Microsoft's GitHub source shack is reporting a 50 percent error rate on repository content downloads. GitHub Copilot is also "experiencing degraded availability." The problems began at 1340 UTC, when the company's status page reported "impacted performance for some GitHub services." This rapidly escalated to degraded performance across numerous services, including Issues – which was, appropriately enough, experiencing an issue of its own. GitHub is investigating and has promised an update, but today's incident is only the latest in a string of disruptions that have left developer nerves frayed. Earlier in August, GitHub's Actions automation platform and Pages hosting service experienced problems. In its May 2026 availability report, the company acknowledged that AI-assisted coding and agentic workflows were adding to the strain. GitHub parent Microsoft boasted last year that AI was writing as much as 30 percent of the code in some of its repositories, subject to human review, according to CEO Satya Nadella. Addressing GitHub's repeated outages in June, software engineering SVP Jakub Oleksy said structural changes were afoot to "permanently remove failure modes." "We acknowledge that we have work to do, but we're committed to getting it done and making GitHub reliable when and where you need it." Brave words, but today's disruption demonstrates that there is still plenty of work to do – and each recurrence further tests developer confidence in the service. Unsurprisingly, developers took to social media to vent their frustration as Monday Mondayed even harder thanks to the issues. One posted, "Github down again, abou[t] as surprising as the sun rising." Another was more plaintive: "Github is really falling apart. Can we stop being down please... We got work to do." The cause remains unknown, but GitHub's disruptions are stacking up, leaving developers to count the idle hours and consider alternatives. "Maybe," pondered one developer, "the AI code submissions are too massive for them servers." Maybe they are. ®

The cost of agentic AI workflows is forecast to increase more than fivefold by the end of 2028 as users adopt more complex applications of the technology. As Nvidia and other tech giants push inference and agentic AI as the next stage of the AI wave, Gartner warns that the cost of implementing these systems will rise even as foundation models become cheaper. The analyst firm has cast its eye over the nascent world of AI agents – systems designed to act independently in pursuit of a goal – and sees multiple challenges ahead. Leaving aside the substantial security concerns, these software agents are considerably more complex than chatbots. Gartner believes falling model prices are tempting users to build more complex workflows, whose greater token consumption can outweigh those savings and drive up overall inference costs. In other words, tokens are becoming more cost-efficient, but those savings are not keeping pace with the rising cost of more advanced AI capabilities. The rate of innovation is outpacing the cost curve, Gartner claims. "The harsh economics of the inference paradox are exemplified by the differences between a simple chatbot and an AI agent," says Gartner senior director analyst Will Sommer. "Where a simple chatbot must read and interpret a query and quickly respond with a probabilistic reasonable answer, an AI agent must constantly reason, negotiate, and question itself," he explains. Those processes add up: routing a task to an agentic reasoning model increases inference costs at least fivefold, and potentially by much more as the task becomes more complex. Securing a return on investment from such advanced AI tools therefore demands either much greater returns than basic models provide or better optimization of inference, routing, and orchestration, Gartner warns. This could mean assigning each task to the most cost-efficient model capable of handling it. The move by some AI providers from flat-rate subscriptions to usage-based billing hasn't helped, as The Register reported last month. Token-heavy workflows can produce runaway costs under the new model. Perhaps it is no wonder Gartner predicted earlier this year that 40 percent of organizations would demote or decommission AI agents because of problems with the heavily hyped technology. The analyst biz also cheerily forecast last year that at least half of all generative AI projects would blow their budgets because of poor architectural choices and a lack of expertise, while most attempts to build custom models would be abandoned. ®

