Takes practice, and a bit of audacity.
The intent pipeline: why most prompt guides miss how people actually use AI
Most prompt guides assume that people interact with AI by carefully authoring prompts. In practice, that is rarely how AI is used. Most…
The Interview Question Bank for Engineering Managers
Organised by theme, and every question comes with a short thinking prompt
Google’s AI search is so broken it can ‘disregard’ what you’re looking for
“If you need anything else or have a new question later, just let me know!”
My 'Grill Me' Skill Went Viral
Learn the "Grill Me" AI skill—a powerful technique to deeply explore coding plans, requirements, and ideas through structured AI conversations.
Inside the Don’t Ask, Don’t Tell Era of AI in Music
From juicing demos to cloning vocals, AI music tools are creeping into the workflows of top producers, songwriters and artists. It’s mostly happening behind closed doors — for now
The thing it turns out lots of us want
Last month I posted a questionnaire. Here’s what you said
values based software talks
Talk #3 Files, algorithms, media, software as lived practice, and personal software
things I should know by 30 (but don’t)
How to learn things at 1000x the speed
Throughout my schooling and career, I’ve impressed people over and over again with how quickly I pick up things, especially hard things. For instance, exactly 4y ago I did my first ever interview, got
Launching the Tacit Knowledge Podcast: How the world's hardest problems really get solved
By Kumar Garg
Why You Should Keep Listening Even If You Don’t Understand | AJATT | All Japanese All The Time
Like I’ve said before…the set of tools/methods described on this site…I don’t know why it all works; looking at and thinking about how people learn their native language, it just all seemed obvious to me. In other words, I knew what I needed to do to achieve fluency…but not much more.
Do People Ask Good Questions?
People ask questions in order to efficiently learn about the world. But do people ask good questions? In this work, we designed an intuitive, game-based task that allowed people to ask natural language questions to resolve their uncertainty. Question quality was measured through Bayesian ideal observer models that considered large spaces of possible game states. During free-form question generation, participants asked a creative variety of useful and goal-directed questions, yet they rarely asked the best questions as identified by the Bayesian ideal observers (Experiment 1). In subsequent experiments, participants strongly preferred the best questions when evaluating questions that they did not generate themselves (Experiments 2 and 3). On one hand, our results show that people can accurately evaluate question quality, even when the set of questions is diverse and an ideal observer analysis has large computational requirements. On the other hand, people have a limited ability to synthesize maximally informative questions from scratch, suggesting a bottleneck in the question asking process.
Expecting researcher taste and judgement to become increasingly valuable (this is from Anthropic's Opus 5.5 system card) anthropic.com/claude-opus-5-5-system-card
