jtmarmon

Ditto - using the macbook trackpad, if relevant

My guess is that, in the vein of the "monitor flickering" symptom, your PC sees the DP/HDMI cable disconnect and reconnect due to the static. The reconnection wakes it up.

I pretty much only use o1 for more rigorous tasks (coding/math). Eg the other day I gave it the tax rates for my area and used it to explore different tax scenarios

I’m no expert on docker but I thought the hashes for each layer would already be computed if your image is built

Great writeup. To add an example, I personally use JSON for most of my work, but have found myself using XML for certain AI use cases that require annotating an original text.

For example, if I wanted an AI to help me highlight to the user where in a body of text I mentioned AI, I might have it return something like:

<text>Great writeup. To add an example, I personally use JSON for most of my work, but have found myself using XML for certain <ai-mention>AI</ai-mention> use cases that require annotating an original text with segments.</text>

I recently evaluated Dagster, Prefect, and Flyte for a data pipeliney workflow and ended up going with Temporal.

The shared feature between Temporal and those three is the workflow orchestration piece. All 3 can manage a dependency graph of jobs, handle retries, start from checkpoints, etc.

At a high level the big reason they’re different is Temporal is entirely focused on the orchestration piece, and the others are much more focused on the data piece, which comes out in a lot of the different features. Temporal has SDKs in most languages, and has a queuing system that allows you to run different workflows or even activities (tasks within a workflow) in different workers, manage concurrency, etc. You can write a parent workflow that orchestrates sub-workflows that could live in 5 other services. It’s just really composable and fits much more nicely into the critical path of your app.

Prefect is probably the closest of your list to temporal, in that it’s less opinionated than others about the workflows being “data oriented”, but it’s still only in python, and it deosn't have queueing. In short this means that your workflows are kinda supposed to run in one box running python somewhere. Temporal will let you define a 10 part workflow where two parts run on a python service running with a GPU, and the remaining parts are running in the same node.js process as your main server.

Dagster’s feature set is even more focused on data-workflows, as your workflows are meant to produce data “assets” which can be materialized/cached, etc.

They’re pretty much all designed for a data engineering team to manage many individual pipelines that are external from your application code, whereas temporal is designed to be a system that manages workflow complexity for code that (more often) runs in your application.

This is a pretty good way to go bankrupt when you have a real health emergency

EDIT: I doubt OP is reading this but I would highly recommend they get insurance before giving birth...sure, they won't cover your at home birth, but they will cover your hospital stay if you end up having potentially fatal complications

Slow build times make everything slower, including refactoring tech debt (which means people are less likely to do it).

Congrats on the launch, looks like a great product.

Out of curiosity - the demo on the site suggests the local first latency is like 10-40 ms. I would think reading/writing to SQLite locally would be on the order of 1ms or less. Why is that?