A lot of these bot-less tools don't indicate who said what in their captured transcript. Many people face problems with misattribution when they ask their meeting note-taker a question about what they might have said in a particular meeting a few months ago.
Every iOS app I've shipped over the last nine years started the same way: a Rails developer with a great web app, users who want it in the App Store, and weeks spent on Xcode, signing certificates, and Swift boilerplate that has nothing to do with the actual product.
NotebookLM is quietly becoming one of the most powerful tools for serious thinking work; yet most people use only a fraction of its potential. If you work with research, strategy, product thinking, or complex data research & analysis, NotebookLM can dramatically improve the quality of your decisions. I've demonstrated what NotebookLM is capable of in the article NotebookLM for Product Designers.
The software industry is collectively hallucinating a familiar fantasy. We visited versions of it in the 2000s with offshoring and again in the 2010s with microservices. Each time, the dream was identical: a silver bullet for developer productivity, a lever managers can pull to make delivery faster, cheaper, and better. Today, that lever is generative AI, and the pitch is seductively simple: If shipping is bottlenecked by writing code, and large language models can write code instantly, then using an LLM means velocity should explode.
They may be spending a lot of combined time at the office and commuting, or just putting in a lot of hours both at work and at home. Fixing that problem can't be done abstractly, though. If you're going to address the balance of work and life activities, you have to start getting specific about where your time is going and where you really want it to go.
One thing I always do when I prompt a coding agent is to tell it to ask me any questions that it might have about what I've asked it to do. (I need to add this to my default system prompt...) And, holy mackerel, if it doesn't ask good questions. It almost always asks me things that I should have thought of myself.