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12705
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BeatPad by @ApolloIE | Stardance
|
ApolloIE
|
0
|
2.06
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0
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[]
|
[{"post_id": 5282, "ts": "2026 [{"post_id": 5282, "ts": "2026-06-09T00:16:08Z", "hours": 2.0569, "text": "Working on my HackPad and learning how to do matrix (havent fully understood it yet) BTW the main goal is a secret for now🤫"}]...
|
Title: BeatPad by @ApolloIE | Stardance
Devlogs:
Title: BeatPad by @ApolloIE | Stardance
Devlogs:
Working on my HackPad and learning how to do matrix (havent fully understood it yet) BTW the main goal is a secret for now🤫...
|
1793443937.8108156
|
1794048737.8108156
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My first slack bot! by @Akhil_A | Stardance
|
Akhil_A
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0
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[]
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[]
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Title: My first slack bot! by @Akhil_A | Stardance
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1793969533.7137313
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Dissect by @yashbavale1578 | Stardance
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yashbavale1578
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Title: Dissect by @yashbavale1578 | Stardance
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a PID controller for an inverted pendulum by @Ath a PID controller for an inverted pendulum by @Ath | Stardance...
|
Ath
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0
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[]
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[]
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Title: a PID controller for an inverted pendulum b Title: a PID controller for an inverted pendulum by @Ath | Stardance...
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1793184879.5742233
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OwlStanding by @adityaaaa | Stardance
|
adityaaaa
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0
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1.09
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0
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[]
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[{"post_id": 9878, "ts": "2026 [{"post_id": 9878, "ts": "2026-06-16T10:57:45Z", "hours": 1.0853, "text": "First devlog on Stardance! I have no clue how this works but just wanted share a quick lil project I’ve been working on, its a next js site for my sister’s startup pretty basic with few cool components anddd thats as they roll more cohorts I’ll add more pages. I built it all solo from the ui to the aesthetics its wayy less like ai slop if you interested can hit it up here its a production build : https://owlstanding.in thenks :)"}]...
|
Title: OwlStanding by @adityaaaa | Stardance
Devl Title: OwlStanding by @adityaaaa | Stardance
Devlogs:
First devlog on Stardance! I have no clue how this works but just wanted share a quick lil project I’ve been working on, its a next js site for my sister’s startup pretty basic with few cool components anddd thats as they roll more cohorts I’ll add more pages. I built it all solo from the ui to the aesthetics its wayy less like ai slop if you interested can hit it up here its a production build : https://owlstanding.in thenks :)...
|
1793210194.7925804
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12717
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Untitled project by @sm | Stardance
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sm
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Title: Untitled project by @sm | Stardance
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Untitled by @Tigerente10 | Stardance
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Tigerente10
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Title: Untitled by @Tigerente10 | Stardance
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My awesome macropad! by @meri | Stardance
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meri
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[]
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Title: My awesome macropad! by @meri | Stardance
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1793451163.4495578
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1794055963.4495578
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Untitled by @meri | Stardance
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meri
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Title: Untitled by @meri | Stardance
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12736
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JEPA-Chess by @Seranom | Stardance
|
Seranom
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[]
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Title: JEPA-Chess by @Seranom | Stardance
|
1793260510.575746
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12739
|
A local file transfer application by @Racheal | St A local file transfer application by @Racheal | Stardance...
|
Racheal
|
0
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0.0
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[]
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[]
|
Title: A local file transfer application by @Rache Title: A local file transfer application by @Racheal | Stardance...
