AI Horseless Carriages (🔥 Score: 161+ in 2 hours)
Link: https://readhacker.news/s/6tgvf
Comments: https://readhacker.news/c/6tgvf
Link: https://readhacker.news/s/6tgvf
Comments: https://readhacker.news/c/6tgvf
koomen.dev
AI Horseless Carriages | koomen.dev
An essay about bad AI app design
Show HN: Node.js video tutorials where you can edit and run the code (Score: 150+ in 7 hours)
Link: https://readhacker.news/c/6tfHx
Hey HN,
I'm Sindre, CTO of Scrimba (YC S20). We originally launched Scrimba to make video learning more interactive for aspiring frontend developers. So instead of passively watching videos, you can jump in an experiment with the code directly inside the video player. Since launch, almost two million people have used Scrimba to grow their skills.
However, one limitation is that we've only supported frontend code, as our interactive videos run in the browser, whereas most of our learners want to go fullstack—building APIs, handling auth, working with databases, and so forth.
To fix this, we spent the last 6 months integrating StackBlitz WebContainers into Scrimba. This enables a full Node.js environment—including a terminal, shell, npm access, and a virtual file system—directly inside our video player. Everything runs in the browser.
Here is a 2-minute recorded demo: https://scrimba.com/s08dpq3nom
If you want to see more, feel free to enroll into any of the seven fullstack courses we've launched so far, on subject like Node, Next, Express, SQL, Vite, and more. We've opened them up for Hacker News today so that you don't even need to create an account to watch the content:
https://scrimba.com/fullstack
Other notable highlights about our "IDE videos":
- Based on events (code edits, cursor moves, etc) instead of pixels
- Roughly 100x smaller than traditional videos
- Recording is simple: just talk while you code
- Can be embedded in blogs, docs, or courses, like MDN does here: https://developer.mozilla.org/en-US/curriculum/core/css-fund...
- Entirely built in Imba, a language I created myself: https://news.ycombinator.com/item?id=28207662
We think this format could be useful for open-source maintainers and API-focused teams looking to create interactive docs or walkthroughs. Our videos are already embedded by MDN, LangChain, and Coursera.
If you maintain a library or SDK and want an interactive video about it, let us know—happy to record one for free that you can use however you like.
Would love to answer any questions or hear people's feedback!
Link: https://readhacker.news/c/6tfHx
Hey HN,
I'm Sindre, CTO of Scrimba (YC S20). We originally launched Scrimba to make video learning more interactive for aspiring frontend developers. So instead of passively watching videos, you can jump in an experiment with the code directly inside the video player. Since launch, almost two million people have used Scrimba to grow their skills.
However, one limitation is that we've only supported frontend code, as our interactive videos run in the browser, whereas most of our learners want to go fullstack—building APIs, handling auth, working with databases, and so forth.
To fix this, we spent the last 6 months integrating StackBlitz WebContainers into Scrimba. This enables a full Node.js environment—including a terminal, shell, npm access, and a virtual file system—directly inside our video player. Everything runs in the browser.
Here is a 2-minute recorded demo: https://scrimba.com/s08dpq3nom
If you want to see more, feel free to enroll into any of the seven fullstack courses we've launched so far, on subject like Node, Next, Express, SQL, Vite, and more. We've opened them up for Hacker News today so that you don't even need to create an account to watch the content:
https://scrimba.com/fullstack
Other notable highlights about our "IDE videos":
- Based on events (code edits, cursor moves, etc) instead of pixels
- Roughly 100x smaller than traditional videos
- Recording is simple: just talk while you code
- Can be embedded in blogs, docs, or courses, like MDN does here: https://developer.mozilla.org/en-US/curriculum/core/css-fund...
- Entirely built in Imba, a language I created myself: https://news.ycombinator.com/item?id=28207662
We think this format could be useful for open-source maintainers and API-focused teams looking to create interactive docs or walkthroughs. Our videos are already embedded by MDN, LangChain, and Coursera.
If you maintain a library or SDK and want an interactive video about it, let us know—happy to record one for free that you can use however you like.
Would love to answer any questions or hear people's feedback!
