The best Hacker News stories from Show from the past day
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Show HN: Rust based AWS Lambda Logs Viewer (TUI)
My first Rust program with support from Cursor :)). few days for idea. 1 night for "talk and fight" with Cursor
Show HN: Rust based AWS Lambda Logs Viewer (TUI)
My first Rust program with support from Cursor :)). few days for idea. 1 night for "talk and fight" with Cursor
Show HN: Rust based AWS Lambda Logs Viewer (TUI)
My first Rust program with support from Cursor :)). few days for idea. 1 night for "talk and fight" with Cursor
Show HN: Pneumatic – free open-source workflow software
Hi HN,<p>I'm one of the co-founders of Pneumatic, an enterprise-grade workflow software designed for small, fast-growing startups.<p>Yesterday, we released Pneumatic under the Apache 2.0 license.<p>If your team has used Trello, Basecamp, or Asana before and you're now looking to implement a more structured, mature approach by building repeatable task sequences, you should try Pneumatic.<p>Here's what Pneumatic offers:<p>- Task sequences defined by templates. Design a template once and run multiple instances of a process based on this reusable template—manually, via API, or with a public share kick-off form.<p>- An intuitive, user-friendly Workflow Template Editor.<p>- Workflow conditions to skip tasks or create branches.<p>- Dynamic task performer assignment: defined by the template or variable, based on conditions.<p>- Email, mobile, push, and REST notifications for all major events, such as when workflows start/stop, tasks start/stop, mentions, and more.<p>- Support for parallel tasks. And much more.<p>Some of the most popular use cases include chains of approvals, employee or customer onboarding, software development and design processes, and content creation workflows for teams.<p>I’d love your feedback and questions. You can reach me at anton.seidler@pneumatic.app
Show HN: Pneumatic – free open-source workflow software
Hi HN,<p>I'm one of the co-founders of Pneumatic, an enterprise-grade workflow software designed for small, fast-growing startups.<p>Yesterday, we released Pneumatic under the Apache 2.0 license.<p>If your team has used Trello, Basecamp, or Asana before and you're now looking to implement a more structured, mature approach by building repeatable task sequences, you should try Pneumatic.<p>Here's what Pneumatic offers:<p>- Task sequences defined by templates. Design a template once and run multiple instances of a process based on this reusable template—manually, via API, or with a public share kick-off form.<p>- An intuitive, user-friendly Workflow Template Editor.<p>- Workflow conditions to skip tasks or create branches.<p>- Dynamic task performer assignment: defined by the template or variable, based on conditions.<p>- Email, mobile, push, and REST notifications for all major events, such as when workflows start/stop, tasks start/stop, mentions, and more.<p>- Support for parallel tasks. And much more.<p>Some of the most popular use cases include chains of approvals, employee or customer onboarding, software development and design processes, and content creation workflows for teams.<p>I’d love your feedback and questions. You can reach me at anton.seidler@pneumatic.app
Show HN: PreCog AI – Automatic AI Model Selection for Any Task
Hi HN,<p>I'm one of the co-founders of PreCog AI, a project my friend and I started to make the best AI models more accessible. PreCog AI is a chatbot that automatically picks and answers with the best AI model for whatever task you throw at it.<p>We made PreCog public on Monday and are getting great feedback. Originally built as an internal tool to help our small team reduce costs (paying for various chatbots) and get better AI output, PreCog has helped us so much with our workflow and ideation that we just had to share it.<p>Key Features of PreCog
- AI Model Matchmaking: With access to 18 models, PreCog automatically matches your questions with the most fitting AI model based on the task.<p>- Versatile Adaptation: Works with any task, from coding to creative writing, giving you the right tool for the job.<p>-Ongoing Updates: Stay current with AI advancements using the latest LLM leaderboard data (we are constantly adding and changing our leaderboard). See the leaderboard here - <a href="https://precog.ubik.studio/leaderboard" rel="nofollow">https://precog.ubik.studio/leaderboard</a><p>-Preferred Model Selection: If you have a preferred model, choose it, and PreCog will use that model exclusively to respond.<p>How PreCog Works:<p>PreCog analyzes your query, references the model leaderboard, and then matches your query with the highest-ranked AI for that niche task. Delivering high-quality, task-specific output. PreCog's Model Leaderboard ranks AI models through over a million human comparisons, evaluated and presented on an Elo-scale. The dataset used to build the PreCog Leaderboard is from ChatBot Arena by <a href="https://lmarena.ai/" rel="nofollow">https://lmarena.ai/</a>. Researchers from UC Berkeley SkyLab and LMSYS developed the battle framework to produce the dataset.<p>I love feedback, questions, and critiques it helps me and my friend develop with the user in mind.<p>You can reach me at anytime at:
info@ubik.studio
Show HN: PreCog AI – Automatic AI Model Selection for Any Task
Hi HN,<p>I'm one of the co-founders of PreCog AI, a project my friend and I started to make the best AI models more accessible. PreCog AI is a chatbot that automatically picks and answers with the best AI model for whatever task you throw at it.<p>We made PreCog public on Monday and are getting great feedback. Originally built as an internal tool to help our small team reduce costs (paying for various chatbots) and get better AI output, PreCog has helped us so much with our workflow and ideation that we just had to share it.<p>Key Features of PreCog
