Posts about Technology

Years ago, I played a Timeline game with some coworkers, and I immediately wanted to play this game to sequence other events in more specific (or even personal) domains.

Years passed with only a TODO note, so this year, I figured this might be a good candidate to see what Gemini CLI can mostly do on its own in "one shot".

I wrote an initial spec, and I told the agent to read it and implement the whole thing. Of course, it ran off in the wrong direction for the first pass, so I deleted the resulting code, expanded the spec with some more detail, and kicked it off again. I did this about 7 more times, and the results kind of worked, but randomly included and ignored some of my directions. As usual, the guesses it took were mostly welcome, since I just needed to see something, but didn’t know what yet.

Spending tokens to generate the whole thing and throw it away spent lots of tokens and time. Is it really "one shot" if you need to do it multiple times?

A handful of those candidate applications would have been a fine starting point, so I kept one, and went into iterative mode. From that point, I asked the agent for small focused changes like I had for other apps. It’s really good at gathering the context from the existing project and implementing those fixes and enhancements. I (we?) worked much faster and consistently in small bites.

The agent was able to locate and build some datasets for me, but I also scraped and transformed a dataset from the Computer History Museum. That was one of my main motivations to get this project going.

My implementation of Timeline is fun to explore very specific domains and to learn. It’s like flashcards.

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.

I saw a tire was low on the display of my 2017 Chevy Bolt EV, so I topped up the tire with the tire inflator jumpstarter I keep in the car. The next day, I noticed it was still low, so I hit it again and brought it up a little higher. When I checked in the car again, I saw it’s still low, but the back tire is high. The TPMS sensors aren’t in the right place.

They apparently are the type of sensors that I can receive with my RTL-SDR as they drive by the house.

To get the car to register each sensor in the right place, I needed to tell it to relearn the IDs. I bought a little tool for $10 to trigger the sensors, but I apparently could have also done it by deflating the tires in turn to also trigger the sensor on demand.

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.