stopachka
Every student is cheating with AI
From Matmul to Meaning
The Productivity Mirage
Core dump epidemiology: fixing an 18-year-old bug
Core dump epidemiology: fixing an 18-year-old bug
Show HN: Baserates.dev, memorize programmer napkin math
When I began my career in programming I remember reading Jeff Dean's "Latency Numbers Every Programmer Should Know" [1], and getting inspired. Alas, it's been over a decade, and I never fully internalized all the numbers.Until recently. I discovered Simon Eskildsen's talk [2] and github repo [3] on programmer napkin math. I liked his reasoning, and decided to _actually_ internalize the numbers...
Project Fetch: Phase Two
> It is highly unlikely that an AI agent startup becomes wealthy by creating the best harness for a particular use case.
If it's not the harness, what do you think is the thing that will differentiate AI agent startups? Is it mainly data, or something else?
Turing Conjugation
Vibe Diaries: Training Nanochat
I wonder what in the training / system prompt causes Claude to do this.
The most complex model we understand [video]
AFAIK you would get about ~5 concurrent users, with a max context window of ~128K tokens on the larger models.
This wouldn't be good enough for coding -- are you guys thinking of using it for something else?
We added it to help the app builders that do a lot of caching get unique responses. Turns out even if you set no-store cache headers, some app builders cache the pages. We tested this idea with those app builders and saw that they did generate uuids each time.
I think it could be. Consider an argument like this:
It's valuable to ask ChatGPT questions and receive text responses. Some of the responses are more valuable when they don't just return text, but some markup: bolding, adding visualizations etc. Why can't some responses be more valuable if they return little apps?
One place where I've wanted this myself are with using LLMs for long-running goals I have. For example, I do my blood work about once a year, and I use the results to make changes and track. For a long time I had a long chat thread with ChatGPT. Now I have a little app instead.
An extreme version of this starts to turn responses into more and more fully-fledged apps. I did an experiment recently with creating a personal finance app. I found customizing the app to my specific needs made it much more valuable to me then generic personal finance apps, which have much more effort put it, but aren't tailored to my needs [^1]
[^1]: more on this experiment here: https://x.com/stopachka/status/2040982623636607009
We hope delightful experiences like that then prod hackers to dive deeper and use Instant for startups.
1. For the users table specifically, we have a default rule that says `"view": "auth.id == data.id"`. This way even if the the user (or AI) did not set access controls, user data is protected by default.
2. In the instructions file given to the agent (https://www.getadb.com/provision/new), we specifically mention permissions and how to push them. We found this prods the agent to push perms.
In practice many GET requests don't adhere to this spec. For example, when you load a page, your "view" generally changes lots of things on the backend. Those changes come back to you in ways too: for example, consider view counts on Youtube videos or X posts.