- AI Model Matchmaking: With access to 18 models, PreCog automatically matches your questions with the most fitting AI model based on the task.<p>- Versatile Adaptation: Works with any task, from coding to creative writing, giving you the right tool for the job.<p>-Ongoing Updates: Stay current with AI advancements using the latest LLM leaderboard data (we are constantly adding and changing our leaderboard). See the leaderboard here - <a href="https://precog.ubik.studio/leaderboard" rel="nofollow">https://precog.ubik.studio/leaderboard</a><p>-Preferred Model Selection: If you have a preferred model, choose it, and PreCog will use that model exclusively to respond.<p>How PreCog Works:<p>PreCog analyzes your query, references the model leaderboard, and then matches your query with the highest-ranked AI for that niche task. Delivering high-quality, task-specific output. PreCog's Model Leaderboard ranks AI models through over a million human comparisons, evaluated and presented on an Elo-scale. The dataset used to build the PreCog Leaderboard is from ChatBot Arena by <a href="https://lmarena.ai/" rel="nofollow">https://lmarena.ai/</a>. Researchers from UC Berkeley SkyLab and LMSYS developed the battle framework to produce the dataset.<p>I love feedback, questions, and critiques it helps me and my friend develop with the user in mind.<p>You can reach me at anytime at:
info@ubik.studio
Show HN: PreCog AI – Automatic AI Model Selection for Any Task
Hi HN,<p>I'm one of the co-founders of PreCog AI, a project my friend and I started to make the best AI models more accessible. PreCog AI is a chatbot that automatically picks and answers with the best AI model for whatever task you throw at it.<p>We made PreCog public on Monday and are getting great feedback. Originally built as an internal tool to help our small team reduce costs (paying for various chatbots) and get better AI output, PreCog has helped us so much with our workflow and ideation that we just had to share it.<p>Key Features of PreCog
- AI Model Matchmaking: With access to 18 models, PreCog automatically matches your questions with the most fitting AI model based on the task.<p>- Versatile Adaptation: Works with any task, from coding to creative writing, giving you the right tool for the job.<p>-Ongoing Updates: Stay current with AI advancements using the latest LLM leaderboard data (we are constantly adding and changing our leaderboard). See the leaderboard here - <a href="https://precog.ubik.studio/leaderboard" rel="nofollow">https://precog.ubik.studio/leaderboard</a><p>-Preferred Model Selection: If you have a preferred model, choose it, and PreCog will use that model exclusively to respond.<p>How PreCog Works:<p>PreCog analyzes your query, references the model leaderboard, and then matches your query with the highest-ranked AI for that niche task. Delivering high-quality, task-specific output. PreCog's Model Leaderboard ranks AI models through over a million human comparisons, evaluated and presented on an Elo-scale. The dataset used to build the PreCog Leaderboard is from ChatBot Arena by <a href="https://lmarena.ai/" rel="nofollow">https://lmarena.ai/</a>. Researchers from UC Berkeley SkyLab and LMSYS developed the battle framework to produce the dataset.<p>I love feedback, questions, and critiques it helps me and my friend develop with the user in mind.<p>You can reach me at anytime at:
info@ubik.studio
Show HN: I made a Bluesky video downloader
Hey HN,<p>Recently, a friend introduced me to the Bluesky platform, and I found it intriguing—especially its focus on decentralization. I believe it has the potential to become the next Twitter, and it already has over 13 million users.<p>Today, as I was browsing the platform, I came across a video in one of the posts that I found really interesting and wanted to download to my local drive. However, after searching for a while, I couldn’t find a suitable tool for this purpose.<p>So, I thought, why not create a tool to meet this need? All it should require is the link to a post, and it would allow users to download the embedded video directly to their local storage.<p>With Cursor’s help, I managed to complete this tool in just one day. It’s now fully functional and can download videos from Bluesky posts.<p>I'm thrilled to share this tool with everyone, and I hope you find it useful.<p>would love your feedback pls<p>Charles
Show HN: TypeSchema – A JSON specification to describe data models
Show HN: TypeSchema – A JSON specification to describe data models
Show HN: TypeSchema – A JSON specification to describe data models
Show HN: TypeSchema – A JSON specification to describe data models
Show HN: TypeSchema – A JSON specification to describe data models
Show HN: TypeSchema – A JSON specification to describe data models
Show HN: Which animal shares your body fat percentage?
I recently came across a youtube video about animals and their average body fat percentages.I thought it would be fun to compare my body fat to different animals and see which one I most resemble. This idea spiraled into a two-hour project, where I turned the data from the video into a JSON file, asked chatgpt to help create a UI, and deployed the whole thing on netlify. Pretty cool how fast we can quickly build random projects like this 10x faster with llms!<p>Now that I’m typing this, I still have no clue why I made this... but here it is. Enjoy!
