The best Hacker News stories from Show from the past day
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Show HN: Powerful Visual Programming Language (Book)
Throughout my 30+ software development career, after spending many sleepless nights digging up through enormous codebases to understand logic or fix a bug, I was thinking: "There must be a better, visual way to represent program rather than text". However, no usable visual programming language popped up on horizon for the whole duration of 30+ years of my career. Therefore, I decided to take matters in my own hands, creating new visual programming language called "Pipe". A book about this language was published recently. The book is available for free on Amazon Kindle and Apple iBooks.<p>Language Pipe has a level of sophistication and power comparable to existing most powerful textual languages and therefore, it has a very high chances to successfully compete with text-based programming. The book provides full and comprehensive language specification. On top of that, the book contains many features and ideas planned for future versions of the language.<p>Pipe implements many novel concepts and unique features. As a result, multiple patent applications have already been filed and pending. The published book contains complete language specification, including graphical notation of all its elements and full API specification for code integration. Pipe has the following features:<p>* General-purpose visual language.<p>* Compact but powerful language.<p>* Complete and detailed language specification.<p>* Practical visual language.<p>* API specification for integration with non-visual languages.<p>* Statically-typed language.<p>* Long-term plans for future versions.<p>* Augmentation of AI code generation.<p>* Language for the next generation of low-code systems.<p>The problem of AI code generation is that it is very difficult to prepare complete and precise input specifications, especially in case of a large project. The solution is generating code only for base-level components easily explainable to AI, completing the rest of application via manual coding. That, however, undermines the goal of leveraging AI to remove the need for human programming. Pipe provides an alternative to textual coding by encapsulating AI-generated components within visual blocks for building the rest of application as graphical workflows via an intuitive drag-and-drop interface. As a next level of Pipe evolution, AI will be generating complete visual workflows directly, making it much easier to understand and modify generated logic.<p>Usage of a general-purpose visual programming language Pipe to connect blocks containing AI-generated code can inspire the next generation of extremely versatile low-code platforms, as AI code generation followed by visual integration of generated components is a very powerful low-code framework. Users will be able to generate new components using AI and that solves the problem of limited customization in existing low-code platforms where components are mostly predefined. On top of that, common visual programming language Pipe will ensure portability of low-code projects between different platforms.<p>Please find PDF with book preview here: <a href="https://www.pipelang.com/sample/sample.pdf" rel="nofollow">https://www.pipelang.com/sample/sample.pdf</a>
Show HN: FLE v0.3 – Claude Code Plays Factorio
We're excited to release v0.3.0 of the Factorio Learning Environment (FLE), an open-source environment for evaluating AI agents on long-horizon planning, spatial reasoning, and automation tasks.<p>== What is FLE? ==<p>FLE uses the game Factorio to test whether AI can handle complex, open-ended engineering challenges. Agents write Python code to build automated factories, progressing from simple resource extraction (~30 units/min) to sophisticated production chains (millions of units/sec).<p>== What's new in 0.3.0 ==<p>- Headless scaling: No longer needs the game client, enabling massive parallelization!<p>- OpenAI Gym compatibility: Standard interface for RL research<p>- Claude Code integration: We're livestreaming Claude playing Factorio [on Twitch](<a href="http://twitch.tv/playsfactorio" rel="nofollow">http://twitch.tv/playsfactorio</a>)<p>- Better tooling and SDK: 1-line CLI commands to run evaluations (with W&B logging)<p>== Key findings ==<p>We evaluated frontier models (Claude Opus 4.1, GPT-5, Gemini 2.5 Pro, Grok 4) on 24 production automation tasks of increasing complexity.<p>Even the best models struggle:<p>- Most models still rely on semi-manual strategies rather than true automation<p>- Agents rarely define helper functions or abstractions, limiting their ability to scale<p>- Error recovery remains difficult – agents often get stuck in repetitive failure loops<p>The performance gap between models on FLE correlates more closely with real-world task benchmarks (like GDPVal) than with traditional coding/reasoning evals.