A critical assessment of current AI limitations, focusing on the failure of 'intent engineering'. Despite scaling, LLMs remain static and lack the dynamic, deeply human value systems derived from experience. Using the Klarna AI case, this post argues that centralized LLMs are light-years away from understanding true, adaptable intent.

The traditional tech hierarchy is collapsing. AI agents like Claude Code and Lovable are merging the roles of PMs, designers, and engineers, effectively eliminating the entry point for juniors. We are entering a brief window where professionals must transition into AI operators before token costs lock the gates. Adapt now, or risk obsolescence.

AI is eliminating pointless corporate meetings, but it demands a new skill: clear communication for AI transcription. Product managers must now become 'human APIs,' connecting business fundamentals with technical execution. As LLM costs rise and teams shrink, the non-technical PM is becoming obsolete. It's time to adapt by mastering the tools and the economics, or risk being replaced. The future of product management is technical, concise, and relentlessly focused on value.

A journey into replacing Google-centric devices with Linux alternatives like the PinePhone reveals a harsh reality: we are losing ownership of our technology. This is a look at the forced telemetry in our phones, cars, and homes, and the near-impossible challenge of reclaiming our digital sovereignty in a world that profits from our data.

We've reached a point in history where LLMs are consuming everything on the web. These new products-whether it's Google, Bing, or the various AI assistants-consume content that doesn't really belong to them. They act as middlemen, delivering results without you ever accessing the original source. They eliminate the need to visit the actual page, to read the original author's work, to see other people's contributions on platforms like Stack Overflow.

A breakdown of Cory Doctorow's essay on why more code, especially AI-generated, is a threat. It covers the hidden dangers of treating code as an asset, the myth of stable software, and the critical difference between writing code and software engineering.