2026-02 - W3
Thinking on Paper Method for Faster Learning & Better Memory
This is a structured learning technique to quickly learn with 3 key principles:
- make it wrong
- make it shorter
- make it again
It’s counter-intuitive as instinctively try to write down what I’m learning / watching. But what Justin Sung is saying makes lots of sense.
I’ll try on my next learning sessions or meetings.
93% of Developers Use AI - Productivity Only 10%
I’m not surprised about the output. This reminds me of dax tweet:
everyone’s talking about their teams like they were at the peak of efficiency and bottlenecked by ability to produce code
here’s what things actually look like
- your org rarely has good ideas. ideas being expensive to implement was actually helping
- majority of workers have no reason to be super motivated, they want to do their 9-5 and get back to their life
- they’re not using AI to be 10x more effective they’re using it to churn out their tasks with less energy spend
- the 2 people on your team that actually tried are now flattened by the slop code everyone is producing, they will quit soon
- even when you produce work faster you’re still bottlenecked by bureaucracy and the dozen other realities of shipping something real
- your CFO is like what do you mean each engineer now costs $2000 extra per month in LLM bills
tuicr - TUI for Code Reviews
Really interesting TUI for reviewing AI generated changes.
rtk — Make your AI coding agent smarter
CLI tool to have the agent consume less tokens.
I started using it, and I also created a pi extension so that it’s also using it for pi.
Another similar tool that could be interesting to test out: tokf — Token Filter for LLMs.
Gitbutler CLI is really good
Good post about Gitbutler and how it improved his workflow. This post made me want to try this CLI and improve my workflow.