|
1793515807.422749
|
1794120607.422749
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12742
|
PCB Forge by @shree_builds | Stardance
|
shree_builds
|
0
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7.0
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0
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[]
|
[{"post_id": 5732, "ts": "2026 [{"post_id": 5732, "ts": "2026-06-09T17:04:44Z", "hours": 4.0, "text": "Devlog #1 PCB Forge started from a simple question: “Why is there no modern, beginner-friendly desktop application that lets you inspect, analyze, and understand PCB manufacturing files while also helping you design better boards?” Most existing EDA tools are either extremely complex, focused solely on design, or require significant experience to interpret manufacturing outputs. I wanted to build something that bridges that gap—a tool useful for makers, students, Hack Club participants, and professional hardware developers alike. The long-term vision is a desktop application capable of importing Gerber and Excellon drill files, visualizing PCBs in both 2D and 3D, performing manufacturer-specific DFM (Design for Manufacturability) analysis, estimating thermal behavior, and generating detailed manufacturability reports. Today’s work was focused on building a strong foundation rather than rushing into features. The project architecture has been organized as a Rust workspace with separate crates for the PCB core data model, Gerber parser, Excellon parser, DFM engine, thermal engine, geometry utilities, performance utilities, and database layer. The frontend is being developed using React and TypeScript, packaged as a native desktop application through Tauri. This modular architecture will make future development significantly easier and allow different subsystems to evolve independently. On the visualization side, a custom 2D rendering engine has already been prototyped. The viewer now supports a smooth infinite grid with adaptive scaling, automatic camera fitting, pan controls, zoom centered around the cursor, and rendering of board outlines, traces, pads, and vias. A desktop-style interface has also been introduced with a dedicated sidebar, toolbar, status panel, and a rendering architecture that cleanly separates the camera, renderer, and future visualization layers. Even though the current PCB being displayed is generated from demo data, the entire rendering pipeline has been designed so that it can later display real manufacturing files without requiring major architectural changes. Perhaps the biggest achievement so far is not a visible feature but the underlying engineering structure. Instead of building a collection of scripts, PCB Forge is being developed like a professional CAD application with dedicated rendering pipelines, camera abstraction, reusable geometry utilities, and an internal PCB intermediate representation that will eventually power DFM checks, thermal estimation, and 3D visualization. The immediate roadmap is exciting. The next development phase will add interactive object selection, hover highlighting, coordinate readouts, measurement tools, and a fully functional layer manager with independent visibility controls. After that, the temporary demo PCB will be replaced by a real RS-274X Gerber and Excellon parser capable of importing actual manufactured boards. Once the parser is complete, development will move toward GPU-accelerated 3D visualization, manufacturer-specific rule checking for services like JLCPCB and PCBWay, thermal estimation using engineering approximations, and comprehensive manufacturability scoring with automated suggestions. PCB Forge is still in its early stages, but today’s progress establishes the foundation for what I hope will become a powerful open-source tool for understanding, validating, and visualizing printed circuit boards. This is only the beginning."}, {"post_id": 6914, "ts": "2026-06-11T16:13:42Z", "hours": 2.0, "text": "Devlog #2 - Building the Interaction Engine This development cycle was all about transforming PCB Forge from a simple renderer into an interactive PCB viewer. The viewer now supports smooth panning, zooming, auto-fit camera controls, and rendering of board outlines, traces, pads, and vias. More importantly, I built a complete interaction engine that allows hovering over and selecting PCB objects, with visual highlighting and a properties panel displaying information about the selected component. I also implemented a measurement tool for calculating distances directly on the board and added quality-of-life features like ESC to deselect objects. Behind the scenes, the rendering, interaction, and PCB data model have been modularized, creating a strong foundation for future development. The next major milestone is replacing the current demo board with real PCB data. Instead of uploading individual Gerber files, PCB Forge will allow users to import an entire manufacturing ZIP package, automatically detect all layers, parse the files, and render the complete board. After that, development will focus on advanced features such as layer management, DFM analysis, thermal simulation, and manufacturability reports, moving PCB Forge closer to becoming a complete open-source PCB engineering platform. 