Let’s start by being specific. I’m talking about cloud software vendors, not software vendors in general. So this has nothing to do with the recent recoding and release of the entire Adobe suite. That’s a different conversation.
Most cloud software vendors offer a function that is already available within the major cloud services but which is awkward or difficult to configure, non-obvious, or has various pitfalls. Essentially, they provide a framework for your cloud, usually for a specific function.
As we all know, frameworks are designed to offer simplicity and ease of use, but to do that, they often have to roll up or hide a lot of the features you might actually want or display them in a slightly different way.
This is one of the core reasons why frameworks often start out seeming like a brilliant idea but end up a burden. Say a problem seems really hard to solve, and a company comes along and says, “Yes, we’ll do this for you. It’ll make it easier.”
However, as a system matures, you add features and gain complexity, and the overlayed framework or cloud vendor’s system can actually become harder to update, maintain and pay for, than if you’d simply done it directly using the original cloud services.
And I think this is where generative AI coding tools are starting to change things.
AI can now remove a lot of this particular problem. It can provide the initial ease of implementation that frameworks and cloud vendors offer, without necessarily being any harder to edit after implementation.
So you could start off with Azure or AWS, sit down with Claude or whatever AI tool you prefer, and get it to write you a function or feature. It will go off and do that, producing nicely documented code that does what you want.
However, one of the core things people don’t like about AI written code is that, once it had been produced, very rarely would humans go through and work out exactly how it had been done. This made it potentially harder to maintain.
But that’s not really any different from using a vendor’s product or a big framework. You put it in, it does a very fast job initially, but going back and changing anything can be an absolute devil.
However, AI has not only provided that first fast implementation that a vendor or framework would offer, but it also writes a lot of its own documentation. Anyone who’s read one of those monstrous README files that AI code generation tools produce will know what I mean.
More importantly, AI is actually quite good at going back, reviewing what was done previously and making amendments without screwing everything up. And it’s getting better and better at it.
It’s that speed of updating, but also the fact that doing so costs comparatively little compared to paying for a framework, dealing with the risk of nobody maintaining it, or continuing to pay a vendor’s licence costs, that makes AI a genuine advantage for the customer.
So you end up, three or five years down the line, with a system written directly using basic cloud services, which is well documented and which you can change whenever you need to.
If a vendor goes out of business, changes direction or suddenly changes its pricing, you’re suddenly under threat.
There’s also the question of rewriting.
People who have given AI an existing codebase and asked it to recreate it in something else, notably Rust at the moment, will know just how good AI is becoming at doing that.
Compare this with the sheer monumental difficulty of migrating from one framework or vendor to another.
I say this as someone who’s been doing migrations for 30 years.
This is one of the genuine jobs for AI, and I think it’s why, when you’re talking to almost any cloud software vendor, they themselves go on and on about what their own AI functionality gives you.
Because I suspect they’re the ones, more than almost anybody else, facing a genuine threat from AI taking away their particular market.