<p>== Why this matters ==<p>Unlike benchmarks based on exams that saturate quickly, Factorio's exponential complexity scaling means there's effectively no performance ceiling. The skills needed - system debugging, constraint satisfaction, logistics optimization - transfer directly to real challenges.<p>== Try it yourself ==<p>>>> uv add factorio-learning-environment<p>>>> uv add "factorio-learning-environment[eval]"<p>>>> fle cluster start<p>>>> fle eval --config configs/gym_run_config.json<p>We're looking for researchers, engineers, and modders interested in pushing the boundaries of agent capabilities. Join our Discord if you want to contribute. We look forward to meeting you and seeing what you can build!<p>-- FLE Team
Show HN: FLE v0.3 – Claude Code Plays Factorio
We're excited to release v0.3.0 of the Factorio Learning Environment (FLE), an open-source environment for evaluating AI agents on long-horizon planning, spatial reasoning, and automation tasks.<p>== What is FLE? ==<p>FLE uses the game Factorio to test whether AI can handle complex, open-ended engineering challenges. Agents write Python code to build automated factories, progressing from simple resource extraction (~30 units/min) to sophisticated production chains (millions of units/sec).<p>== What's new in 0.3.0 ==<p>- Headless scaling: No longer needs the game client, enabling massive parallelization!<p>- OpenAI Gym compatibility: Standard interface for RL research<p>- Claude Code integration: We're livestreaming Claude playing Factorio [on Twitch](<a href="http://twitch.tv/playsfactorio" rel="nofollow">http://twitch.tv/playsfactorio</a>)<p>- Better tooling and SDK: 1-line CLI commands to run evaluations (with W&B logging)<p>== Key findings ==<p>We evaluated frontier models (Claude Opus 4.1, GPT-5, Gemini 2.5 Pro, Grok 4) on 24 production automation tasks of increasing complexity.<p>Even the best models struggle:<p>- Most models still rely on semi-manual strategies rather than true automation<p>- Agents rarely define helper functions or abstractions, limiting their ability to scale<p>- Error recovery remains difficult – agents often get stuck in repetitive failure loops<p>The performance gap between models on FLE correlates more closely with real-world task benchmarks (like GDPVal) than with traditional coding/reasoning evals.<p>== Why this matters ==<p>Unlike benchmarks based on exams that saturate quickly, Factorio's exponential complexity scaling means there's effectively no performance ceiling. The skills needed - system debugging, constraint satisfaction, logistics optimization - transfer directly to real challenges.<p>== Try it yourself ==<p>>>> uv add factorio-learning-environment<p>>>> uv add "factorio-learning-environment[eval]"<p>>>> fle cluster start<p>>>> fle eval --config configs/gym_run_config.json<p>We're looking for researchers, engineers, and modders interested in pushing the boundaries of agent capabilities. Join our Discord if you want to contribute. We look forward to meeting you and seeing what you can build!<p>-- FLE Team
Show HN: FLE v0.3 – Claude Code Plays Factorio
We're excited to release v0.3.0 of the Factorio Learning Environment (FLE), an open-source environment for evaluating AI agents on long-horizon planning, spatial reasoning, and automation tasks.<p>== What is FLE? ==<p>FLE uses the game Factorio to test whether AI can handle complex, open-ended engineering challenges. Agents write Python code to build automated factories, progressing from simple resource extraction (~30 units/min) to sophisticated production chains (millions of units/sec).<p>== What's new in 0.3.0 ==<p>- Headless scaling: No longer needs the game client, enabling massive parallelization!<p>- OpenAI Gym compatibility: Standard interface for RL research<p>- Claude Code integration: We're livestreaming Claude playing Factorio [on Twitch](<a href="http://twitch.tv/playsfactorio" rel="nofollow">http://twitch.tv/playsfactorio</a>)<p>- Better tooling and SDK: 1-line CLI commands to run evaluations (with W&B logging)<p>== Key findings ==<p>We evaluated frontier models (Claude Opus 4.1, GPT-5, Gemini 2.5 Pro, Grok 4) on 24 production automation tasks of increasing complexity.<p>Even the best models struggle:<p>- Most models still rely on semi-manual strategies rather than true automation<p>- Agents rarely define helper functions or abstractions, limiting their ability to scale<p>- Error recovery remains difficult – agents often get stuck in repetitive failure loops<p>The performance gap between models on FLE correlates more closely with real-world task benchmarks (like GDPVal) than with traditional coding/reasoning evals.<p>== Why this matters ==<p>Unlike benchmarks based on exams that saturate quickly, Factorio's exponential complexity scaling means there's effectively no performance ceiling. The skills needed - system debugging, constraint satisfaction, logistics optimization - transfer directly to real challenges.<p>== Try it yourself ==<p>>>> uv add factorio-learning-environment<p>>>> uv add "factorio-learning-environment[eval]"<p>>>> fle cluster start<p>>>> fle eval --config configs/gym_run_config.json<p>We're looking for researchers, engineers, and modders interested in pushing the boundaries of agent capabilities. Join our Discord if you want to contribute. We look forward to meeting you and seeing what you can build!<p>-- FLE Team