Show HN: Satoshi9000 analog BTC key generator (mechanical)
I built this machine so I could generate Bitcoin keys that I could trust. Air-gapped and simple to use and understand (mechanical).<p>The Satoshi 9000 demo: <a href="https://youtu.be/bJiOia5PoGE" rel="nofollow">https://youtu.be/bJiOia5PoGE</a><p>The key value proposition of the machine is that it generates analog randomness in the physical world and converts it into digital (1’s and 0’s) randomness. Seamlessly.<p>But it occurs to me that it may have other uses beyond crypto keys for your own use, such as:
* Randomized clinical trials. Clinical trials need a high degree of transparency for ethical reasons; also, for legal reasons should it come to light after the trial has ended that patient selection and treatment selection was not random or in some way biased (say, by the researchers themselves). The machine described herein can provide that transparency to young and old patients, technical and non- technical.
* Non-technical management. Many network engineers in need of security keys have bosses that are non-technical. Such managers might prefer security keys (and their generation) which are easier for them to understand.
* Estate planning. Suppose members of a family were to inherit digital assets (such as
Bitcoin, for example). Not all members of the family are technical and understand Bitcoin. However, each will still need to generate a secure Bitcoin key to receive their share of the inheritance. The machine described herein might help in that task because its source of randomness is more easily understood by laypeople and each can generate their own private key in private (in isolation with the machine).
* Anywhere where the users have to have an intuitive understanding of how the randomness is being created; whether they are 5 years old, or 95 years old, and all ages in between.<p>I'm curious to know if any of the folks over at HN can think of other use cases?
Show HN: Satoshi9000 analog BTC key generator (mechanical)
I built this machine so I could generate Bitcoin keys that I could trust. Air-gapped and simple to use and understand (mechanical).<p>The Satoshi 9000 demo: <a href="https://youtu.be/bJiOia5PoGE" rel="nofollow">https://youtu.be/bJiOia5PoGE</a><p>The key value proposition of the machine is that it generates analog randomness in the physical world and converts it into digital (1’s and 0’s) randomness. Seamlessly.<p>But it occurs to me that it may have other uses beyond crypto keys for your own use, such as:
* Randomized clinical trials. Clinical trials need a high degree of transparency for ethical reasons; also, for legal reasons should it come to light after the trial has ended that patient selection and treatment selection was not random or in some way biased (say, by the researchers themselves). The machine described herein can provide that transparency to young and old patients, technical and non- technical.
* Non-technical management. Many network engineers in need of security keys have bosses that are non-technical. Such managers might prefer security keys (and their generation) which are easier for them to understand.
* Estate planning. Suppose members of a family were to inherit digital assets (such as
Bitcoin, for example). Not all members of the family are technical and understand Bitcoin. However, each will still need to generate a secure Bitcoin key to receive their share of the inheritance. The machine described herein might help in that task because its source of randomness is more easily understood by laypeople and each can generate their own private key in private (in isolation with the machine).
* Anywhere where the users have to have an intuitive understanding of how the randomness is being created; whether they are 5 years old, or 95 years old, and all ages in between.<p>I'm curious to know if any of the folks over at HN can think of other use cases?
Show HN: Satoshi9000 analog BTC key generator (mechanical)
I built this machine so I could generate Bitcoin keys that I could trust. Air-gapped and simple to use and understand (mechanical).<p>The Satoshi 9000 demo: <a href="https://youtu.be/bJiOia5PoGE" rel="nofollow">https://youtu.be/bJiOia5PoGE</a><p>The key value proposition of the machine is that it generates analog randomness in the physical world and converts it into digital (1’s and 0’s) randomness. Seamlessly.<p>But it occurs to me that it may have other uses beyond crypto keys for your own use, such as:
* Randomized clinical trials. Clinical trials need a high degree of transparency for ethical reasons; also, for legal reasons should it come to light after the trial has ended that patient selection and treatment selection was not random or in some way biased (say, by the researchers themselves). The machine described herein can provide that transparency to young and old patients, technical and non- technical.
* Non-technical management. Many network engineers in need of security keys have bosses that are non-technical. Such managers might prefer security keys (and their generation) which are easier for them to understand.
* Estate planning. Suppose members of a family were to inherit digital assets (such as
Bitcoin, for example). Not all members of the family are technical and understand Bitcoin. However, each will still need to generate a secure Bitcoin key to receive their share of the inheritance. The machine described herein might help in that task because its source of randomness is more easily understood by laypeople and each can generate their own private key in private (in isolation with the machine).
* Anywhere where the users have to have an intuitive understanding of how the randomness is being created; whether they are 5 years old, or 95 years old, and all ages in between.<p>I'm curious to know if any of the folks over at HN can think of other use cases?
Show HN: RF Hunter – Find hidden cameras and other devices
This project is an RF Signal Scanner built using an ESP32, AD8317 RF detector, and various other components. It's designed to detect and measure RF signals in the environment and display the signal strength on an OLED display. It's useful to find hidden cameras, wiretapping devices, and other RF-enabled devices.