🚀"}, {"post_id": 8587, "ts": "2026-06-14T08:49:55Z", "hours": 1.0, "text": "Devlog #2 – Building the PCB Import Pipeline This development cycle focused on transforming PCB Forge from a simple PCB viewer into the foundation of a real PCB import tool. On the frontend, the viewer gained several usability improvements, including object selection, hover highlighting, a properties panel, an ESC-to-deselect shortcut, and a measurement tool, making interaction with the board much more intuitive. The UI was also reorganized to support a cleaner workflow with floating controls and import status panels. The biggest milestone, however, was implementing the complete ZIP import pipeline. PCB Forge can now open a native file picker, load a PCB ZIP package, extract its contents through a Rust backend, and display the files inside the archive. An automatic layer detection engine was added to identify important layers such as top copper, bottom copper, solder mask, silkscreen, edge cuts, and drill files, producing a structured board manifest instead of just a list of filenames. An import engine abstraction was also introduced to separate the application logic from the UI, laying the groundwork for future drag-and-drop support and recent project management. Most importantly, PCB Forge now successfully reads the actual contents of Gerber files stored inside the ZIP archive. Seeing real Gerber source data generated by KiCad flow from the ZIP file through Rust and into the application confirmed that the entire import pipeline is functioning correctly. During this process, the project architecture was refactored to properly unify the Tauri backend and plugin system, eliminating several integration issues. The remaining major task is replacing the temporary demo parser with a true Gerber parser that converts the imported files into PCB geometry, allowing the application to render real user boards instead of the hardcoded demo design. With the import infrastructure now complete, development will shift toward implementing the parser and achieving the first end-to-end rendering of a real PCB."}]...
|
Title: PCB Forge by @shree_builds | Stardance
Dev Title: PCB Forge by @shree_builds | Stardance
Devlogs:
Devlog #2 – Building the PCB Import Pipeline This development cycle focused on transforming PCB Forge from a simple PCB viewer into the foundation of a real PCB import tool. On the frontend, the viewer gained several usability improvements, including object selection, hover highlighting, a properties panel, an ESC-to-deselect shortcut, and a measurement tool, making interaction with the board much more intuitive. The UI was also reorganized to support a cleaner workflow with floating controls and import status panels. The biggest milestone, however, was implementing the complete ZIP import pipeline. PCB Forge can now open a native file picker, load a PCB ZIP package, extract its contents through a Rust backend, and display the files inside the archive. An automatic layer detection engine was added to identify important layers such as top copper, bottom copper, solder mask, silkscreen, edge cuts, and drill files, producing a structured board manifest instead of just a list of filenames. An import engine abstraction was also introduced to separate the application logic from the UI, laying the groundwork for future drag-and-drop support and recent project management. Most importantly, PCB Forge now successfully reads the actual contents of Gerber files stored inside the ZIP archive. Seeing real Gerber source data generated by KiCad flow from the ZIP file through Rust and into the application confirmed that the entire import pipeline is functioning correctly. During this process, the project architecture was refactored to properly unify the Tauri backend and plugin system, eliminating several integration issues. The remaining major task is replacing the temporary demo parser with a true Gerber parser that converts the imported files into PCB geometry, allowing the application to render real user boards instead of the hardcoded demo design. With the import infrastructure now complete, development will shift toward implementing the parser and achieving the first end-to-end rendering of a real PCB.
