Weekend Reading List — 04/04/2026
Have a great weekend.
Links
“Nothing new to see here” - Brad Feld. Every big tech transformation (internet, web, cloud, mobile) creates new winners and most importantly, makes new losers out of legacy winners (Blackberry, Blockbuster etc). What’s interesting about these great tectonic shifts is that the “rules” of the old game don’t necessarily apply to the new game anymore. Keep in mind when anyone tells you “it isn’t possible/it won’t work/we’ve always done it this way”.
“Why are executives enamored with AI but ICs aren’t?” - John J Wang. A refreshingly new take on why, in broad terms, managers love AI, but (many) individual contributors are more skeptical. The cynical argument that you’ve read a thousand times on this is easy to make: managers are morons who are too disconnected from the work to tell whether the output is good or not. This seems like a drastic oversimplification to me, and I like John’s nuance here. His basic premise is that managers are simply more comfortable working within chaos. In highly non-deterministic chaos where they can grasp onto the “the general behavior of the system, even if they cannot predict the specific outcomes at any point in time”. Incentives matter here too. Managers are rewarded and evaluated on their ability to steer the ship in the right direction inside a chaotic system, whilst ICs are evaluated on specific task execution where accuracy is (obviously) more important.
“Institutional AI vs Individual AI” - George Sivulka. There is a weird thing going on right now. Individuals can be 10x more productive with AI tools, but most companies aren’t 10x more productive. This is a good piece that tries to explain why this is and presents a framework for “Institutional AI” which could start to solve some of these problems for organisations. Put simply, you won’t institutionalise the productivity gains until a whole system is rebuilt around enabling these gains.