Show HN: Browserbeam – a browser API built for AI agents
2 by nyku | 0 comments on Hacker News.
I often use LLMs to automate different workflows, some of which include browsing the web and gathering data. At some point I started noticing a few things that bothered me: the browser interactions were clunky, as if the agent was struggling to "see" and understand the page, and as a result, many tokens were wasted. Same for knowing when the page is actually ready or not. I started digging deeper and at some point I just bluntly asked in the Cursor chat the following question: "I ask you, as an LLM that uses these headless browsers, what do you wish people would build to make your work easier?" And it worked because I expanded the "Thinking" section and I saw: "The user is asking me a really interesting meta-question ..." and after that it just listed top 10 most painful issues related to the agent<->browser interaction. So I started building a browser API that returns what LLMs actually need, not what browsers return. Fast forward a few weeks and here we are. A REST API built specifically to help LLMs interact with real browsers. Instead of reading raw HTML, you get markdown, page map, short refs (e1, e2) for clicking instead of CSS selectors, a stable flag when the page is ready, diffs after each step, the list of all interactive elements (links, buttons, inputs), automatic blocker dismissal and a small extract step that returns structured JSON from a schema you describe. Official SDKs for Python, TypeScript, Ruby. MCP server for Cursor and Claude Desktop. Would appreciate any feedback, especially on the API design.
Hack Nux
Watch the number of websites being hacked today, one by one on a page, increasing in real time.
New Show Hacker News story: Show HN: DeepTable – an API that converts messy Excel files into structured data
Show HN: DeepTable – an API that converts messy Excel files into structured data
6 by francisrafal | 0 comments on Hacker News.
We tried to build an Excel error checker. To achieve that, we needed to actually understand the semantic structure of a spreadsheet first. So we built that, and it turned out to be the harder, more general problem. The core issue: most real-world spreadsheets aren't relational tables. Merged cells, multi-level headers, multiple tables per sheet, totals mixed in with data. You can't just dump them to CSV and call it done. LLMs handle the easy cases but fall apart on complex workbooks at scale. Our approach uses an agent-guided compilation pipeline that produces SQL-ready relational tables with full cell-level provenance. This demo visualizes what we do: https://ift.tt/peWl7AV... We have a handful of early customers but honestly don't know yet whether this is a real market or a niche problem. We're posting this to hear from people who've dealt with arbitrary spreadsheet ingestion. Whether you solved it, gave up, or are still living with the pain. If you want to try it on your own files, email me (see my profile for my email) and I'll give you API access.
6 by francisrafal | 0 comments on Hacker News.
We tried to build an Excel error checker. To achieve that, we needed to actually understand the semantic structure of a spreadsheet first. So we built that, and it turned out to be the harder, more general problem. The core issue: most real-world spreadsheets aren't relational tables. Merged cells, multi-level headers, multiple tables per sheet, totals mixed in with data. You can't just dump them to CSV and call it done. LLMs handle the easy cases but fall apart on complex workbooks at scale. Our approach uses an agent-guided compilation pipeline that produces SQL-ready relational tables with full cell-level provenance. This demo visualizes what we do: https://ift.tt/peWl7AV... We have a handful of early customers but honestly don't know yet whether this is a real market or a niche problem. We're posting this to hear from people who've dealt with arbitrary spreadsheet ingestion. Whether you solved it, gave up, or are still living with the pain. If you want to try it on your own files, email me (see my profile for my email) and I'll give you API access.
New ask Hacker News story: LinkedIn uses 65GB of RAM with 7 tabs opened
LinkedIn uses 65GB of RAM with 7 tabs opened
3 by daniele_dll | 1 comments on Hacker News.
https://ibb.co/605p8bP3 A couple of months ago my machine became totally unusable and wasn't understanding why, however after a quick check I discovered the ram was full and the swap as well. After discovering that chrome ate more than half of my ram I checked out the ram consumption on chrome and I was shocked 65GB it's just insane. (ram bought a couple of years ago)
3 by daniele_dll | 1 comments on Hacker News.
https://ibb.co/605p8bP3 A couple of months ago my machine became totally unusable and wasn't understanding why, however after a quick check I discovered the ram was full and the swap as well. After discovering that chrome ate more than half of my ram I checked out the ram consumption on chrome and I was shocked 65GB it's just insane. (ram bought a couple of years ago)
New ask Hacker News story: Ask HN: Does anyone else notice that gas runs out faster than usual
Ask HN: Does anyone else notice that gas runs out faster than usual
3 by cat-turner | 4 comments on Hacker News.
- gas smells less like gas - not getting as much mileage as usual I filled up my car and I have a habit of resetting my mileage tracker (next to odometer) to see how many miles I get out of a full tank. I've noticed that I get much less gas than usual for the same number of bars. What can I do to make this more concrete? Has anyone else noticed this?
3 by cat-turner | 4 comments on Hacker News.
- gas smells less like gas - not getting as much mileage as usual I filled up my car and I have a habit of resetting my mileage tracker (next to odometer) to see how many miles I get out of a full tank. I've noticed that I get much less gas than usual for the same number of bars. What can I do to make this more concrete? Has anyone else noticed this?
New Show Hacker News story: Show HN: Rusdantic
Show HN: Rusdantic
2 by mmgehlot | 0 comments on Hacker News.
