I never viewed it as that. I used it as I kicked off initial implementation/discovery with it, and edited with it along the way

Are you using hooks? Hook based functional components will do funky things if you don’t adhere to the lifecycle rules

🦡 🍄 🐍 archive.org/details/flas...

How can you reduce the risk of misreading the expensive to read signal? Find lots of cheap correlated signals.

When one cheap signal diverges, you have your first signal the expensive signal has diverged. You should dig a bit deeper.

But some signals are cheap to read, and some signals are expensive to read.

And with enough historical correlation you can still safely estimate the correlated signal from the cheaper signal.

This allows prioritising resources to only measure the expensive, when a deviation is detected…

A larger working memory means more data to understand cause and effect.

I was always thought to understand history lest I would be doomed to repeat it.

And before you state correlation != causation, you’re true...

Dave the diver but instead of diving into the ocean, you’re trying to climb the launderette corporate ladder while running a micro brewery in the evening.

I was using it in my last scrappy startup. We had a shoestring budget so we didn’t want to spend on GitHub copilot at the time, when this was free available, and more full featured.

It didn’t seem to do anything unique, it was just an alternate copilot imo, using aws llms

Brought to you by the ADHD struggle to charge things

Sometimes it’s just a matter of perspective ✨

She’s drinking the cool aid 🥁

This feels like the return of clippy

Ahaha, same immediate response, I also posted the gif before seeing someone else had one as a reply already 😂