Devlog #2 - Building the Interaction Engine This development cycle was all about transforming PCB Forge from a simple renderer into an interactive PCB viewer. The viewer now supports smooth panning, zooming, auto-fit camera controls, and rendering of board outlines, traces, pads, and vias. More importantly, I built a complete interaction engine that allows hovering over and selecting PCB objects, with visual highlighting and a properties panel displaying information about the selected component. I also implemented a measurement tool for calculating distances directly on the board and added quality-of-life features like ESC to deselect objects. Behind the scenes, the rendering, interaction, and PCB data model have been modularized, creating a strong foundation for future development. The next major milestone is replacing the current demo board with real PCB data. Instead of uploading individual Gerber files, PCB Forge will allow users to import an entire manufacturing ZIP package, automatically detect all layers, parse the files, and render the complete board. After that, development will focus on advanced features such as layer management, DFM analysis, thermal simulation, and manufacturability reports, moving PCB Forge closer to becoming a complete open-source PCB engineering platform. 🚀
Devlog #1 PCB Forge started from a simple question: “Why is there no modern, beginner-friendly desktop application that lets you inspect, analyze, and understand PCB manufacturing files while also helping you design better boards?” Most existing EDA tools are either extremely complex, focused solely on design, or require significant experience to interpret manufacturing outputs. I wanted to build something that bridges that gap—a tool useful for makers, students, Hack Club participants, and professional hardware developers alike. The long-term vision is a desktop application capable of importing Gerber and Excellon drill files, visualizing PCBs in both 2D and 3D, performing manufacturer-specific DFM (Design for Manufacturability) analysis, estimating thermal behavior, and generating detailed manufacturability reports. Today’s work was focused on building a strong foundation rather than rushing into features. The project architecture has been organized as a Rust workspace with separate crates for the PCB core data model, Gerber parser, Excellon parser, DFM engine, thermal engine, geometry utilities, performance utilities, and database layer. The frontend is being developed using React and TypeScript, packaged as a native desktop application through Tauri. This modular architecture will make future development significantly easier and allow different subsystems to evolve independently. On the visualization side, a custom 2D rendering engine has already been prototyped. The viewer now supports a smooth infinite grid with adaptive scaling, automatic camera fitting, pan controls, zoom centered around the cursor, and rendering of board outlines, traces, pads, and vias. A desktop-style interface has also been introduced with a dedicated sidebar, toolbar, status panel, and a rendering architecture that cleanly separates the camera, renderer, and future visualization layers. Even though the current PCB being displayed is generated from demo data, the entire rendering pipeline has been designed so that it can later display real manufacturing files without requiring major architectural changes. Perhaps the biggest achievement so far is not a visible feature but the underlying engineering structure. Instead of building a collection of scripts, PCB Forge is being developed like a professional CAD application with dedicated rendering pipelines, camera abstraction, reusable geometry utilities, and an internal PCB intermediate representation that will eventually power DFM checks, thermal estimation, and 3D visualization. The immediate roadmap is exciting. The next development phase will add interactive object selection, hover highlighting, coordinate readouts, measurement tools, and a fully functional layer manager with independent visibility controls. After that, the temporary demo PCB will be replaced by a real RS-274X Gerber and Excellon parser capable of importing actual manufactured boards. Once the parser is complete, development will move toward GPU-accelerated 3D visualization, manufacturer-specific rule checking for services like JLCPCB and PCBWay, thermal estimation using engineering approximations, and comprehensive manufacturability scoring with automated suggestions. PCB Forge is still in its early stages, but today’s progress establishes the foundation for what I hope will become a powerful open-source tool for understanding, validating, and visualizing printed circuit boards. This is only the beginning....
|
1792943433.3221083
|
1793807433.3221083
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12743
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1792936117.960139
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1793800117.960139
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1792929259.3524313
|
1793793259.3524313
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12745
|
My awesome macropad! by @Notluffy | Stardance
|
Notluffy
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: My awesome macropad! by @Notluffy | Stardan Title: My awesome macropad! by @Notluffy | Stardance...
|
1793231800.3211539
|
1793836600.3211539
|
|
12746
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|
1792932717.0590217
|
1793796717.0590217
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|
12747
|
Hack-A-Gent by @to_aarav_g | Stardance
|
to_aarav_g
|
1
|
177.01
|
0
|
[{"ship_num": 1, "ts": "2026-0 [{"ship_num": 1, "ts": "2026-09-29T13:09:15Z", "hours": 141.0, "multiplier": null, "payout": 0, "blessing": "neutral", "text": "What did you make? Hack-A-Gent — an AI coding agent that can plan, write, test and fix code for a hackathon project. What was challenging? Getting the agent to fix its own mistakes without breaking existing code. Cross-file dependencies and keeping shared code safe were probably the hardest parts. What are you proud of? I got it to go beyond just generating code and actually test and repair what it creates. How do I run it? Clone the repo, run npm install , create a .env with your Gemini API key, then run npm run dev . Start with a small coding task and let the agent work through it.", "repo": "https://github.com/Theuser1211/Hack-A-Gent", "demo": "https://github.com/Theuser1211/Hack-A-Gent/releases/"}]...
