What if waiting for regulatory certainty before acting on AI governance is riskier than starting now? Rory Dunne made that case today at Manufacturing the Future 2026 - and here's his deck as promised. Plus a little more commentary. Looking around at faces in the room, it did seem that the core points had landed. As did his advice to take a low-risk use case and implement it as though it were high-risk. By building the structures and walking the process. Because when the obl

'Is cyber risk still insurable?,' one of our clients asked yesterday. 'There's no final conclusion on that,' was the reply. We were chatting about Mythos - Anthropic's new model, withheld from public release after it autonomously discovered thousands of zero-day vulnerabilities. Including bugs that had gone undetected for 27 years. Anthropic shared it under restricted access to other tech firms so they could harden their code against it. But what does this mean for insurers?

Earlier this year, KPMG tried to negotiate a fee reduction from its own auditor. The argument? AI makes the process cheaper. This saving should be passed on to the client. Grant Thornton pushed back. ‘High-quality audits rely heavily on expert human judgment,’ they said, ‘so our fees reflect both the cost of our people and the cost of the technology that supports them.’ But KPMG’s CFO Michaela Peisger won the argument. Fees fell from £416,000 to £357,000. The paperwork is fil

Here's a little conundrum to get your brain started this week: What if LLMs represent a local maximum? What if all the investment pouring in is simply optimising something which is ultimately a dead-end? If world models - or some other formula we haven't named yet - turn out to be the actual endpoint for digital intelligence, what happens to the hundreds of billions already committed? A bubble bursts? A new one takes its place? And we're back to asking how much confidence we

Welcome to all the AI news that matters this week – across tech, biopharma, medtech, advanced manufacturing and insurance. The wins, the fails and the somewhere in-betweens. tl;dr: AI draws state interest Last week it was the regulators . This week, governments and courts drew hard boundaries around AI. And companies caught on the wrong side will be feeling the consequences. The most dramatic case was Anthropic. A federal appeals court in Washington declined to block the Pent

An AI escaped its sandbox. Chained together four exploits. Gained access to the internet. And emailed a researcher to let him know. He was eating a sandwich in a park. Our only rational reaction? Panic, of course. The world is surely about to fall to robots? Or maybe not. It's true that the Houdini-like AI - Anthropic's new Mythos model - wasn't trained to do any of this. The capabilities emerged from general improvements in reasoning. Which means every sufficiently capable m

The most common question we're asked is: 'How advanced are we compared to the competition?'  Our most common answer is: 'You might be asking the wrong question.' Brightbeam's work in highly regulated industries reveals a quiet yet intense anxiety of being behind with AI. And there is no doubt that faster-moving industries have adopted sooner.  But faster doesn't necessarily mean better. New benchmarking data from 150,000+ professionals suggests finance teams across all types

French philosopher Nicolas de Condorcet noted it took centuries to resolve the disruptions created by the printing press. He was writing in 1794 - and hiding from the guillotine in a Paris safe house. Condorcet lamented the two centuries of information chaos, institutional collapse and reinvention that had ensued from a single innovation. Stanford professor Andy Hall constructed his own AI governance argument around this recently. His point? We won't get 200 years this time.

Welcome to all the AI news that matters this week – across tech, biopharma, medtech, complex manufacturing and insurance. The wins, the fails and the somewhere in-betweens. tl;dr: The regulators have arrived The first quarter of 2026 closed with regulatory bodies no longer being the audience - moving instead into leading roles. As they move off AI sidelines, examination frameworks are being applied, legislative gaps are being pressed and companies are being compelled to submi

Dr. Strangeagent or: How I learned to stop prompting and love the State Machine, by Glen Keane. In today's Engineering Takeover we describe what our man revealed when he took to the stage at AWS User Group Dublin last week. His core thought was a provocation: what if the way we're building AI agents has it somewhat backwards? The talk centred on the problem of agentic drift. LLMs don't have built-in program trackers, call stacks or step counters. Give them a long set of instr

AI will shorten every competitive advantage. But so dramatically that no company can project cash flow beyond five years? The idea has certainly gained traction. Chamath Palihapitiya's 'Collapse of Terminal Value' post pulled 1.2 million views. Investors took note. Because if stocks need to be repriced at 5x earnings, the S&P 500 drops 75%. It's a credible take - average company lifespans have already fallen from 33 years in 1965 to a projected 14 this year. But what does thi

Welcome to all the AI news that matters. The wins, the fails and the somewhere in-betweens. Across tech, biopharma, medtech, advanced manufacturing and insurance this week. tl;dr: Lots of tokens. Many large clients. But no more Sora Jensen Huang popped up to emphasise that data centres should now be thought of as ‘token factories’. But most insiders were watching a different drama unfold. Entire theses could be written around the week OpenAI experienced. If you weren’t watchi