They made computers behave like annoying salesmen (Score: 153+ in 4 hours)
Link: https://readhacker.news/s/6tgtq
Comments: https://readhacker.news/c/6tgtq
Link: https://readhacker.news/s/6tgtq
Comments: https://readhacker.news/c/6tgtq
You Wouldn't Steal a Font (🔥 Score: 182+ in 47 minutes)
Link: https://readhacker.news/s/6thaY
Comments: https://readhacker.news/c/6thaY
Link: https://readhacker.news/s/6thaY
Comments: https://readhacker.news/c/6thaY
fedi.rib.gay
Rib :ms_red_panda: (@Rib)
Today Melissa Lewis over on BlueSky pointed out that the font used in the infamous "You wouldn't steal a car" anti-piracy campaign was actually designed by Just van Rossum, whose brother, Guido, created the Python programming language (https://bsky.app/p…
Doge Worker's Code Supports NLRB Whistleblower (🔥 Score: 176+ in 51 minutes)
Link: https://readhacker.news/s/6thkN
Comments: https://readhacker.news/c/6thkN
Link: https://readhacker.news/s/6thkN
Comments: https://readhacker.news/c/6thkN
Krebs on Security
DOGE Worker’s Code Supports NLRB Whistleblower
A whistleblower at the National Labor Relations Board (NLRB) alleged last week that denizens of Elon Musk's Department of Government Efficiency (DOGE) siphoned gigabytes of data from the agency's sensitive case files in early March. The whistleblower said…
Teaching LLMs how to solid model (Score: 150+ in 5 hours)
Link: https://readhacker.news/s/6tgSg
Comments: https://readhacker.news/c/6tgSg
Link: https://readhacker.news/s/6tgSg
Comments: https://readhacker.news/c/6tgSg
willpatrick.xyz
Teaching LLMs how to solid model
It turns out that LLMs can make CAD models for simple 3D mechanical parts. And, I think they’ll be extremely good at it soon.
How to quickly charge your smartphone: fast charging technologies in detail (Score: 150+ in 1 day)
Link: https://readhacker.news/s/6teeJ
Comments: https://readhacker.news/c/6teeJ
Link: https://readhacker.news/s/6teeJ
Comments: https://readhacker.news/c/6teeJ
Shortest-possible walking tour to 81,998 bars in South Korea (Score: 150+ in 4 hours)
Link: https://readhacker.news/s/6thRT
Comments: https://readhacker.news/c/6thRT
Link: https://readhacker.news/s/6thRT
Comments: https://readhacker.news/c/6thRT
Show HN: Rowboat – Open-source IDE for multi-agent systems (Score: 150+ in 1 day)
Link: https://readhacker.news/s/6tdmr
Comments: https://readhacker.news/c/6tdmr
Hi HN! We’re Arjun, Ramnique, and Akhilesh, and we are building Rowboat (https://www.rowboatlabs.com/), an AI-assisted IDE for building and managing multi-agent systems. You start with a single agent, then scale up to teams of agents that work together, use MCP tools, and improve over time - all through a chat-based copilot.
Our repo is https://github.com/rowboatlabs/rowboat, docs are at https://docs.rowboatlabs.com/, and there’s a demo video here: https://youtu.be/YRTCw9UHRbU
It’s becoming clear that real-world agentic systems work best when multiple agents collaborate, rather than having one agent attempt to do everything. This isn’t too surprising - it’s a bit like how good code consists of multiple functions that each do one thing, rather than cramming everything into one function.
For example, a travel assistant works best when different agents handle specialized tasks: one agent finds the best flights, another optimizes hotel selections, and a third organizes the itinerary. This modular approach makes the system easier to manage, debug, and improve over time.
OpenAI’s Agents SDK provides a neat Python library to support this, but building reliable agentic systems requires constant iterations and tweaking - e.g. updating agent instructions (which can quickly get as complex as actual code), connecting tools, and testing the system and incorporating feedback. Rowboat is an AI IDE to do all this. Rowboat is to AI agents what Cursor is to code.
We’ve taken a code-like approach to agent instructions (prompts). There are special keywords to directly reference other agents, tools or prompts - which are highlighted in the UI. The copilot is the best way to create and edit these instructions - each change comes with a code-style diff.
You can give agents access to tools by integrating any MCP server or connecting your own functions through a webhook. You can instruct the agents on when to use specific tools via ‘@mentions’ in the agent instruction. To enable quick testing, we added a way to mock tool responses using LLM calls.
Rowboat playground lets you test and debug the assistants as you build them. You can see agent transfers, tool invocations and tool responses in real-time. The copilot has the context of the chat, and can improve the agent instructions based on feedback. For example, you could say ‘The agent shouldn’t have done x here. Fix this’ and the copilot can go and make this fix.