|
[{"post_id": 77987, "ts": "202 [{"post_id": 77987, "ts": "2026-10-09T03:55:17Z", "hours": 3.6219, "text": "Greeting! I have made 1 bid decision and ported the whole hag to python scipt using external libraries instead of building every agent myself. But for this we need gemini-cli configured with a paid account(which I dont have!). Sad, but I am happy rest all of hag works without any issues"}, {"post_id": 76687, "ts": "2026-10-04T10:37:59Z", "hours": 3.055, "text": "Got 208/208 tests to pass. Also I have implemented the providor for LLM as Gemini(Primary) -> Openrouter -> NVIDIA. So that maximum success rates can be achived. Also for anyone to test out HAG, just use README.md from github to install HAG, then setup up your API keys in the .env (don’t worry it’s all local), and you are ready to go."}, {"post_id": 76124, "ts": "2026-10-02T12:50:50Z", "hours": 3.5364, "text": "Heyyy, I have updated my README.md and also fixed my failing tests by now. I guess I am ready to ship Hack-A-Gent for Ship#1"}, {"post_id": 75504, "ts": "2026-09-30T09:17:25Z", "hours": 25.7925, "text": "I have realised that using NVIDIA NIMS is the issue, my app is almost working. , but the providors is failing at this point. I will try using gemini and openrouter to chek if it will work or not. I guess I will not be able to. And I also need to update my README.md for some reason it looks like AI written, I will write it in a funny way now."}, {"post_id": 72689, "ts": "2026-09-23T14:43:47Z", "hours": 20.6364, "text": "Fixed a pretty annoying bug today. HAG can now actually reach Nemotron during auto-repair after NVIDIA 503s. One step closer to a full successful run."}, {"post_id": 42039, "ts": "2026-08-06T16:28:40Z", "hours": 8.8503, "text": "Major progress today! I completed the Phase 1 stabilization of Hack-A-Gent by resolving all remaining test and build issues (1721/1721 tests passing, clean TypeScript build). I also performed a deep forensic investigation into the AI generation pipeline and discovered a critical issue where the router was rejecting recoverable LLM responses before they reached the JSON extraction layer. With the core architecture now stable, the focus shifts to eliminating unnecessary template fallbacks and improving the quality of AI-generated hackathon projects."}, {"post_id": 41361, "ts": "2026-08-05T15:03:39Z", "hours": 13.7719, "text": "Today’s work focused on stabilizing Hack-A-Gent for a production-ready release. I fixed the Improvement Pass so it now completes the full critique -> patch -> build -> judge cycle with measurable score improvements, strengthened template fallback generation with complete project scaffolding and improved styling, added automatic generation of deployment assets like LICENSE and vercel.json, and implemented comprehensive child-process lifecycle management to ensure the CLI exits cleanly after execution. I also streamlined the interview flow by removing unnecessary prompts, improved validation, and verified the project with a clean TypeScript build and extensive unit and feature test coverage."}, {"post_id": 39997, "ts": "2026-08-03T10:51:49Z", "hours": 8.8792, "text": "This is session I added a better parser so I get almost 99% accuracy and also made many improvements in the code generation. Almost done and drained out from all this"}, {"post_id": 39011, "ts": "2026-08-01T17:39:57Z", "hours": 14.4528, "text": "Spent this session improving Hack-A-Gent’s reliability and generation pipeline. Fixed a major architectural issue where generated apps were being overwritten by fallback templates, allowing AI-generated pages to be preserved correctly. Also resolved several runtime and build issues, improved validation, and verified the full pipeline by generating, building, and running a real hackathon project successfully. The next focus is improving project quality so the generated apps are more original, context-aware, and competitive in real hackathons."