Batteries included: how AI will transform the who and how of programming

The 1947 paper titled “Preparation of Problems for EDVAC-Type Machines” talks about the idea and usefulness of a “subroutine”. At the time there were only a tiny number of computers worldwide and subroutines were a novel idea, and it was clear that these subroutines were going to make programmers more productive: “Many operations which are thus excluded from the built-in set are still of sufficiently frequent occurrence to make undesirable the repetition of their coding in detail.”

Looking back it seems amazing that subroutines had to be invented, but at the time programmers wrote literally everything they needed to complete a task. That made programming slow, error-prone and restricted who could be a programmer to a relatively small group of people.

Luckily, things changed.

You can look at the history of computer programming as improvements in programmer productivity and widening the scope of who is a programmer. Think of syntax highlighting, high-level languages, IDEs, libraries and frameworks, APIs, Visual Basic, code completion, refactoring tools, spreadsheets, and so on.

And here we are with things changing again.

The new programmers

The recent arrival of LLMs capable of assisting programmers in writing, debugging and modifying code is yet another step. It’s a step at both making programmers more productive and helping more people be programmers.

As programmers a lot of what we do is arcane.

Sure, we have helped create the modern world, but we spend a lot of time on things that actually exclude many from being programmers. Think of how many times you’ve messed up syntax, misinterpreted the result of calling a function, or made an off-by-one error in a loop.

And we’re expected to operate at a concrete and abstract level simultaneously. We hold the architecture and state of a system in our heads, imagining the program as data flows through it, and worry about a missing semicolon.

This is, frankly, weird.

That weirdness is partly why the children’s programming language Scratch eliminates much of the arcana. It’s designed to stop the user making small mistakes that add up to not making progress on a program. Its on-screen shapes are designed to show how a program flows and loops. What if AI eliminates much of our odd work and lets people concentrate on the thing they are creating?

I think that would be wonderful and would open the world of programming to many, many more people. But we’re not there yet. We’re at the point where AIs are hugely helpful assistants in the traditional art of programming. And this week Cloudflare will introduce its own AI assistants to make programmers using Cloudflare Workers much more productive. And these assistants are going to help more people use the Cloudflare Developer Platform.

The new platforms

A developer platform without AI isn’t going to be much use. It’ll be a bit like a developer platform that can’t do floating point arithmetic, or handle a list of data. We’re going to see every developer platform have AI capability built in because these capabilities will allow developers to make richer experiences for users.

If you’ve used a phone’s picture library recently you’ve probably discovered that you can search by what’s in an image. Type ‘cat’ and you can see all the cat pictures you’ve taken. Image classification like this is an example of the sort of functionality that a developer platform should provide so that a programmer can build a productive and exciting experience for their users.

That’s why this week we’ll be announcing AI features built directly into the Cloudflare Workers platform so that developers have a rich toolset at their disposal. And they’ll be able to train and upload their own models to run on our global network.

AI systems, by their nature, require a lot of data both for training and for executing models. Think giga- to petabytes. And a lot of that data needs to move around. Unlike a database where data might largely be stored and accessed infrequently, AI systems are alive with moving data.

To accommodate that, platforms need to stop treating data as something to lock in developers with. Data needs to be free to move from system to system, from platform to platform, without transfer fees, egress or other nonsense. If we want a world of AI, we need a world of data fluidity. We’ll look this week at how Cloudflare (including our R2) enables that.

I like to think (it has to be!)

As I look back at 40 years of my programming life, I haven’t been this excited about a new technology… ever. That’s because AI is going to be a pervasive change to how programs get written, who writes programs and how all of us interact with software.

In a talk, Andrew Ng called AI “The New Electricity”. Does that seem exaggerated? I don’t think so. Electricity utterly altered work and life for everyone and has become so much part of life that when electricity supplies fail it’s a shock.

AI is going to have a similarly profound effect on the way we live and work, and will be equally pervasive. And AI is already here, not just in the form of ChatGPT and Google Bard, but through machine translation, agents like Siri and Alexa, and a myriad of unseen systems that do something humans can’t do: keep up with the speed of the Internet helping to protect it and us.

And, I predict, AI is going to help people be smarter. That effect has already been seen with the ancient game Go. In 2016, one of the world’s strongest Go players, Lee Sedol, was beaten by AlphaGo and later retired. But something interesting has happened: Go players playing against AI are getting stronger. Humans are learning new strategies and improving.

I think AI has the potential to do that for all of us. And for programmers I think it’ll make us more productive and make more people programmers.

Which makes me wonder what a 2047 paper entitled “Preparation of Programs for NEURAL-Type Machines” will introduce. What new exciting way of programming is there for us to discover in the next few years? What cybernetic ecology will be created that makes the flow of ideas from the brain to silicon so much quicker?

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