Show HN: FLE v0.3 – Claude Code Plays Factorio
We're excited to release v0.3.0 of the Factorio Learning Environment (FLE), an open-source environment for evaluating AI agents on long-horizon planning, spatial reasoning, and automation tasks.<p>== What is FLE? ==<p>FLE uses the game Factorio to test whether AI can handle complex, open-ended engineering challenges. Agents write Python code to build automated factories, progressing from simple resource extraction (~30 units/min) to sophisticated production chains (millions of units/sec).<p>== What's new in 0.3.0 ==<p>- Headless scaling: No longer needs the game client, enabling massive parallelization!<p>- OpenAI Gym compatibility: Standard interface for RL research<p>- Claude Code integration: We're livestreaming Claude playing Factorio [on Twitch](<a href="http://twitch.tv/playsfactorio" rel="nofollow">http://twitch.tv/playsfactorio</a>)<p>- Better tooling and SDK: 1-line CLI commands to run evaluations (with W&B logging)<p>== Key findings ==<p>We evaluated frontier models (Claude Opus 4.1, GPT-5, Gemini 2.5 Pro, Grok 4) on 24 production automation tasks of increasing complexity.<p>Even the best models struggle:<p>- Most models still rely on semi-manual strategies rather than true automation<p>- Agents rarely define helper functions or abstractions, limiting their ability to scale<p>- Error recovery remains difficult – agents often get stuck in repetitive failure loops<p>The performance gap between models on FLE correlates more closely with real-world task benchmarks (like GDPVal) than with traditional coding/reasoning evals.<p>== Why this matters ==<p>Unlike benchmarks based on exams that saturate quickly, Factorio's exponential complexity scaling means there's effectively no performance ceiling. The skills needed - system debugging, constraint satisfaction, logistics optimization - transfer directly to real challenges.<p>== Try it yourself ==<p>>>> uv add factorio-learning-environment<p>>>> uv add "factorio-learning-environment[eval]"<p>>>> fle cluster start<p>>>> fle eval --config configs/gym_run_config.json<p>We're looking for researchers, engineers, and modders interested in pushing the boundaries of agent capabilities. Join our Discord if you want to contribute. We look forward to meeting you and seeing what you can build!<p>-- FLE Team
Show HN: Privacyforge.ai – AI Privacy Compliance Documents That Work
Hi HN,<p>I'm Divy, former CTO at Branch and previously led engineering teams at Credit Karma and NexHealth. Over the past decade in fintech and healthtech, I've watched too many founders get blindsided by privacy compliance.<p>The Problem: 80% of startups are unaware of privacy laws affecting their business. The choice between expensive attorneys ($5,000+) and risky generic templates is getting worse as regulations expand. Generic privacy policies fail because they make promises your business can't keep – I've seen this tank funding rounds and trigger regulatory investigations.<p>My Personal Pain: At Branch, we spent weeks and over $5K just to get basic privacy compliance docs. Our attorneys charged hundreds per hour to essentially fill out forms about our data practices. The kicker? The policy didn't even cover our specific use cases properly, and we had to redo everything when new regulations kicked in.<p>The Solution: PrivacyForge.ai generates legally compliant privacy documentation using AI trained on current regulations. Instead of generic templates, it creates documents based on your actual business practices – what data you collect, how you process it, where you store it, and which jurisdictions apply to you.<p>Technical Approach: We built this on Google Cloud with Vertex AI, using Claude Sonnet and Gemini 2.5 for document generation. The system maintains separate knowledge bases for GDPR, CCPA, CPRA, PIPEDA, COPPA, and CalOPPA. Each document gets validated against jurisdiction-specific requirements before delivery. We're continuously expanding the regulations we support.<p>Different from existing tools: Most privacy generators use static templates with basic fill-in-the-blanks. We analyze your specific data flows and generate custom language. No per-site pricing that kills agencies – just one-time payments with included updates when regulations change.