You can integrate agentic systems built in Rowboat into your application via the HTTP API or the Python SDK (‘pip install rowboat’). For example, you can build user-facing chatbots, enterprise workflows and employee assistants using Rowboat.
We’ve been working with LLMs since GPT-1 launched in 2018. Most recently, we built Coinbase’s support chatbot after our last AI startup was acquired by them.
Rowboat is Apache 2.0 licensed, giving you full freedom to self-host, modify, or extend it however you like.
We’re excited to share Rowboat with everyone here. We’d love to hear your thoughts!
Link: https://readhacker.news/s/6tdmr
Comments: https://readhacker.news/c/6tdmr
Hi HN! We’re Arjun, Ramnique, and Akhilesh, and we are building Rowboat (https://www.rowboatlabs.com/), an AI-assisted IDE for building and managing multi-agent systems. You start with a single agent, then scale up to teams of agents that work together, use MCP tools, and improve over time - all through a chat-based copilot.
Our repo is https://github.com/rowboatlabs/rowboat, docs are at https://docs.rowboatlabs.com/, and there’s a demo video here: https://youtu.be/YRTCw9UHRbU
It’s becoming clear that real-world agentic systems work best when multiple agents collaborate, rather than having one agent attempt to do everything. This isn’t too surprising - it’s a bit like how good code consists of multiple functions that each do one thing, rather than cramming everything into one function.
For example, a travel assistant works best when different agents handle specialized tasks: one agent finds the best flights, another optimizes hotel selections, and a third organizes the itinerary. This modular approach makes the system easier to manage, debug, and improve over time.
OpenAI’s Agents SDK provides a neat Python library to support this, but building reliable agentic systems requires constant iterations and tweaking - e.g. updating agent instructions (which can quickly get as complex as actual code), connecting tools, and testing the system and incorporating feedback. Rowboat is an AI IDE to do all this. Rowboat is to AI agents what Cursor is to code.
We’ve taken a code-like approach to agent instructions (prompts). There are special keywords to directly reference other agents, tools or prompts - which are highlighted in the UI. The copilot is the best way to create and edit these instructions - each change comes with a code-style diff.
You can give agents access to tools by integrating any MCP server or connecting your own functions through a webhook. You can instruct the agents on when to use specific tools via ‘@mentions’ in the agent instruction. To enable quick testing, we added a way to mock tool responses using LLM calls.
Rowboat playground lets you test and debug the assistants as you build them. You can see agent transfers, tool invocations and tool responses in real-time. The copilot has the context of the chat, and can improve the agent instructions based on feedback. For example, you could say ‘The agent shouldn’t have done x here. Fix this’ and the copilot can go and make this fix.
You can integrate agentic systems built in Rowboat into your application via the HTTP API or the Python SDK (‘pip install rowboat’). For example, you can build user-facing chatbots, enterprise workflows and employee assistants using Rowboat.
We’ve been working with LLMs since GPT-1 launched in 2018. Most recently, we built Coinbase’s support chatbot after our last AI startup was acquired by them.
Rowboat is Apache 2.0 licensed, giving you full freedom to self-host, modify, or extend it however you like.
We’re excited to share Rowboat with everyone here. We’d love to hear your thoughts!
GitHub
GitHub - rowboatlabs/rowboat: AI-powered multi-agent builder
AI-powered multi-agent builder. Contribute to rowboatlabs/rowboat development by creating an account on GitHub.
YAGRI: You are gonna read it (Score: 151+ in 8 hours)
Link: https://readhacker.news/s/6thvz
Comments: https://readhacker.news/c/6thvz
Link: https://readhacker.news/s/6thvz
Comments: https://readhacker.news/c/6thvz
Google blocked Motorola use of Perplexity AI, witness says (Score: 150+ in 9 hours)
Link: https://readhacker.news/s/6thms
Comments: https://readhacker.news/c/6thms
Link: https://readhacker.news/s/6thms
Comments: https://readhacker.news/c/6thms
Bloomberg.com
Google Blocked Motorola Use of Perplexity AI, Witness Testifies
Google’s contract with Lenovo Group Ltd.’s Motorola blocked the smartphone maker from setting Perplexity AI as the default assistant on its new devices, an executive of the startup testified at the search giant’s antitrust trial.
