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I think “agent” may finally have a widely enough agreed upon definition to be useful jargon now - “[AI ‘agents’ are] Tools in a loop to achieve a goal… wiring up tools to an LLM in order to achieve goals using those tools in a bounded loop.” // Also, he’s not a fan of the “autonomous” vision, which feels right. // “This category of agent remains science fiction. If your agent strategy is to replace your human staff with some fuzzily defined AI system (most likely a system prompt and a collection of tools under the hood) you’re going to end up sorely disappointed."

When you don't know what you're doing, do a lot of it

This a good, correct framing of the AI project failure stuff. No one really knows what will work and what they’re doing yet. As we learned in the digital transformation craze of the 2010’s, this means failure == learning. And learning is what you need to do a lot of. More so, this kind of rapid learning, innovation, and sense making is exactly what a platform like Tanzu Platform with Cloud Foundry is excels at, and has a long, proven history of supporting.
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Anthropic Economic Index report: Uneven geographic and enterprise AI adoption - 🤖: “Enterprise deployment via Anthropic’s API exposes a different facet: businesses adopt AI programmatically to automate. 77% of API usage is automation-dominant, particularly in coding, debugging, office administration, and recruitment. Surprisingly, firms are not especially price-sensitive; higher-cost tasks see higher adoption if they deliver economic value. Yet complex, high-impact deployments are constrained by context—firms need to restructure data flows and centralize knowledge to fully unlock AI potential. Without this, sophisticated tasks remain underutilized, delaying broader productivity diffusion."

Gartner predicts 40% of enterprise apps will feature AI agents by 2026 - “Enterprise applications are entering a new phase of automation, with Gartner forecasting that 40 percent of them will include task-specific AI agents by 2026 – up from less than 5 percent today.” And: “By 2035, the firm predicts, agentic AI will account for nearly $450 billion in enterprise software revenue, or 30 percent of the market.” // Some predictions about broad uses as well. The uses are mostly (all?) the idea of having an assistant in your tasks, yes, a “copilot."

School phone policies and their association with mental wellbeing, phone use, and social media use (SMART Schools): a cross-sectional observational study - Update on the young people and those damn video games. // “There is no evidence that restrictive school policies are associated with overall phone and social media use or better mental wellbeing in adolescents. The findings do not provide evidence to support the use of school policies that prohibit phone use during the school day in their current form, and indicate that these policies require further development.” // See Tyler Cowen’s disclaimer. // I mean, it could be one of those “phones don’t ruin kids lives, kids using phones to ruin their lives ruins their lives” situations.

How To Build Agentic AI That Ships - The New Stack - “Ninety-five percent of AI initiatives should be expected to fail as long as we ignore these pitfalls: Models are generic. Enterprises are unique. Ideal use cases aren’t flashy. Coordination across teams is hard.” // Lots of other good executive think too, especially being blind to how complex the overall system is w/r/t dependencies. // Also notable is that, technology aside, these are all the concerns of “digital transformation."