This document is a summary of my personal experiences using generative models while programming over the past year. It has not been a passive process. I have intentionally sought ways to use LLMs while programming to learn about them. The result has been that I now regularly use LLMs while working and I consider their benefits net-positive on my productivity. (My attempts to go back to programming without them are unpleasant.)
Forcing Generative Models to Degenerate Ones: The Power of Data...
Growing applications of large language models (LLMs) trained by a third party raise serious concerns on the security vulnerability of LLMs.It has been demonstrated that malicious actors can...
In spite of hype, many companies are moving cautiously when it comes to generative AI | TechCrunch
Companies are extremely interested in generative AI as vendors push potential benefits, but turning that desire from a proof of concept into a working product is proving much more challenging.
Avoiding generative models is the rational and responsible thing to do – follow-up to “Trusting your own judgement on ‘AI...’”
Writing at the end of the world, from Hveragerði, Iceland
Here’s how I use LLMs to help me write code
Online discussions about using Large Language Models to help write code inevitably produce comments from developers who’s experiences have been disappointing. They often ask what they’re doing wrong—how come some …
How I program with Agents
Personal experiences using feedback-driven LLMs to write programs.
Compiling knowledge, not retrieving it: a hands-on deep dive into llm-wiki-compiler
The thesis of this piece is simple and uncomfortable: the problem of making an LLM “remember” what you’ve read isn’t solved with more…
LLM-generated skills work, if you generate them afterwards
LLM “skills” are a short explanatory prompt for a particular task, typically bundled with helper scripts. A recent paper showed that while skills are useful to LLMs, LLM-authored skills are not. From the abstract:
On generative AI and LLMs | Stefan Bohacek
Generative AI is anti-worker, anti-environment, and doesn't even work all that well.
Generative AI’s crippling and widespread failure to induce robust models of the world
LLM failures to reason, as documented in Apple’s Illusion of Thinking paper, are really only part of a much deeper problem
Generative AI’s crippling and widespread failure to induce robust models of the world
LLM failures to reason, as documented in Apple’s Illusion of Thinking paper, are really only part of a much deeper problem
Dan Shipper 📧 on Twitter / X
this is true and is a big reason why you don’t need to be a highly technical researcher to use LLMs in surprising and novel ways https://t.co/TuxNzXzToU— Dan Shipper 📧 (@danshipper) July 27, 2025
Generative artificial intelligence: The Times and Sunday Times editorial guidelines
As we explore the potential of generative artificial intelligence our commitment is to uphold our high editorial standards.
I'm thinking about what *generatives* are most applicable in the atmosphere — per Kevin Kelly, "better than free" qualities that can't be copied even on the internet: edge.org/conversation/kevin_kelly-bett… Things like contextualization, personalization, sensemaking…ideas? Need to write about this more!