Microsoft will retire Excel's COPILOT() function on September 14, barely a year after its preview debut. Introduced in August 2025, initially for Beta Channel users with a Microsoft 365 Copilot license and later for Excel for the web users through the Frontier program, the COPILOT() function let users send instructions to the company's AI assistant directly from a worksheet cell. Microsoft has now decided the Copilot side pane should be enough for anyone. Beginning September 14, 2026, the COPILOT() function will no longer be available. Microsoft had planned to make the function generally available in 2027. It has now updated the Microsoft 365 roadmap to say: "We have decided not to move forward with this feature. We apologize for the inconvenience." According to a Microsoft 365 Message Center post, "this change helps streamline the Copilot experience within Excel while continuing to provide AI assistance through a supported interface." "Customers can continue using Copilot in Excel through the Copilot side pane, which provides many of the same AI-powered capabilities, including summarizing text, classifying data, generating content, and retrieving information from the web." Since the function remained in preview, spreadsheet wranglers should not have relied on it in production workflows. Anyone who did now has some formulas to replace. In its original announcement, Microsoft wrote: "Its output should be reviewed and validated for accuracy, especially for critical business decisions or reports." Hardly music to the ears of spreadsheet users, for whom accuracy tends to matter, but par for the course with AI services. Microsoft has spent recent months trying to make Copilot behave more consistently across its productivity applications. It has also responded to some user feedback – the Dynamic Action Button can, for example, be banished to the toolbar rather than left floating atop the content. With similar capabilities remaining in the side pane, Microsoft evidently decided that a dedicated worksheet function was surplus to requirements. Google Sheets still offers a similar AI function. The search giant announced the feature in June 2025. ®

UK supermarket giant Sainsbury's temporarily suspended live facial recognition (LFR) at one of its stores after staff wrongly ejected a shopper in response to an alert – the second such incident this year. Matt Arnold, 46, was ejected from the chain's store in East Dulwich, London, on August 6 after staff responding to a Facewatch LFR alert apparently mistook him for a suspected thief. The comedy promoter told the BBC that he was using a self-service checkout and called an assistant over to approve an alcohol purchase. Instead, two Sainsbury's managers approached him, refused to serve him, and linked him to an incident earlier that week. Arnold said he was told that the store's LFR system had identified him in connection with a previous offense before he was escorted from the premises. "They came over and said I had to leave," Arnold told the broadcaster. "The staff member said I'd been identified by the AI, and the cameras had flagged me. "A shoplifter does not walk around with that much shopping, they don't scan it through, they don't put their Nectar card through. "But what upset me was thinking this is what the future could be – people just listen to what the machine tells them to do without thinking about the consequences." Sainsbury's told The Register that the mistaken ejection resulted from human error rather than a false match by the Facewatch system. A spokesperson said: "We have contacted Mr Arnold to apologise for his experience at our Dulwich superstore. "The incident was caused by human error, not the facial recognition technology. Customers can be reassured that the Facewatch system has a 99.98 percent accuracy rate, and every match is reviewed by a trained manager." A Facewatch spokesperson likewise said: "We can confirm that our live facial recognition technology was not at fault in this incident. A correct alert was sent to the retailer, but was subsequently subject to human error in the way it was handled and communicated by the retailer." We asked Sainsbury's what exactly the human error was in this case, but it did not reply. The Register understands, however, that Arnold's ejection was similar to that of Warren Rajah, who was wrongly removed from the chain's Elephant and Castle store earlier this year. As in Arnold's case, Sainsbury's maintained that the Facewatch system had worked as intended. Regarding Rajah, the supermarket said the system correctly identified someone linked to a previous theft, but staff responding to the alert approached the wrong person. Rajah said at the time that he was approached by three store managers holding smartphones. They looked at the screen, then at him, told him to leave, and pointed to an LFR flyer posted up near the store's entrance. Arnold told the BBC that, as he left the store, he looked behind him and saw what he believed was a security alert displaying his face inside a red circle. Sainsbury's temporarily suspended LFR alerts at the store while it reviewed its internal processes and considered additional staff training. Facewatch said: "When we suspend a retailer from our system, this is a precautionary measure that prevents the store from receiving further alerts while the retailer reviews its use of the system and undertakes appropriate actions, including further colleague training where necessary." Sainsbury's announced a major expansion of its LFR deployment last month, confirming plans to install the technology in up to 200 stores by the end of the year in an effort to tackle shoplifting. The technology currently operates in 55 stores, and the supermarket claims that 90 percent of people identified through the system do not return. Despite Facewatch's oft-touted 99.98 percent accuracy figure, other wrongful interventions involving the technology have been reported at UK retailers. Retailers using the technology include B&M, Budgens, Costcutter, Iceland, Southern Co-op, Spar, and Sports Direct. ®