Deep research is underappreciated. The feature exists in all three LLM chat apps I pay for (ChatGPT, Claude and Gemini) and is unfortunately heavily rate limited, which makes sense given the likely token cost. But the massive amount of tokens burnt on reading and analyzing hundreds of articles is the reason it can have such a big impact on some
Here's a model I use to think about how AI will change work. Some parts of every activity will cost 1,000x less than they do when a human does it. For engineers it might mean reading and typing code, for radiologists reading X-ray images, etc. But it's not 100% of the time a human
I've recently seen several engineers struggle when moving to the role of leading a small product team and managing a couple engineers. There are so many newly important meetings and Slack messages (that you could ignore as an individual contributor) and they take up most of your time, but don't feel like "real work"
There seem to be two views of what will happen with engineers' jobs given the new efficiencies from using advanced AI coding tools (Cursor, Claude Code, etc). The first view is partial rebound. Fewer engineers will be needed in total: if engineers are 20% more effective per hour, there will be some downsizing of the total engineering bill. Perhaps
Gemini 2.5 Pro was just released and it could be a big deal, if its coding abilities pan out. The current positioning of Gemini has been roughly that it is a tad behind the OpenAI/Anthropic models of the same class, and far behind the coding capabilities of Claude 3.7 Sonnet which is considered unmatched for practical engineering
At one point in my career, our company was hiring for role of a Head of Marketing. I got a strong referral from a friend, reached out, the match was great, and she passed the interview process with ease. And then we just... sat on it. The hiring manager said he wanted to consider three candidates and then pick the
Anthropic, OpenAI and possibly others are doing one in the US with 1,000 participants from public sector research institutes. It's called an "AI Jam" and the companies are obviously doing it out of commercial interest. Even so, the government sector must have such obvious use cases. Just running a bureaucracy consists of processing and summarizing
In Would You Rather Have Married Young?, Lillian Fishman writes about the "fundamental ethos that had long governed the young secular woman" in the last 50 years: Experience, we hoped, would broaden us. The new object seems to be the inverse: the contraction and refinement of the self, within and against the overwhelming flood of external information with
I rarely look at the search analytics for my blog, but today I did. I am really amused by the most common search queries that bring people to this website, which definitely show the variety of content I post here. Here are the top ones in the past month, with similar ones grouped: 1. are LLMs deterministic (Are LLMs deterministic?
Vibe-coding produces close-to-unmaintainable code right now. But it is an acceptable trade-off in places where it produces decent results and maintainability matters less -- for example making simple UIs. So maybe a good approach is to vibe-code with stable infrastructure. This riffs off of Facebook's engineering principle "move fast with stable infrastructure"
