Plus: OpenAI has unveiled its long-awaited super app. The AI firm Anthropic has got the clearest glimpse yet at what's really going on inside large language models as they answer questions or carry out tasks. What they found ranges from the mundane to the unnerving. Researchers at the company built a tool called the Jacobian lens (or J-lens) and used it to uncover a hidden area, which they named the J-space, inside its flagship LLM, Claude. The J-space contains words related to the response a model is working on but may not ultimately produce. If Claude were a person (which it is not), you might say these hidden words reveal what's on its mind before it actually speaks.

The AI firm Anthropic has developed a technique that has given it the clearest glimpse yet at what's really going on inside large language models as they answer questions or carry out tasks. What they found ranges from the mundane to the unnerving. Researchers at the company built a tool called the Jacobian lens (or J-lens) and used it to uncover a hidden area, which they named the J-space, inside Claude Opus 4.6, a version of Anthropic's flagship LLM released in February.

Plus: NATO is building a network to stop Russian attackers in their tracks. I was really looking forward to July 4, and not just because I love a poolside barbecue. This year the American holiday also marked a big symbolic deadline for US nuclear power. Last year the Trump administration set a goal to see three new microreactors achieve criticality, a technical milestone establishing that a reactor can sustain a chain reaction, by the nation's 250th birthday. And just in time, not just three, but four reactors did so. But achieving criticality doesn't mean a reactor is ready to provide electricity for the grid (or at all, for that matter).

Plus: Samsung profits have jumped 1,800% on booming AI chip sales. Sam Altman's proposal that Americans should share in the wealth created by AI is back in the spotlight, with reports that he is discussing giving the US government a 5% stake in OpenAI. At the company's current valuation, that stake would be worth roughly $320 per American household. The idea is meant to address concerns that AI companies are benefiting from human-generated work without compensating creators, while also easing fears that AI will cause a collapse of the labor market by providing a safety net. The details, however, remain unclear. Indeed, the offer may be more powerful as a political narrative than as a policy plan.

Discover four foundational elements of AI architecture that will endure as models continue to advance: data quality, context engineering, governance, and human expertise. With the rapid progress of AI capabilities and the move to agentic systems, organizations are expanding their use cases as the technology continues to grow. That constant evolution also introduces risk, leaving IT leaders to wonder which investments will prove valuable even six months into the future. Returning to the foundational elements of AI architecture--the structural framework required for deploying and managing reliable, integrated AI systems at scale--allows technology leaders to make astute decisions today while supporting a future of AI agents that can retrieve information, make decisions, and execute complex workflows across systems. The following capabilities provide a stable compass on the path to production-ready deployment, regardless of how the underlying technology evolves. Models are only as reliable as the data they can access, and poor data quality leads to AI hallucinations, bias, and unreliable outputs.

Sam Altman wants Americans to share in AI's wealth. The proposal may be more revealing as a political narrative than as a policy plan. OpenAI CEO Sam Altman's oft-discussed promise that Americans will share in the wealth AI creates was in the news again last week. On Thursday, the reported that Altman is in talks with President Trump about giving the US government a 5% stake in OpenAI. In some ways, Altman's plan is old news. He wrote about a more radical version of this back in 2021, proposing that companies above a certain valuation (not just AI companies) pay 2.5% of their market value each year into a fund that sends Americans annual disbursements.

Plus: An EU lawmaker investigating spyware was hacked by that same spyware. The UK's generational tobacco ban might not work. As the parent of two little girls, I often think about how their childhood is different from mine. The seven-year-old is learning about AI at school. The five-year-old is given internet-based homework every week. And they are both absolutely repulsed by the idea of smoking.

As AI reshapes how work gets done, organizations with strong process frameworks are best positioned to lead and maintain operational rigor at scale. Frameworks like Lean Six Sigma and business process management (BPM) first gained traction because they promised clarity in the chaos--a structured way to bring order to messy, sprawling operations. Lean Six Sigma emphasized statistical rigor and quality control; BPM created end-to-end maps of how work should flow across departments. Both offered a repeatable way to embed habits of measurement, analysis, and accountability into day-to-day company culture. But today, those time-tested playbooks are evolving as companies seek to embed AI into established process excellence methodologies. By some estimates, the market for AI-powered process optimization is projected to exceed $113 billion within the next decade.

The Download: a startup has a solution for AI's groupthink problem Plus: Scientists say they have built a cell from scratch for the first time. LLMs are stuck in a groupthink groove. This startup is trying to get them out. Open up your chatbot of choice--Claude, ChatGPT, Gemini--and type "Give me a random number between 1 and 10." You're going to get 7. Almost always. That won't work every time--but if it did for you, you may wonder if I have superpowers. The truth is that most large language models are stuck in a rut.

Let's start with a game. Open up your chatbot of choice--Claude, ChatGPT, Gemini--and type "Give me a random number between 1 and 10." You're going to get 7. Almost always. Now type "Another" and you'll get 3 or 4. Type "Another" again and you'll get 8 or 9. That won't work every time--but if it did for you, you may wonder if I have superpowers.