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funerr

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Ask HN: Is SaaS dead?

1 分·作者 funerr·6个月前·1 评论

Ask HN: Any Devtools for Easy Integrations?

1 分·作者 funerr·7个月前·2 评论

Ask HN: PDF JSON Extraction Libraries?

2 分·作者 funerr·11个月前·0 评论

Self-Driving Postgres

postgres.fm
2 分·作者 funerr·11个月前·0 评论

I built a unified Python library for AI batch requests (50% cost savings)

github.com
4 分·作者 funerr·12个月前·4 评论

Pdoc vs. Pdoc3 Controversy

github.com
2 分·作者 funerr·12个月前·0 评论

One-man Lovable competitor sold for $80M

calcalistech.com
4 分·作者 funerr·去年·0 评论

Ask HN: How do you generate long LLM outputs?

1 分·作者 funerr·去年·1 评论

App Generator including Backend using AI

base44.com
2 分·作者 funerr·去年·0 评论

Ask HN: Best AI IDE right now?

4 分·作者 funerr·去年·8 评论

Ask HN: Milestone Based Equity for Developers?

1 分·作者 funerr·去年·1 评论

Ask HN: Why can't Mozilla offer a paid privacy tier?

22 分·作者 funerr·2年前·18 评论

ChatGPT's Prompt Rules Revealed

chatgpt.com
6 分·作者 funerr·2年前·1 评论

The Creativity Lab at UC San Diego

creativity.ucsd.edu
3 分·作者 funerr·2年前·0 评论

Ask HN: Next.js and Python Backend?

3 分·作者 funerr·2年前·9 评论

Ask HN: Vercel for B2B Enterprise SaaS?

2 分·作者 funerr·2年前·0 评论

[untitled]

1 分·作者 funerr·2年前·0 评论

[untitled]

1 分·作者 funerr·2年前·0 评论

Criticisms of the Internet Archive

space.matthewphillips.info
3 分·作者 funerr·2年前·0 评论

Disable Firefox Telemetry Settings

github.com
35 分·作者 funerr·3年前·4 评论

评论

funerr
·4个月前·讨论
I really like cmux for this (https://github.com/manaflow-ai/cmux)
funerr
·7个月前·讨论
ChatGPT summary:

Prototaxites was a massive, trunk-like organism (up to ~8m tall, ~1m wide) that dominated land ~420–370 million years ago, long before trees or complex plants existed. It looked like a tree, but chemical evidence suggests it didn’t photosynthesize. Internally it was made of interwoven microscopic tubes, unlike plant tissue. It’s often described as a giant fungus, but it doesn’t cleanly match modern fungi either, and some researchers think it may represent an entirely extinct branch of eukaryotic life. In other words, early “forests” may have been dominated by something we don’t have a modern analog for.
funerr
·12个月前·讨论
ai-sdk by vercel?
funerr
·12个月前·讨论
When you have LLM requests you don't mind waiting for (up to 24h) then you can save 50% in costs. Great for document processing, image classification at scale, anything that you don't need an immediate result from the LLM provider and costs play a role.
funerr
·12个月前·讨论
I needed a Python library to handle complex batch requests to LLMs (Anthropic & OpenAI) and couldn't find a good one - so I built one.

Batch requests take up to 24h but cut costs by ~50%. Features include structured outputs, automatic cost tracking, state resume after interruptions, and citation support (Anthropic only for now).

It's open-source, feedback/contributions welcome!

GitHub: https://github.com/agamm/batchata
funerr
·去年·讨论
How does this compare to better-auth?
funerr
·去年·讨论
I think it is actually a solid choice given the startup ecosystem and generally easy async nature.
funerr
·2年前·讨论
I met the founders, great people. Any open-source tools to start out dealing with failed payments before we scale?
funerr
·2年前·讨论
I didn't know that about Maybe Finance. Was that what prompted you to os inboxzero?

What are the pros and cons? Aren't you afraid that it makes the SaaS offering less enticing, especially to highly technical people (which seems like might be a big chunk of your potential users)?
funerr
·3年前·讨论
Retool for sure, they are pumping out features really quickly too. The model makes a lot of sense from a developer's point of view. Now that they are also going into public apps I would really consider them seriously.

Hoping for: - Better pricing for public apps. - Better ability to easily customize the frontend design without touching CSS/HTML/JS.
funerr
·3年前·讨论
There are too many variables to predict the future. Yet, I believe that it will empower more 1-3 person businesses to compete with the big incumbents.

Imagine you could run teams of marketing/sales/support ai-agents and focus on your core business. "The next 1B, 1 Person companies".

Just 15 years ago you'd need teams of 10+ people to do basic ml tasks you could do today. Now you have an LLM or a SaaS service that outperforms those teams for the fraction of the cost.