Treat your to-read pile like a river - ”To return to information overload: this means treating your “to read” pile like a river (a stream that flows past you, and from which you pluck a few choice items, here and there) instead of a bucket (which demands that you empty it).” // Be comfortable with a to didn’t read list.
Posts in "links"
32 notes on AI & writing - “AI is better than most humans at producing prose. In a couple years, it will be better than most “professional writers” as well. Most text is not creative. Emails, policy papers, reported news. It does not desire to surprise or delight. It aims to convey ideas and information as clearly as possible.” // We should be using AI for corporate communication without shame. There is little value in internal, corporate communication to be “genuine.” The very important except is when you lay people off. // That said: I should test this theory by having Gemini rewrite my inner-comms for a week.
The Ditherinator - Convert your photos to shitty old versions that will print well on dot matrix printers. Love it.
UK government productivity not enhanced by Copilot AI pivot-to-ai.com/2025/09/1… ‘The main uses were “transcribing or summarising a meeting”, “writing an email”, and “summarising written communications”. The bot didn’t do so well on anything more complicated.'
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."
Atlassian acquires DX, a developer productivity platform, for $1B - That’s a good match, and a quick exit.
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.
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."
Slowing Down - How to avoid burnout as you get more successful at life.