19 February 2026
The Gemini AI will make some pretty good guesses about how a 3rd-party API may work. It is good at searching the internet, but when APIs have changed across versions, the old and new docs and examples it’ll find can confuse it. In a dynamic language and environment you’ll not spot these errors until runtime.
To combat the ambiguity and to give the AI agent more power to solve its own problems, ask it to add some tests around the code that uses the API. (In my case, the API is the XTDB client API.) Once it has a way to execute the code through tests, it’ll quickly start figuring out where it’s made mistakes and start running its own experiments to observe errors, search for fixes, and applying those fixes around the codebase. I exhibit the same pattern when I’m doing it by hand.
The tests also give you, the human, an easier entry point to evaluate the code the AI generated. If the tests look gnarly, you know to suggest refactorings to improve the architecture and make it easier to test. When the AI has the tests passing, and the test code is easy enough to read, then you can have a closer look at the application code to refine and keep that maintainable too.
09 February 2026
Gemini CLI
is getting even stronger
for Clojure code.
The clojure-mcp
is part of that power:
it’s exploring the code and fixing up syntax
quicker now.
In addition to writing code, it’s been good at listing and implementing optimizations and refactorings to improve the code when asked.
I’d still like to remind you to ask the AI to explain itself. It’s still our responsibility to understand what it’s doing and to question its decisions, just like we would to get the best we can from any other teammate. It’s our opportunity to learn and understand too from a very comprehensive summary of all the internet searches I used to need to do for myself.
31 December 2025
I’ve had Gemini CLI installed on my workstation since August 2025.
Originally,
it would default
to use the gemini-2.5-pro model
and your "access" to that
would run out for the day,
and it would switch to using gemini-2.5-flash.
I found the flash model to be adequate
for the way I’d use it to do Clojure and ClojureScript,
so most the time I’d override
it to just use flash from the beginning.
I thought I could kick over to pro
if I found a problem for which I’d need more power.
Eventually,
Gemini CLI started switching back and forth
between models more intelligently,
so it didn’t burn through your limited access
to pro,
so I no longer override it with 3.0 models.
The AI agent by itself has read lots of documentation, and it’s pretty good at Googling the answers to questions and picking something to try. (I often get a bit of analysis paralysis when trying to choose a library.) It can be surprisingly good at translating sample usage of some JavaScript library it finds into a simple bit of ClojureScript.
In my experience, it’s sometimes bad at matching parentheses, so I just fix them myself. Recently, it may be getting better, and some Clojure MCP projects can cleanup parentheses automatically.
I only ask it to do small tasks,
and I closely review and test
the code it generates.
When it looks good,
I commit and push the code,
but I know I can always
easily go back to a previous working version
when the AI goes off the rails.
I don’t have to worry too much
about it getting too confused
or destroying something.
I tell it to forget what we were doing,
/clear the context,
or just restart the agent completely,
and recover my known good state from git.
(Update 2026-02-17:
/rewind may be better these days
for clearing some context.)
I find that even if it fails to complete a task, I at least learn a little from what it did, and often have an initial direction or two to explore.
It’s pretty good at keeping my momentum when working and keeping me from spinning my wheels, like pairing with another programmer.
11 August 2025
For our local art collective, Susquehanna River Creative Collective (SRCC), I setup some Raspberry PIs connected to televisions to display our flyers advertising benefits of membership and upcoming events.
The machines are behind a firewall and running on a read-only overlay filesystem for resiliency, so I had the machines periodically pull the event images from the website, and I can change out the images on the website any time.
This was all done with desktop autostart scripts
and cron for quite some time,
but eventually, we needed more control.
We wanted to have different sets of images and to be able to choose them. For a show, we may want to only show the logo, while other times might call for all the normal advertisements.
The machines have no keyboards or mice, so they needed to be controlled by a web browser. I also don’t know if they’ll start up on the same IP addresses, so I needed a bit of Javascript in a static place to have the browser search and find running slide servers.
The service on each machine
now runs as a babashka script that starts upon automatic login.
It pulls new images from the website
and from a Google Drive,
periodically refreshes them,
and starts Eye of Mate (eom)
to run the slide show.
The babashka script
also starts a small web server
on http-kit to let us
to choose image sets
and to trigger a refresh of the images.
http-kit is provided by default in babashka.
The SRCC website is a static site built with Hugo, so I add all the events to it via an image or 2 and some YAML. It’s hard to train another normal person to do this stuff, so the responsibility fell exclusively on me. I scripted it up with some bash, but that’s still only accessible to me.
Finally, I’ve been coding all Clojure code for the past couple weeks, and I’ve started playing with Gemini CLI to see what it can do with some Clojure code.
I now have a web form available to
allow others to create events
for the website,
and it interacts with git
for publishing to the Hugo site.
The service is deployed on my normal Linux servers
as a container run by podman kube play
and systemd quadlet.
I can direct Gemini to make changes or add features, and I review the code, ask for corrections or just make updates myself. It’s kind of like pair programming with someone who’s really good at Googling answers and jumping to some (mostly) useful conclusions. Having the AI agent has helped maintain some momentum and saved me jumping down some deep rabbit holes before I needed. I’m asking it for small changes and iterating, not trying to get it to do everything in one shot.
Gemini’s CLI interface makes it easy to switch to another project directory and let it try some stuff on lots of my projects recently.
I had also played with Claude CLI for a day, but Gemini’s free tier is proving capable enough for me so far.