A unified, high-performance data validation and serialization framework for Rust, inspired by Pydantic's ergonomics and powered by Serde.
2 by mmgehlot | 0 comments on Hacker News.
A unified, high-performance data validation and serialization framework for Rust, inspired by Pydantic's ergonomics and powered by Serde.
New ask Hacker News story: Are you team MCP or team CLI?
Are you team MCP or team CLI?
2 by sharath39 | 4 comments on Hacker News.
Bonus point is you say why.
2 by sharath39 | 4 comments on Hacker News.
Bonus point is you say why.
New ask Hacker News story: Ask HN: Release Path for 'Transformers Alternatives'?
Ask HN: Release Path for 'Transformers Alternatives'?
2 by adinhitlore | 0 comments on Hacker News.
So, a side project I've spent/wasted ~1000 hours on, with 2 goals set in mind: 1. faster than transformers on CPU; 2. smarter than transformers. couple of screenshots below (the black/red part are censored on purpose...for now): https://ift.tt/fAtrWK7 https://ift.tt/LEhmjsG https://ift.tt/G5W3H2Q Summary: what the hell is this? Two architectures - 1. Linear RNN which solves the long memory problem in current front-runner RNN transformer alternatives (RWKV, Mamba), in addition to being cpu friendly and entirely in C from scratch, but not too big: ~4000 lines. 2. 2 SNN experimental programs (in C originally but also ported to C# and F#) that turned out to be better than expected but unfortunately for the time being: dumber than the linear RNN one (i need more tests). The question is: what to do with them? google gemini pro 3.1/sonnet 4.6 told me to patent, IP, estimating value in the many millions and while this is clearly a mistake: I've uploaded all the code to claude/gemini for analysis though seeing how the project is ~70% vibecoded I think it would be snobby to act like a gatekeeper. The thing is: I don't want millions but at the same time i see several issues with fee open source rollout: * completely unalighned, i don't believe in the "agi hype" but potential risks may exist, such as in cybersecurity; * I frankly hate Xai and Musk and since the companies who may be interested in running AI models as b2c solution are likely ~20, one of them will be xai. * Very unorthodox implementation: All in C with ports in c#/f#. No python or rust, which would mean likely some people unfamiliar with these languages in ML running into issues so i'd have to support nonstop which is time consuming and let's face it i'll have to do it for free once it's open source. * It may die completely unheard of somewhere on GitHub even if it has potential, organic traffic rarely works unless you hit the lottery. This is NOT a flex btw, I'm convinced there are programmers better than me, people who understand ML better than me, mathematicians better than me though frankly I posses special kind of persistence combined with arrogance which goes a long way in terms of technology/inventions/novelty. Like i said this is the results of hundreds of hours work spiced up by many years programming experience in other areas, this wasn't one weekend "claude, give me agi" kind of shot. All of the projects compile with zero warnings, logically seem to work and are visibly faster than transformers with obvious ability to generalize and create new/unique content. The missing part is scaling and benchmarking on classic benchmarks. What I lack is understanding adoption of technology.10x!
2 by adinhitlore | 0 comments on Hacker News.
So, a side project I've spent/wasted ~1000 hours on, with 2 goals set in mind: 1. faster than transformers on CPU; 2. smarter than transformers. couple of screenshots below (the black/red part are censored on purpose...for now): https://ift.tt/fAtrWK7 https://ift.tt/LEhmjsG https://ift.tt/G5W3H2Q Summary: what the hell is this? Two architectures - 1. Linear RNN which solves the long memory problem in current front-runner RNN transformer alternatives (RWKV, Mamba), in addition to being cpu friendly and entirely in C from scratch, but not too big: ~4000 lines. 2. 2 SNN experimental programs (in C originally but also ported to C# and F#) that turned out to be better than expected but unfortunately for the time being: dumber than the linear RNN one (i need more tests). The question is: what to do with them? google gemini pro 3.1/sonnet 4.6 told me to patent, IP, estimating value in the many millions and while this is clearly a mistake: I've uploaded all the code to claude/gemini for analysis though seeing how the project is ~70% vibecoded I think it would be snobby to act like a gatekeeper. The thing is: I don't want millions but at the same time i see several issues with fee open source rollout: * completely unalighned, i don't believe in the "agi hype" but potential risks may exist, such as in cybersecurity; * I frankly hate Xai and Musk and since the companies who may be interested in running AI models as b2c solution are likely ~20, one of them will be xai. * Very unorthodox implementation: All in C with ports in c#/f#. No python or rust, which would mean likely some people unfamiliar with these languages in ML running into issues so i'd have to support nonstop which is time consuming and let's face it i'll have to do it for free once it's open source. * It may die completely unheard of somewhere on GitHub even if it has potential, organic traffic rarely works unless you hit the lottery. This is NOT a flex btw, I'm convinced there are programmers better than me, people who understand ML better than me, mathematicians better than me though frankly I posses special kind of persistence combined with arrogance which goes a long way in terms of technology/inventions/novelty. Like i said this is the results of hundreds of hours work spiced up by many years programming experience in other areas, this wasn't one weekend "claude, give me agi" kind of shot. All of the projects compile with zero warnings, logically seem to work and are visibly faster than transformers with obvious ability to generalize and create new/unique content. The missing part is scaling and benchmarking on classic benchmarks. What I lack is understanding adoption of technology.10x!