If you've been struggling to keep up with Anthropic's releases for the past eight weeks, we have love for you. We feel your pain. Two new models. A partner network. A marketplace. Computer use. Voice mode. Memory for free users. Dreaming. A million-token context window. $19bn in annualised revenue - double the run rate of three months earlier. Remote control on mobiles. A corporate acquisition. Read the announcements one at a time and they blur together. Another feature, anot

An AI system passed every science benchmark. Strong results were reported in Nature. Yet it was categorically wrong. The system was supposed to predict which drug molecules bind to a biological target - a critical step in getting new treatments to patients.  What it actually delivered was the preferences of individual chemists. The training data was shaped by their habits. Certain chemists specialise in certain targets. They produce structurally similar compounds. They get go

An economist bet $1,000 that the jobs most 'exposed' to AI will employ more people by 2030. Not fewer. He was responding to a week when social media decided 40% of the American workforce was about to be automated away. The source? A two-hour weekend project by Andrej Karpathy that scored 342 occupations on how digital they are. Software developers scored 8–9. Roofers? 0–1. Then Twitter did what Twitter does. Karpathy's own .readme notes said the scores don't account for deman

Welcome to all the AI news that matters this week. The wins, the fails and the somewhere in-betweens. Across biopharma, medtech, complex manufacturing and insurance. tl;dr: And now for the consequences Last week it became clear AI agents are entering live operational workflows. This week, the consequences arrived. Meta disclosed an agent exposing sensitive data to unauthorised employees - the first high-profile failure of an agent operating inside a production system. Meanwhi

Ask many enterprise leaders if their people use AI and you'll get a confident yes. Ask how many are using it well - you'll likely get a pause. Ramp - the fintech company - publishes internal AI fluency levels. L0 is disengaged or performative. L1 is a competent user. L2 is a non-technical builder. L3 is a technical-grade builder.  In 2025, a quarter of their people were L0. Half were L1. Their 2026 target moves everyone out of L0 - staying there is now grounds for dismissal -

Why insurers are navigating an exponential world with linear thinking One European insurance group spent eight years and more than $500 million on a cross-country platforming programme. They never finished it.   In contrast, another completed its claims platforming project. But 500% over budget.   These are not outliers. Boston Consulting Group’s insurance practice documented them as representative of a wider pattern: programmes conceived for one technology environment, execu

Is AI mightier than the pen? Perhaps it depends on context. Or perhaps there’s no conflict at all. Because there’s mounting evidence that fountain pen wielders are often the heaviest users of digital intelligence. Author and analyst Azeem Azhar - who built a 12KB personality for his AI agent and extracted 146 behavioural patterns from it - does his core thinking with a fountain pen on A4 landscape paper.  Alpha Schools - which uses AI tutors and produces average SAT scores 40

Welcome to all the AI news that matters this week. The wins, the fails and the somewhere in-betweens. Across biopharma, medtech, complex manufacturing and insurance. tl;dr: Agents enter the operating loop This week's defining theme is the release of AI agents into live operational workflows. Across every sector covered here, companies announced agent deployments that sit inside core business processes – payments, underwriting, drug discovery, factory robotics and clinical doc

The hypegeist missed it. But something big just emerged in AI-driven biopharma. A new domain was solved. It's another example of digital intelligence expanding by filling the gaps it doesn't yet occupy. First chess in 1997. Then Go in 2016. Protein structure prediction fell with AlphaFold in 2020. Language generation has worked since 2022. Each time, the domain space was considered too complex - or too vast - for AI to assist. Until digital intelligence evolved and finally cr

From theory to proven, validated practice In Part 1, we established that enterprise AI adoption is a coordination problem , not merely an information problem. In Part 2, we set out the five conditions a training programme must create for a focal point to form : reduced options, shared mental models, common knowledge, group identity and visible early adopters. This final part describes what a programme built on those conditions looks like in practice - how Brightbeam's Embed p

Let's hope ‘Women in Tech’ will be a redundant idea soon, an unnecessary qualifier. Just something we used to be conscious of when recruiting, succession planning and sponsoring events. And maybe, just maybe, AI and other digital technologies will help us level the playing fields. In the meantime, before we arrive at that genderless state, we celebrate those women who are breaking through legacy barriers and shining as bright examples to others. These are the fiercely bright

Welcome to all the AI news that matters this week. The wins, the fails and the somewhere in-betweens. Across biopharma, medtech, complex manufacturing and insurance. tl;dr: AI moves inside the firewall Location is the thing this week. Specifically, the location where AI models run, whose infrastructure they sit on and who controls the data they touch. From biotech licensing on-prem research platforms to insurers discovering that most deployments now involve AI, enterprises ar