JUXT

Huge congratulations FoundryOS team for reaching your go-live milestone! We're thrilled that XTDB is a core pillar of your release here, helping to solve the pains of complex KYC audit requirements. (...new XTDB case study coming soon! ✨)

Is there going to be a Vendorpocalypse? It's a question I've been posed a few times now: How will professional services companies survive the coming AI-driven Vendorpocalypse? First, I'm excited for this era. I want that Star Trek utopian future where they had decent AI. I got into software to make things better. Over decades I've seen so many software projects fail, becoming bloated and wasteful in the process. Used well, AI can allow us to reduce waste and bloat, speeding up and derisking development. We can finally end the tyranny of legacy systems that have longer lifespans than most tenured employees. I'm excited for all my connections who are now in a position to make their software estates vastly simpler. But what does this mean for software consultancies? Pure commodity-driven players will have a harder time, no doubt. But I am seeing a stronger need for high-value consultancies, to help clients accelerate and take advantage of AI. We are the yin to the client's yang. We exist on the Darwinian cutting edge of value provision in the outside world. We will always be learning by having the best people doing the most challenging work and taking advantage of what’s new. Roles are changing, be it engineers, product owners or project managers. We're all having to learn again what software development looks like. Companies will need guides. To maintain and increase our value proposition, we consultancies need to specialise further, bringing AI acumen together with industry domain experience and systems-design skills. AI is all about acceleration and we need to be accelerators. So will there be a Vendorpocalypse? For some, yes, it will happen. For the players adding clear value, we can now deliver to our clients on a scale we never previously imagined.

📣 Save the Date – June 18, 2026 XT26 Fintech Conference returns to London for its third year, bringing together Senior Engineers Leaders in banking and financial services. Invite-only. Apply for an invite: juxt.pro/xt26

I've written about three ideas that explain #AI's impact on software engineering better than the #Jevons' Paradox framing that dominates the discourse. #Solow's Paradox explains why returns are unevenly distributed: the technology works but organisational restructuring takes time, so some teams capture value quickly while others see nothing. #Braess's Paradox explains why faster code generation doesn't mean faster delivery: local speedups create congestion elsewhere. And #Bainbridge's Ironies of Automation explain why engineers feel like they're working harder: hand the routine work to agents and every remaining task is a difficult decision. Three explanations at different scales, each revealing what the others miss. Together they point to a way through.  Link in comments. #SoftwareEngineering #AIProductivity #AgenticCoding

Filing cabinets and lightbulbs aren't the obvious route into software engineering. As the year winds down, I've been thinking about my somewhat unconventional path into the industry. At JUXT, we take any in-person get-together as an opportunity for a tech conference, and this includes our Christmas Party. Inspired by our venue (the Quantum Untangled exhibition at the Science Gallery London) I used my talk to share some of my personal story, and the Big Ideas I was wrestling with as an arts undergraduate. Some of the biggest ideas came to me via the books of David Deutsch. For example, his thesis behind The Beginning of Infinity is that the scientific revolution wasn't just a significant cultural moment for humanity; it was a significant moment in the universe itself. Once humans became focused on identifying good explanations, the world entered a period of potentially unbounded progress. Why do we see such polarisation between those who wield AI despite its flaws and those who are fervently anti-AI despite its extraordinary successes? I wonder if it has to do with intuitions about the quality of explanations. Human progress is full of incredibly useful models that turned out to be absolutely wrong: the geocentric model of the universe, for example. Seasoned technical people, especially, have a deep aesthetic objection to anything that seems predicated on flawed explanations. I share some of my own disappointments and concerns about the current state of the AI industry, but above all my excitement that we simply can't know where the next stepping stones will come from. Whether current AI models turn out to be an evolutionary dead-end or the basis of ever more powerful intelligence, we can only connect the dots in hindsight. We didn't know that the technology for making reading glasses would lead to Galileo's telescopes and the end of the geocentric model, or that the valves for amplifying telephone signals would enable the first electronic computers. We're still early, and there will always be problems to solve. As Alan Kay said, the best way to predict the future is to invent it. https://lnkd.in/eM5iiq2S #AI #SoftwareEngineering #Innovation #PhilosophyOfScience #TechTalks

You can listen to the full JUXT Cast episode, with Rob Moffat and Henry Garner, right here: https://lnkd.in/eSmi75Kn