Experimenting with #AI #subagents.
I delegated 4 GitHub issues to parallel subagents. The biggest win wasn't the speed — it was context isolation. Here's how I did it.
claudecode
AI-assisted #genealogy with #ClaudeCode
My son recently came to me to brag about using AI to find our ancestors. While the results were correct, I didn’t learn anything new, as it stopped at my grandparents. I was never very interested in my genealogy, but I decided to see if AI would be a good tool for this. In a little less than one month, I managed to gather more than 600 individuals and get back 12 generations in some branches.
Most developers now use coding assistants. I do too—#Copilot at work, #ClaudeCode at home. As a developer, I prefer not to repeat myself. This post explains why and how to avoid repetition with skills.
So Anthropic employees are using Claude Code to contribute AI-generated code to open source repositories and hiding the fact using their own internal “undercover mode”.
Totally trustworthy people.
(Any open source project that at the very least requires disclosure of AI-authored contributions should immediately ban Anthropic employees on principle.)
Edited 167d ago
I recently reread Fred Brooks's 1986 classic No Silver Bullet, which you can find here: https://www.cs.unc.edu/techreports/86-020.pdf . I think it is useful to re-consider Brooks's distinction between the essential complexity versus the accidental complexity of software development in light of the recent mania behind using LLMs for coding. Which of these types of complexity does LLM use address? Does it introduce more of either class of complexity?
In light of what I've seen, LLM use seems to provide the illusion of addressing both kinds of complexity in the short-term while it increases essential complexity in the long-term. It may or may not reduce some accidental complexity; the verdict is still out, as far as I can tell. Judging from the recent leak of the Claude Code front end source code, LLMs seem to introduce an enormous amount of new accidental complexity.
To the extent that LLMs are in the category of what Brooks calls automatic programming, this quote he shares from David Parnas is important:
Taken together, all this seems to suggest that LLM use in coding is a net negative, and if the above is to be believed it will result in worse outcomes, not better, over the long haul. Definitely re-read Brooks and see if you agree.
#AI #GenAI #GenerativeAI #AgenticAI #LLMs #ClaudeCode #software #tech #dev #SoftwareEngineering #SoftwareDevelopment
In light of what I've seen, LLM use seems to provide the illusion of addressing both kinds of complexity in the short-term while it increases essential complexity in the long-term. It may or may not reduce some accidental complexity; the verdict is still out, as far as I can tell. Judging from the recent leak of the Claude Code front end source code, LLMs seem to introduce an enormous amount of new accidental complexity.
To the extent that LLMs are in the category of what Brooks calls automatic programming, this quote he shares from David Parnas is important:
Automatic programming always has been a euphemism for programming with a higher-level language than was presently available to the programmer.
Taken together, all this seems to suggest that LLM use in coding is a net negative, and if the above is to be believed it will result in worse outcomes, not better, over the long haul. Definitely re-read Brooks and see if you agree.
#AI #GenAI #GenerativeAI #AgenticAI #LLMs #ClaudeCode #software #tech #dev #SoftwareEngineering #SoftwareDevelopment
I realized that if I was writing a program and it didn't always work, I had a choice: I could either fix it, or call it AI.
#AI #GenAI #GenerativeAI #AgenticAI #LLMs #Claude #ClaudeCode #ChatGPT #tech #dev #software #SoftwareDevelopment #SoftwareEngineering