When Software Becomes Ephemeral: The Death of SaaS As We Know It?
Anthropic's 'Imagine with Claude' hints at software that exists only when you need it and vanishes when you don't
Anthropic slipped something quietly radical into this week’s Sonnet 4.5 release: “Imagine with Claude.” Not another chatbot upgrade. Not incremental performance gains. A research experiment that generates functional interfaces on demand—working software that materialises when you need it and disappears when you don’t.
So I imagined a world where the UI is created for me just-in-time when I need it, begging the question: would software-as-a-service eventually, on some level, be replaced with software-as-needed?
https://www.anthropic.com/news/claude-sonnet-4-5
This is a little glimpse into the future of working with software where UIs are generated on demand when the user needs them, tailored to the specific user task at the time. Software that exists only as long as you need it, then vanishes. Ephemeral by design.
The Middleware That Never Was
Anthropic’s pitch is deceptively simple: instead of writing code to describe a text box, Claude just makes a text box. No React components. No state management. No wrestling with CSS. Just intent to interface, instantly.
But here’s where it gets interesting. Some will point out that Claude Artifacts, Gemini Canvas, and even existing Tools already do this on some level. Fair point. Except there’s a critical problem: determinism.
In the unpredictable world of generative AI, ask twice and you’ll get two different implementations. Perfectly fine for prototyping. Absolutely catastrophic for production software. You can’t run a business on interfaces that might render differently each time you load them.
This appears to be addressed by a library of constrained tools which the AI has access to, allowing it to construct software much faster and more reliably than if you were describing what you want in natural language. Think of it less as freeform code generation and more as an expert system with remarkably good taste, assembling pre-vetted components into reliable patterns.
The AI becomes a compiler, not a creative writer. And that changes everything.
The Salesforce Question
Here’s an interesting thought experiment: would the likes of Salesforce be playing with UI generative frameworks where AI assembles Lightning pages on the fly? It could certainly help keep the low-code momentum going and shorten implementation timelines dramatically.
Imagine: a sales manager describes their pipeline view requirements in plain English. Claude assembles the Lightning page—fields, workflows, reports—in real-time. No Trailhead courses. No consultant retainer. No three-month implementation cycle.
The technical feasibility is almost certainly there. The business implications are thornier.
What Salesforce gains: Acceleration of their low-code promise. Democratisation of customisation. Reduced implementation friction that’s always been a barrier to adoption.
What Salesforce risks: Obsolescence of their professional services ecosystem. Commoditisation of the configuration expertise that forms part of their moat. A fundamental question about what customers are actually paying for.
And Salesforce is just the canary. Any platform built on configuration over code faces the same reckoning.
Software-as-Needed: Not Just Faster, Different
Strip away the hype and what we’re really discussing is a category shift in how software exists.
Traditional SaaS: Persistent applications you subscribe to, learn, maintain, and pay for continuously whether you’re using them or not. Feature bloat is a business model—you’re paying for optionality.
Software-as-Needed: Purpose-built interfaces that exist in response to specific tasks, then gracefully cease. No onboarding. No unused features. No long-term relationship with a vendor.
Consider a practical example: You need to reconcile invoice discrepancies between your accounting system and payment processor.
Today: You open your SaaS accounting platform (which you pay £50/month for), navigate through menus you’ve memorised, export two CSV files, open Excel (another subscription), build a VLOOKUP formula (which you’ll have to remember or Google again next month), manually identify discrepancies, and email the results.
Tomorrow: You describe the problem to Claude. It generates a purpose-built interface—upload forms for both sources, an intelligent diff table that highlights discrepancies, export options, even suggested resolution actions. You use it for 20 minutes. When you’re done, it evaporates. Next month, when you need it again, it reappears—but potentially evolved based on what you actually did last time.
The cost isn’t zero, but it’s not £50/month either. It’s £2 for compute. Or £0 if the AI provider is loss-leading for market share.
