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Retraining our Brains To Review LLM-augmented work 2025-07-22
A Simple Path To Building Trust 2024-06-25
Setting Expectations: 4 key areas for performance management 2023-02-12
3 Pillars For Effective Work 2023-01-13
2022 Books 2023-01-03
Blog Updates: New name, new platform 2022-12-17
Mental Models For Managing Change 2022-01-24
More Thoughts On Time 2022-01-10
How I Think About Time 2021-12-13
Values Are How You Scale Culture 2021-11-29
This is a good summary of the state of AI takes right now I think
No one knows anything about AI
AI is important. But we don’t yet fully know why.
AI currently has all the “noise” and incentives to hype that crypto had a few years ago, but underneath that is clearly much more “real”. It makes things hard to evaluate for now.
The intended takeaway from all this is exactly where we started in the introduction: creating quality is context specific. Be wary of following the playbook you’ve seen before, even if those playbook were tremendously successful. They might work extremely well, but they often don’t unless you have a useful model for reasoning about why they worked in the former environment.
Loved the thoughts on quality here from Will Larson: lethain.com/quality/
Over a year old, but new to me – I thought this series of posts was a great roundup of some of the issues that make tech a less happy place to work than in the previous decade: Software and its Discontents
Very helpful writeup on LLMs in production: What We’ve Learned From A Year of Building with LLMs
Reality Has A Surprising Amount Of Detail
This is an old piece, but new to me. What a great turn of phrase, and accurate insight about doing hard things.
Diving back into (Neo)Vim this week for the first time in a few years (have done my core work with VS Code for a while).
Telescope Plugin + Language Server Providers are nice additions to the landscape, and it all feels so powerful, but everything is still so fiddly to setup :/
Really enjoyed these reflections on LLMs: medium.learningbyshipping.com
AI, ChatGPT, and Bing…Oh My
Basically from a “quality triangle” perspective – execs can control costs or time, but holding the line on a minimum quality bar is essentially a core piece of my job, and nobody wins when you try to promise impossible combinations of scope/quality/dates.
In an ideal world, org leaders define goals and teams figure out what to do. But top down asks happen. How I decide whether to push back on top down asks as an EM:
The idea that things become hits mostly due to a small number of large audiences rather than point to point viral sharing seems intuitively correct to me: www.lennysnewsletter.com/p/viralit…
Or at least the large audiences “seed” the viral behavior