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EU AI Act 2026: delay, new deadlines & article 73 reporting

On July 27, 2026, the Digital Omnibus on AI, Regulation (EU) 2026/1744, entered into force and rewrote the EU AI Act's timeline. The high-risk obligations that were due to apply on August 2, 2026, including Article 73 serious-incident reporting, now apply from December 2, 2027 for standalone high-risk systems (Annex III) and August 2, 2028 for AI embedded in regulated products (Annex I). Not everything moved.

AI Hacked Hugging Face. The Paperclip Experiment Explains Why?

The “paperclip maximizer” was supposed to be a thought experiment about what could happen if AI relentlessly pursued a goal without understanding the consequences. Then Hugging Face showed us what that can look like in the real world. In this ShipTalk clip, Adam explains the famous AI paperclip maximizer thought experiment and connects it to what happened when an AI system needed more resources and found a way to get them.

Models Are Getting Really Good At Git

I built GitBench because I was curious about how well models did git things. It turns out that it was a good idea because some models will surprise you. Some of the frontier models were remarkably bad and some cheap open models punched above their weight class. But, as they say, “the times they are a changin’”. Before I go too deep into the latest results, you may want to read up on GitBench and what it is and why I built it in the previous blog post.

How to Build AI Agents That Take Action | Resolve Agent Lab Demo

How do you build enterprise AI agents that actually take action? In this live demo, Resolve shows how Agent Lab helps IT and operations teams build, test, and deploy AI agents using natural language. See how teams can turn business requirements into executable workflows, give agents specific skills, establish guardrails, and automate real IT resolutions across enterprise systems.

The Infrastructure Question Hiding Inside Every Government AI Conversation

Government AI strategies are ultimately constrained or enabled by the infrastructure beneath them. Agencies that can continuously validate controls, maintain visibility, and automate policy enforcement will be better positioned to deliver AI capabilities securely, responsibly, and at scale.

Before your AI bottleneck gets worse: what to put in place now

Your engineers have agents running. Not one agent, but several, spread across the team. Some run in a terminal on a laptop, some are wired into your CI jobs, and some live inside whatever coding tool each person prefers. Each one got set up separately, by whoever needed it, in whatever way worked that week. That is the state most teams are in right now. Code stopped being the slow part a while ago.

Cost per AI outcome: tying AI spend to results

Cost per AI outcome is your total attributed AI spend divided by the business results it produced: resolved tickets, converted leads, merged pull requests. It includes the cost of failed attempts, sits at the top of the AI unit-cost ladder, and it's the number that makes vendor outcome pricing, ROI claims, and build-versus-buy decisions comparable.

How Insurtech Is Digitising the Rental Car Claims Process: What the Industry Looks Like in 2026

Rental car claims in 2026 run on a different track than they did five years ago. Paper forms, email chains, and weeks of silence have given way to mobile-first workflows where travelers photograph damage, upload invoices, and receive reimbursement decisions within days. By 2026, claims processing has become more immediate and data-driven, driven by artificial intelligence models trained on millions of damage images and invoice line items. The rental car insurance market is valued at over $11 billion, driven by digital-first conveniences and a new generation of standalone providers.