Who Wins, Who Loses
Winners:
Anyone building complex, bespoke workflows where existing SaaS is overkill: Legal document assembly. Medical triage interfaces. Educational adaptive content. Niche industry tools with small addressable markets that could never justify traditional software development.
Infrastructure providers: AWS, Google Cloud, and anyone providing the compute and orchestration layer for ephemeral software. They’ll own this the way they own compute today.
Component library creators: The Tailwind and shadcn/ui of the world. Ephemeral software still needs building blocks.
Losers:
Generic SaaS with interchangeable features. If your value proposition is “we have a dashboard with charts,” you’re in immediate danger.
Implementation consultants: When configuration becomes conversational, specialised knowledge becomes less defensible.
Feature-bloated platforms: Paying for 42 capabilities you never use becomes obviously ridiculous when you can summon exactly what you need.
Wild Cards:
Platforms like AWS that provide the infrastructure for this shift, but don’t control the interface layer.
Apple and Google: Do ephemeral apps live in browsers, or do they need new OS primitives? Who controls distribution?
Regulatory bodies: How do you audit software that doesn’t persist? Who’s liable when an ephemeral interface causes financial or medical harm?
The Bit Nobody’s Saying Aloud
Anthropic isn’t trying to build better software. They’re trying to make the concept of “software” as we know it obsolete.
Applications as persistent artefacts you install, learn, update, and maintain? That’s a historical accident of compute scarcity and distribution constraints. We accepted the burden of learning software because we had no choice.
But if interfaces can be generated on-demand, perfectly tailored to immediate needs, why would we tolerate the cognitive overhead of mastering someone else’s abstraction?
This is where it gets uncomfortable for the entire software industry. Ephemeral software doesn’t just threaten SaaS business models—it threatens the very idea that software is a product to be bought and sold. It becomes a utility, like electricity. You don’t have a “relationship” with your power company. You flip a switch, consume what you need, and stop thinking about it.
What You Should Actually Do
If you’re building software: Ask yourself honestly whether your product is a destination or a job-to-be-done. If users come to you because they have to, not because they want to, start experimenting with how your core value could be delivered ephemerally. The build vs. buy calculus is shifting to “build vs. summon.”
If you’re buying software: Start experimenting with AI-generated interfaces now, even if just to understand their failure modes. Spin up Claude Sonnet 4.5 and try “Imagine” yourself. Build something trivial. Then ask: “Could this replace a tool I currently pay for?” If the answer isn’t an immediate “no,” it’s time to rethink your stack.
If you’re investing: Watch for the picks-and-shovels play. The component libraries, the rendering engines, the orchestration layers that make ephemeral software possible. The real money won’t be in ephemeral applications themselves—it’ll be in the infrastructure that makes them reliable, secure, and scalable.
The Honest Limitation
Let’s be clear about what this doesn’t solve yet: trust.
Would you run payroll through a UI that didn’t exist an hour ago? Would you manage patient records in an interface with no audit trail? Would you sign a contract through an ephemeral app with no terms of service?
For software to be truly ephemeral, we need:
Provenance tracking (who generated this interface, from what prompt, at what time?)
Deterministic reproducibility (can this exact interface be recreated if needed?)
Liability frameworks (who’s responsible when ephemeral software fails?)
Security models (how do you pen-test something that doesn’t persist?)
These aren’t small problems. But they’re solvable problems. And the moment they’re solved, the entire SaaS industry has about 18 months before the disruption becomes existential.
What Comes Next
Anthropic is probing. Testing. Seeing what breaks. This is research, not a product launch. But research has a funny way of becoming reality when the economics are undeniable.
The middleware is dying. What replaces it will be strange, powerful, and probably infuriating in entirely new ways. Software that blooms into existence when summoned and evaporates when the job is done.
Whether that’s liberating or dystopian depends largely on who controls the summoning mechanism. But that’s a discussion for the next newsletter.
For now, just know: the era of ephemeral applications may have just begun. And it won’t wait for permission.