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dsmurrell

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It's somehow more tiring, reading complex plans in response to your guidance, and then making decision after decision. Reminds me of this Alan Watts bit...

A farmer who ordered a farmhand quickly discovered he was an extraordinarily efficient worker.

The first day, he put him on sawing logs, and the farmhand sawed more logs than anybody else, ever. It was fantastic — but the wood-cutting work was all done in one day.

So, the next day, the farmer put him onto mending fences. There were all kinds of broken fences around the farm. And, again, the farmhand had all the work done in one day.

So the farmer thought, “What am I going to do with this guy?”

The next day, he took the farmhand to a basement and said, “Look, here all the potatoes that have come in from this harvest. I want you to sort them into three groups: those we sell, those we use for seeding, and those we throw away.”

He left the farmhand to it. And at the end of the day, the laborer came back and said, “Well, that’s enough, mister, I quit.”

“Oh,” the farmer replied, “You can’t quit. I’ve never had such an excellent worker. I’ll raise your salary — I’ll do anything to keep you around me.”

The farmhand said, “No. It’s all right mending fences and chopping wood, but this potato business is decision after decision after decision.”

Making AI great at coding was the strategy that unlocks everything else. That's why they did it first.

They did it first because doing it first was easier. There are tons of examples around and code can be verified to work.

I wrote this coincidentally a few days before the recent news about Tailwind’s layoffs and revenue downturn due to AI’s impact on doc use leading to their paid product distribution being affected.

In my own AI-heavy workflows, I’ve noticed that AI tools are great at generating layouts quickly, but the results tend to converge on a certain look and feel and often lack polish around responsiveness and design details.

Templates still accelerate my builds. They encode decisions, constraints, and taste that I don’t want to recreate from scratch... even with the help of a coding agent.

As AI becomes more central to how we build things, do templates continue to retain value, or is this just a transitional phase?

A few weeks ago I built a very simple metrics tracker that I had been looking for myself... a middle ground between complex observability platforms and tracking a number yourself and then finding a way to visualise its change over time.

I had had the idea and the domain registered for years and recently just took the leap to put it out there.

https://spikelog.com

Great, you're the first user then! If don't mind sharing your metrics, feel free to DM me on discord, I've joined yours.

1) Good point, I wanted to avoid the complexity of this for the first version, but you're 100% right, it would be great for someone to try first then upgrade when they register an account.

2) Thanks. Great to hear!

3) The best way to do this right now would be to create a project for each env and then give each env the API key from the corresponding project. Another way could be to put the env in the tags, but I think that's a bit messier as both lines would appear on the same chart (plus I've not even tested that works yet).

vibescaffold.dev looks interesting. Let me spend a bit of time and I'll feed back in your discord.

Thank you! and I appreciate the mentions... they’ll definitely be useful for my projects that need more than simple tracking. I might choose to link them instead of Axiom after doing more research into the options!

I’m very aware there are a lot of mature solutions in this space. Almost too much choice - which gave me decision paralysis when my need was simple. I’m not aiming to compete with full observability stacks like that. My goal with this was to intentionally stay on the extremely simple end of the spectrum. I'm aiming for something that’s quick to integrate, easy to understand, and focused on lightweight metrics rather than deep operational telemetry.

I’m also a big fan of Plausible and the idea of making select projects or charts publicly viewable in a dynamic way. Their public dashboard here was a big inspiration: https://plausible.io/plausible.io

That’s the model I borrowed for Spikelog as well: https://spikelog.com/p/spikelog