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New article going round about #ai copilots and #llms #llm being found not useful.

When’s the last time you trusted a study on real world software teams productivity? Would you trust a study that says “agile found to have not productivity improvements”? When there are about 800x ways you can do “agile” and 2000 ways to measure “productivity”.

I encourage people to look at people who have the results to show they are credible and check out how they use ai tools (looking at @simon).

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2 comments
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Personally, here’s what I built in about 1h at a coffee shop yesterday using cursor and various #llm #llms:

- autoreload websocket thingamajig with docs and demo github.com/go-go-golems/clay/t
- (minimal for now) svg generating dsl, with full spec, examples, unit tests: github.com/go-go-golems/go-go-
- live web server that renders svgs and autoreloads if a svg gets updated: github.com/go-go-golems/go-go-

I also fixed a few issues in other packages.

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Personally, here’s what I built in about 1h at a coffee shop yesterday using cursor and various #llm #llms:

- autoreload websocket thingamajig with docs and demo github.com/go-go-golems/clay/t
- (minimal for now) svg generating dsl, with full spec, examples, unit tests: github.com/go-go-golems/go-go-
- live web server that renders svgs and autoreloads if a svg gets updated: github.com/go-go-golems/go-go-

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The key thing here is not that I built a lot of features, but that they all come with imo solid documentation, examples, tests, tooling. And it’s absolutely minimal software, built to do exactly what I want with barely an external dependency.

This is way better than what I used to do for my open source, and I did it without eating up my weekend.

It’s an incredible improvement to my creativity and love of software. I get to have a life and build the things I want to build that inspire me.

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