The last six posts were largely written by Claude and merely edited by me.

This post, on the other hand, is all me. In the 6 months or so since we started this GoRead2 adventure, I’ve learned a lot about working with an AI partner.

First, AI is a terrible writer. If you read all of that GoRead2 stuff, well, I’m sorry. AI tries too hard to sound human by using conjunctions and witticisms. It is overly fond of hyphenated sentences. You can tell when a paragraph was written with AI–just look for the mid-sentence hyphen or weirdly-ordered sentences with clauses separated by hyphens. For the GoRead2 posts, I had Claude generate the initial text (after all, it had done all of the hard work), but then I took about a week to edit each one. I had to put a time limit on the editing, or I would have rewritten everything.

Second, keep everything on your system updated, because the AI ecosystem evolves fast. I run brew update and brew upgrade reflexively at this point, and I use a shell script to run a bunch of git pull commands every time I open a terminal. If you skip these sorts of tasks for a week, you will be hopelessly out of date, and you’ll have a bunch of extra work to do to catch up again.

Third, but on a similar note, the capabilities of the AI tools increase almost constantly. It is hard to keep up, but the more of those capabilities you can leverage, the easier things will be. When I started the GoRead2 project, capabilities were limited to having Markdown files that told the AI what to do and what not to do. I know Beads is controversial but using it made sense for this project, and made tracking work across multiple development machines so much simpler. I probably didn’t make use of all of the Claude Code bells and whistles, and I am sure that cost me.

Fourth, as we alluded to in Part 6 of the GoRead2 series, humans have domain knowledge; but at least as of this writing AI tools do not. I’ve been playing with software in some form or another for 40+ years, and in that time I think I’ve learned a thing or two about how things should be run. Claude does not have this experience and needs to be told that (for example) certain approaches to testing or deployment have inherent advantages. AI has come a long way in the last year, but we are not yet at autonomy. The humans still need to be in charge.

Finally, I remember getting my Commodore 128 when I was 14 or 15 years old, and being so thrilled when I could enter 10 lines of BASIC code and get something back. I remember typing in entire programs from magazines, being disappointed when they did not run, spending hours debugging them, realizing the issue was because the magazine was incorrect, experimenting with and finding a fix, and then getting the program working. This process was a rush unlike anything else I’ve ever experienced…until recently. The process of working with an AI and getting it to spit out a working piece of software based on my description alone, tweaking the description and prompts to make the software better, and getting the result I wanted…this is why I love working with computers in the first place. There are many legitimate reasons to look at AI with wary eyes, but I cannot deny that the process of going from zero to working product has become ridiculously easy.