Current status: We're live with paying customers who've saved thousands in legal fees. Generated documents have passed compliance reviews at companies going through Series A due diligence.<p>Try it at privacyforge.ai – would love feedback from the HN community, especially if you're dealing with privacy compliance headaches at your company.<p>What privacy compliance nightmares have you faced? Always curious to hear war stories from fellow builders.
Show HN: Grapes Studio – HTML-first WYSIWYG website editor with LLM assistant
I’ve been working with @artf (creator of GrapesJS) on Grapes Studio, an HTML-first editor with an LLM assistant on top of GrapesJS.<p>We’re approaching this differently than the new wave of AI app/site builders which are typically generating full React applications, which we think is overkill for simple websites. From talking to people using these tools, we’ve seen a lot of issues with build errors and overly complicated pages.<p>With our approach you can:<p>- Edit visually via the no-code editor (drag/drop) or ask the LLM to make scoped changes (like “add a section” or “add a new page”).<p>- Build with straight HTML/CSS<p>- Ask AI to import your current site and start building from there instead of total rebuild.<p>We think there’s a lot of benefit using drag and drop editor functionality with LLMs, or you can jump straight into the code in the editor if you choose.<p>- Do you see value in this hybrid model (AI + visual + code editing)?<p>- What are the biggest blockers you’ve run into with AI-only builders?<p>Let us know what you think.
Show HN: Grapes Studio – HTML-first WYSIWYG website editor with LLM assistant
I’ve been working with @artf (creator of GrapesJS) on Grapes Studio, an HTML-first editor with an LLM assistant on top of GrapesJS.<p>We’re approaching this differently than the new wave of AI app/site builders which are typically generating full React applications, which we think is overkill for simple websites. From talking to people using these tools, we’ve seen a lot of issues with build errors and overly complicated pages.<p>With our approach you can:<p>- Edit visually via the no-code editor (drag/drop) or ask the LLM to make scoped changes (like “add a section” or “add a new page”).<p>- Build with straight HTML/CSS<p>- Ask AI to import your current site and start building from there instead of total rebuild.<p>We think there’s a lot of benefit using drag and drop editor functionality with LLMs, or you can jump straight into the code in the editor if you choose.<p>- Do you see value in this hybrid model (AI + visual + code editing)?<p>- What are the biggest blockers you’ve run into with AI-only builders?<p>Let us know what you think.
Show HN: Traceroute Visualizer
This nifty tool plots the traceroute results and shows you the RTT as well as the distance travelled by the packets!<p>Supports MTR, flyingroutes and of course, traceroute.<p>The existing solutions were too limited so I made that.<p>Let me know if you have any feedback
Show HN: Traceroute Visualizer
This nifty tool plots the traceroute results and shows you the RTT as well as the distance travelled by the packets!<p>Supports MTR, flyingroutes and of course, traceroute.<p>The existing solutions were too limited so I made that.<p>Let me know if you have any feedback
Show HN: Traceroute Visualizer
This nifty tool plots the traceroute results and shows you the RTT as well as the distance travelled by the packets!<p>Supports MTR, flyingroutes and of course, traceroute.<p>The existing solutions were too limited so I made that.<p>Let me know if you have any feedback
Show HN: Traceroute Visualizer
This nifty tool plots the traceroute results and shows you the RTT as well as the distance travelled by the packets!<p>Supports MTR, flyingroutes and of course, traceroute.<p>The existing solutions were too limited so I made that.<p>Let me know if you have any feedback
Show HN: Resterm – A terminal-based REST/GraphQL and gRPC client
Show HN: Resterm – A terminal-based REST/GraphQL and gRPC client
Show HN: ChartDB Agent – Cursor for DB schema design