Show HN: My from-scratch OS kernel that runs DOOM (Score: 150+ in 6 hours)
Link: https://readhacker.news/s/6thRt
Comments: https://readhacker.news/c/6thRt
Hi there! I've been on-and-off working on TacOS for a few months, which follows some UNIX-derived concepts (exec/fork, unix-style VFS, etc) and is now able to run a port of Doom, with a fairly small amount of modifications, using my from-scratch libc. The performance is actually decent compared to what I expected. Very interested to hear your thoughts. Thank you!
Link: https://readhacker.news/s/6thRt
Comments: https://readhacker.news/c/6thRt
Hi there! I've been on-and-off working on TacOS for a few months, which follows some UNIX-derived concepts (exec/fork, unix-style VFS, etc) and is now able to run a port of Doom, with a fairly small amount of modifications, using my from-scratch libc. The performance is actually decent compared to what I expected. Very interested to hear your thoughts. Thank you!
GitHub
GitHub - UnmappedStack/TacOS: An x86_64 UNIX-like OS from scratch
An x86_64 UNIX-like OS from scratch. Contribute to UnmappedStack/TacOS development by creating an account on GitHub.
Graphics livecoding in Common Lisp (Score: 150+ in 13 hours)
Link: https://readhacker.news/s/6tgMy
Comments: https://readhacker.news/c/6tgMy
Link: https://readhacker.news/s/6tgMy
Comments: https://readhacker.news/c/6tgMy
Kevingal
Graphics livecoding in Common Lisp
Developing a Boids program from scratch without restarting it.
The Future of MCPs (Score: 150+ in 17 hours)
Link: https://readhacker.news/s/6tgEr
Comments: https://readhacker.news/c/6tgEr
Link: https://readhacker.news/s/6tgEr
Comments: https://readhacker.news/c/6tgEr
Substack
MCPs, Gatekeepers, and the Future of AI
MCPs—Model Context Protocols—are set to transform AI from passive chatbots into powerful, action-taking agents. But the real story isn’t what MCPs enable—it’s who controls them.
"Careless People" the book that Meta tried to suppress (🔥 Score: 150+ in 2 hours)
Link: https://readhacker.news/s/6tiAd
Comments: https://readhacker.news/c/6tiAd
Link: https://readhacker.news/s/6tiAd
Comments: https://readhacker.news/c/6tiAd
Hyperwood – Open-Source Furniture (Score: 150+ in 1 day)
Link: https://readhacker.news/s/6tdef
Comments: https://readhacker.news/c/6tdef
Link: https://readhacker.news/s/6tdef
Comments: https://readhacker.news/c/6tdef
CubeCL: GPU Kernels in Rust for CUDA, ROCm, and WGPU (Score: 150+ in 12 hours)
Link: https://readhacker.news/s/6thKd
Comments: https://readhacker.news/c/6thKd
Link: https://readhacker.news/s/6thKd
Comments: https://readhacker.news/c/6thKd
GitHub
GitHub - tracel-ai/cubecl: Multi-platform high-performance compute language extension for Rust.
Multi-platform high-performance compute language extension for Rust. - tracel-ai/cubecl
The hidden cost of AI coding (Score: 150+ in 17 hours)
Link: https://readhacker.news/s/6tgYQ
Comments: https://readhacker.news/c/6tgYQ
Link: https://readhacker.news/s/6tgYQ
Comments: https://readhacker.news/c/6tgYQ
Terrible Software
The Hidden Cost of AI Coding
AI coding tools boost productivity but may sacrifice the flow state and deep satisfaction developers experience when writing code by hand. What are we losing?
First Successful Lightning Triggering and Guiding Using a Drone (Score: 150+ in 17 hours)
Link: https://readhacker.news/s/6th88
Comments: https://readhacker.news/c/6th88
Link: https://readhacker.news/s/6th88
Comments: https://readhacker.news/c/6th88
NTT | Nippon Telegraph and Telephone Corporation
World's First Successful Lightning Triggering and Guiding Using a Drone Protecting cities and infrastructure with a lightning drone—toward…
News Highlights: ◆We have achieved the world's first successful lightn...
I wrote to the address in the GPLv2 license notice (2022) (🔥 Score: 162+ in 1 hour)
Link: https://readhacker.news/s/6tj5s
Comments: https://readhacker.news/c/6tj5s
Link: https://readhacker.news/s/6tj5s
Comments: https://readhacker.news/c/6tj5s
Mendhak
I wrote to the address in the GPLv2 license notice and received the GPLv3 license
I was curious about the 51 Franklin Street address in the GPLv2 license notice so I wrote to them as they said