Yay, another AI article about all the amazing things it can't do but might one day.

Researchers found that developers with access to Github Copilot completed programming tasks faster, with less experienced developers benefitting more. If the dramatic productivity improvement persists in future studies, it points to a flood of programming talent by supporting “job transitions into software development” and a probable narrowing of the wage difference between software developers and other professionals.

“I believe technologies like Copilot and ChatGPT will democratize the pay structure for software engineers,” says Siva Sivakolunthu, an engineering manager based in Toronto. “More people will be able to code, so the pay gap between engineers and other professions will close.”

When ChatGPT first came out, Sivakolunthu says, he worried about software development devolving into low-wage factory work. But after he used Copilot, he says, he realized that it accelerated development and reduced the tedious bits of writing code. “If it took an hour previously, it now takes 10 minutes,” Sivakolunthu says, then he adds: “But you still need to know how to code.”

We fix the problems that require the "bigger picture" issues where ChatGPT and AI currently fail the hardest. It's engineering management and junior developers that will struggle more than senior devs in AI era, because their skills and knowledge base rely less on understanding context and outliers

Sivakolunthu envisions a broader talent pool entering software development, capitalizing on skills that are well-suited to AI pair programming. He points to the example of a former schoolteacher who is now a software engineer on his team. “He is great at asking questions and structured thinking,” says Sivakolunthu. His colleague’s teaching experience enables him to break problems down and prompt AI with clear instructions, says Sivakolunthu. The resulting productivity boost is so significant that he is now one of the most productive engineers on the team.

In another study, this one by Andres Comparo and Michele Vacarro at the MIT Center for Collective Intelligence in Cambridge, Mass., AI-powered developer tools enabled non-programmers to create websites almost as quickly as programmers. First, the researchers studied the productivity improvements by giving programmers access to Generative AI to write code. Then non-programmers were asked to perform the same tasks using the same AI tools. This is where things got really interesting: The performances of the two groups were so similar that the study indicated that they were not “statistically different.” The authors noted that this may lead to “deskilling,” the process by which skilled labour is eliminated by the introduction of technologies operated by semi- or unskilled workers. The programmers’ jobs could then be performed by people with less skill – and for lower wages.

Lawai thinks of AI as the evolution of programming. A few decades back, an engineer had to write much of the code from scratch on simple text editors, juggling between tools for version control, compiling and documentation. It was time-consuming and error-prone. Then Integrated Development Environments (IDEs) came along, dramatically improving the developer experience by bundling all of these tools. At around the same time, Application Programming Interfaces (APIs) became pervasive; now a developer could simply call an API to send a text message or process a credit-card payment without having to spend months writing code. These innovations changed the shape of global commerce. “Generative AI is a revolution of that nature,” says Lawai.

With generative AI, the barrier to entry will get dramatically lower – and that creates new possibilities. “Business analysts think clearly and write detailed requirements,” says Sivakolunthu. “In the future, AI may convert user stories to code and BAs may evolve to become high-level programmers.” Similarly, product managers would prompt AI to create functional prototypes. It’s

There is more to senior devs than dev skills,” says Lawai. He says he expects senior engineers to become more valuable at the expense of entry-level programmers as AI tools can do the simple stuff that typically gets farmed out to junior developers. This points to a further concentration of compensation and wealth. Sivakolunthu envisions that “the top one per cent of engineers will work on AI and emerging tech that powers everything else.” They will have up to 30 times the impact and will make the most money. “It’s a bit like the billionaires today, where a small number control most of the wealth. In the future, that may also be the case for elite engineers.