Last year we launched ChartDB OSS (<a href="https://news.ycombinator.com/item?id=44972238">https://news.ycombinator.com/item?id=44972238</a>) - an open-source tool that generates ER diagrams from your database (via query/sql/dbml) without needing direct DB access.<p>Now we’re launching the ChartDB Agent.<p>It helps you design databases from scratch or make schema changes with natural language.<p>You can:<p>- Generate schemas by simply describing them in plain English<p>- Brainstorm new tables, columns, and relationships with AI<p>- Iterate visually in a diagram (ERD)<p>- Deterministically export SQL script<p>Try it out here - <a href="https://chartdb.io/ai" rel="nofollow">https://chartdb.io/ai</a> - no signup required.<p>Or sign up and use it on your own database<p>Would love to get your feedback :)
Show HN: ChartDB Agent – Cursor for DB schema design
Last year we launched ChartDB OSS (<a href="https://news.ycombinator.com/item?id=44972238">https://news.ycombinator.com/item?id=44972238</a>) - an open-source tool that generates ER diagrams from your database (via query/sql/dbml) without needing direct DB access.<p>Now we’re launching the ChartDB Agent.<p>It helps you design databases from scratch or make schema changes with natural language.<p>You can:<p>- Generate schemas by simply describing them in plain English<p>- Brainstorm new tables, columns, and relationships with AI<p>- Iterate visually in a diagram (ERD)<p>- Deterministically export SQL script<p>Try it out here - <a href="https://chartdb.io/ai" rel="nofollow">https://chartdb.io/ai</a> - no signup required.<p>Or sign up and use it on your own database<p>Would love to get your feedback :)
Show HN: ChartDB Agent – Cursor for DB schema design
Last year we launched ChartDB OSS (<a href="https://news.ycombinator.com/item?id=44972238">https://news.ycombinator.com/item?id=44972238</a>) - an open-source tool that generates ER diagrams from your database (via query/sql/dbml) without needing direct DB access.<p>Now we’re launching the ChartDB Agent.<p>It helps you design databases from scratch or make schema changes with natural language.<p>You can:<p>- Generate schemas by simply describing them in plain English<p>- Brainstorm new tables, columns, and relationships with AI<p>- Iterate visually in a diagram (ERD)<p>- Deterministically export SQL script<p>Try it out here - <a href="https://chartdb.io/ai" rel="nofollow">https://chartdb.io/ai</a> - no signup required.<p>Or sign up and use it on your own database<p>Would love to get your feedback :)
Show HN: ChartDB Agent – Cursor for DB schema design
Last year we launched ChartDB OSS (<a href="https://news.ycombinator.com/item?id=44972238">https://news.ycombinator.com/item?id=44972238</a>) - an open-source tool that generates ER diagrams from your database (via query/sql/dbml) without needing direct DB access.<p>Now we’re launching the ChartDB Agent.<p>It helps you design databases from scratch or make schema changes with natural language.<p>You can:<p>- Generate schemas by simply describing them in plain English<p>- Brainstorm new tables, columns, and relationships with AI<p>- Iterate visually in a diagram (ERD)<p>- Deterministically export SQL script<p>Try it out here - <a href="https://chartdb.io/ai" rel="nofollow">https://chartdb.io/ai</a> - no signup required.<p>Or sign up and use it on your own database<p>Would love to get your feedback :)
Show HN: Autism Simulator
Hey all, I built this. It’s not trying to capture every autistic experience (that’d be impossible). It’s based on my own lived experience as well as that of friends on the spectrum.<p>I'm trying to give people a feel for what masking, decision fatigue, and burnout can look like day-to-day. That’s hard to explain in words, but easier to show through choices and stats. I'm not trying to "define autism".<p>I’ve gotten good feedback here about resilience, meds, and difficulty tuning. I’ll keep tweaking it. If even a few people walk away thinking, "ah, maybe that’s why my coworker struggles in those situations," then it’s worth it.<p>Appreciate everyone who’s tried it and shared thoughts.
Show HN: Autism Simulator
Hey all, I built this. It’s not trying to capture every autistic experience (that’d be impossible). It’s based on my own lived experience as well as that of friends on the spectrum.<p>I'm trying to give people a feel for what masking, decision fatigue, and burnout can look like day-to-day. That’s hard to explain in words, but easier to show through choices and stats. I'm not trying to "define autism".<p>I’ve gotten good feedback here about resilience, meds, and difficulty tuning. I’ll keep tweaking it. If even a few people walk away thinking, "ah, maybe that’s why my coworker struggles in those situations," then it’s worth it.<p>Appreciate everyone who’s tried it and shared thoughts.