on LinkedIn and X. There are a lot of ways to die in SaaS, and moving too slow with a great idea is just one.
Proximity to capital
AI has nothing on good ol' money. Because SaaS is being downgraded to a lower expected-value bet, institutional capital will flow asymmetrically to the top of the food chain. Think unicorn ex-founders, YC startups, AI model trainers, etc. Startups are now announcing >$100M seeds. Do you know how long they can just... survive?
Being opinionated
Having strong opinions shaped by your personal experience, quirks, and idiosyncrasies can inject differentiation in crowded categories. A lot of founders are pulling this off, but Adam Robinson of RB2B is the first that comes to mind. He's thrown every decorum rule in SaaS out the window and been rewarded for it.
Positioning savvy
Building and positioning software are wildly different disciplines. Just like you wouldn't want a positioning expert to write code for you, don't let whatever Dave felt like writing that one morning become the official messaging for your product. Great positioning is about making your offering undeniable. It's not a job for a committee.