πŸ’¬ Issue #26: Nerds wanted

Demand for software developers outstrips supply, despite AI

Just in time for the weekend, software developers still rule, no one knows how to measure productivity, and Forbes 30 under 30 might be a scam. Happy Friday.

DEMAND BEATS SUPPLY

Brent Hayward, the big kahuna at Salesforce's MuleSoft, is worried that the growth of tech stacks and AI will lead to an engineering shortage, not programmer unemployment. Maybe we should listen to an exec who could benefit directly by replacing people with AI.

"There aren't enough developers in the world," he said. "We've already achieved exit velocity, where the pace of apps and the pace of technology is way outpacing the ability to bring on tech workers."

Yes, AI can chew up the boring bits of work, but it won't replace top-of-their-game developers. As we look to the future, connecting backend integration with modern task workflows is where our star players will be needed most.

ZDNet (5 minutes)

SOFTWARE DEVELOPMENT IS DEAD (NOT)

Hold your horses: the end is NOT nigh for software engineering. Despite what some doom-and-gloom Google searches might suggest, the rise of AI is not the sound of a death knell for our coding comrades, says Anthony Hughs.

And the tech layoffs? Just a bit of corporate housekeeping. Software development is still crowned America's top job, with a six-figure median salary. And the Bureau of Labor Statistics predicts a 26% jump in demand over the next decade.

We're not out to create machines that can code, but machines that can help us code better, Hughs reports. So, relax - software development is here to stay. It's never been just about writing lines of code anyway; it's about crafting creative solutions to increasingly complex problems. And for that, we'll always need a human touch.

Forbes (5 minutes)

WHAT IS DEVELOPER PRODUCTIVITY, ANYWAY?

Here we go again with the tech world's soaring speculations, this time about AI miraculously increasing developer productivity by tenfold. The inconvenient truth? We still can't reliably measure engineering productivity, as astutely noted by tech bros Brent and Geoff Stevens. (Has anyone ever seen them in the same room together? πŸ€”)

AI, despite its potential to automate mundane tasks, is not a magic bullet, especially when it comes to solving complex, multi-domain problems within a specific timeframe.

The bros say it’s crucial we adopt a data-driven approach, establishing baselines and using even rudimentary metrics to measure productivity before and after AI tool implementation. (May we suggest measuring output, not input?)

Techcrunch (6 minutes)

ELSEWHERE ON THE INTERNETS

YESTERYEAR TECH OF THE WEEK

Backup 2-3 of your iPhone Pro photos all at once. Tapes not included.

Until next week, 🫑

- The EiT crew at Status Hero