I've had so much fun writing small apps in pure JS and HTML witj Gemini (no harness or agent, just the free web chat) because it's forced me to keep my index.html below 1000 lines. I love the forced constraints. It's liberating. My day job is wrangling production-level codebases of a monolith service, so my tiny web apps let me live out the fantasy of cutting features instead of adding them.
And you get sandboxxing for free! My company got tailscale recently, and its just the final cherry on top: `tailscale serve` my `/tools`, and I don't even have to worry about auth!
Hash tables are one of those miraculous data structures that, once grokked, take you up a step-function in understanding modern computer science. I'm not talking about the 2018 leetcode meme of "Just solve everything in a hash table". It's more about Array chapter in CS1 where you're told "...and therefore, can retrieval ever go below O(N), or O(logN) if sorted?" and you sit there scratching your head, assuming thats reality and then BAM, the professor reveals hash tables and O(C) retrieval and drops the mic.
What's "alignment" in your context. In bioimaging it usually refers to aligning something to a reference atlas (like the Allen Reference Mouse Brain Atlas) or aligning two microscope channels (like the red channel and green channel)
Sorry, I'm reposting a comment I made yesterday that seems fitting:
> This reminds me of Antirez's "Don't fall into the anti-AI hype". In a sentence: These foundation models are really good at optimizing these extremely high level, extremely well defined problem spaces (ie multiply matrices faster). In Antirez's case, it's "make Redis faster".
When exploring a new idea or tool, my go to prompt is
```
In a single index.html, no dependencies, sparse styling, create an app that <idea>
```
Even before AI, it's how I built small tools, and there's something lovely about being able to email my friends the tool, and tell them "If you want to make a change, toss it to your LLM!"
1. I admit my job is not a good sample of 'job most mortals work'
2. I still think 'most mortals' software devs aren't Antirez, and work in industries or fields that still require a human to bridge the ambiguity gap.
That's fair, and something I've observed too. I wish I had written "the rest of us shouldn't freak out and quit software today".
But here's another data point: At the biotech I work for, writing good code has never been the bottleneck. I actually told my boss that a paid Claude vs free subscription wouldn't be that much value because even if it took every piece of code or algorithm we've ever written and 10x-ed the hell out of them, we'd still be bottlenecked by the biology and physics which dictates that we wait 24 days for our histology assay pipeline.
I have a hunch most fields outside of software are this way. And I'm personally not planning to quit anytime soon.
This reminds me of Antirez's "Don't fall into the anti-AI hype" [0]
In a sentence: These foundation models are really good at optimizing these extremely high level, extremely well defined problem spaces (ie multiply matrices faster). In Antirez's case, it's "make Redis faster".
There have been two reactions: "Oh it would never work for me" and "I have seen months of my life accomplished in an hour", and I think they're both right. I think we should be excited for Antirez, (who has since been popping off [1]), and I think the rest of us should rest easy knowing that LLM's can't (and maybe were never meant to) tackle the tacit-knowledge-filled, human-system-centric, ambiguously-defined-problem-space jobs most mortals work.
I've used Dagster but I can't compare to airflow. But in terms of DX, I've found Dagster pretty easy to use. Instead of writing their own DSL, they have a python library that lets yo tag your pre-made methods as @ops and and string them together into a DAG.
I disagreed, then re-read your post, then re-read the OP, and now I've come full circle to apologize; I think you make a fair point.
I work at a biotech. We spent who knows how much time and money trying to develop a 'lab technician bot' to automate one of our critical assays. Turns out, a 6-figure machine still isn't as economical as my coworker Y, one of the veteran lab-technicians. Sure she takes the occasional sick day but even at our volume (and we do industrial-level, multiple clients batched into a single assay pass) it won't be economical to replace her for a very long time (if we even reach that scale).
I know I'm bandwagoning but just to make sure the signal beats the noise:
- This looks like vibe-code + fake github stars
- There's a difference between "Summarize this verbose report from my the PM so I can get the gist" and "ELI5 this complex subject so I feel like I understand it".