}, {"post_id": 35101, "ts": "2026-07-26T09:58:01Z", "hours": 11.1589, "text": "Today was mostly about making Hack-A-Gent more reliable instead of adding new features. I finally tracked down a long-standing parser issue that turned out to be an architectural problem: the CLI and the analysis pipeline were using two completely different parsers. I merged everything into a single parser, updated the production build to include it, and verified that all parser regression tests and the full test suite still pass. After that, I confirmed the CLI now extracts real judging criteria like Impact and Innovation instead of mistakenly treating navigation links as judging criteria. With parsing in a much better place, I shifted focus toward hardening the overall pipeline by planning phased reliability work around generation, auto-repair, validation, and recovery so the goal is no longer just generating code, but consistently producing projects that typecheck, build, run, and are ready for submission."}, {"post_id": 33322, "ts": "2026-07-23T04:04:01Z", "hours": 8.9597, "text": "This week I focused on making Hack-A-Gent stable and release-ready instead of adding new features. I cleaned up dead code, removed unused files, improved CLI logging and error messages, and verified the project with a full build and test pass. The CLI now parses real hackathon pages, plans projects, and gracefully falls back when AI providers are unavailable. I also ran end-to-end tests on real hackathon URLs to identify the final issues before release. The remaining work is improving template fallback and validation so every generated project is immediately usable, bringing Hack-A-Gent closer to its first stable release."}, {"post_id": 27158, "ts": "2026-07-12T13:41:30Z", "hours": 6.4664, "text": "Might be on final stages, making sure the agent doesn’t blows up in users hands. Taking time but needs to be done, Hope I can ship it by this week"}, {"post_id": 26029, "ts": "2026-07-10T16:39:54Z", "hours": 22.7653, "text": "Spent today improving Hack-A-Gent’s long-term direction instead of just fixing bugs. I mapped out a roadmap to turn it into a real Devpost hackathon agent, including a hackathon qualification engine, real Devpost benchmark suite, autonomous repair loop, browser validation, and organizational learning. Also audited the current architecture to identify what already exists, what needs refactoring, and what should be built next before writing more code."}, {"post_id": 21958, "ts": "2026-07-04T05:04:47Z", "hours": 25.1944, "text": "Hack-A-Gent I built Hack-A-Gent , a CLI-based AI agent that helps developers turn a Devpost hackathon challenge into a working project in minutes. Simply paste a Devpost competition URL into the terminal, and Hack-A-Gent analyzes the challenge, extracts the judging criteria and submission requirements, plans an appropriate architecture, and generates a production-ready project scaffold. You bring your own LLM API key (Anthropic, OpenAI, Google Gemini, NVIDIA NIMs, Ollama, and more), and Hack-A-Gent orchestrates the rest—from understanding the hackathon prompt to generating code, documentation, and a submission-ready starting point. The goal isn’t to replace developers, but to eliminate the repetitive setup work so builders can spend more time refining their ideas, polishing their projects, and creating a great demo."}]...
|
Title: Hack-A-Gent by @to_aarav_g | Stardance
Dev Title: Hack-A-Gent by @to_aarav_g | Stardance
Devlogs:
Hack-A-Gent I built Hack-A-Gent , a CLI-based AI agent that helps developers turn a Devpost hackathon challenge into a working project in minutes. Simply paste a Devpost competition URL into the terminal, and Hack-A-Gent analyzes the challenge, extracts the judging criteria and submission requirements, plans an appropriate architecture, and generates a production-ready project scaffold. You bring your own LLM API key (Anthropic, OpenAI, Google Gemini, NVIDIA NIMs, Ollama, and more), and Hack-A-Gent orchestrates the rest—from understanding the hackathon prompt to generating code, documentation, and a submission-ready starting point. The goal isn’t to replace developers, but to eliminate the repetitive setup work so builders can spend more time refining their ideas, polishing their projects, and creating a great demo.
Spent today improving Hack-A-Gent’s long-term direction instead of just fixing bugs. I mapped out a roadmap to turn it into a real Devpost hackathon agent, including a hackathon qualification engine, real Devpost benchmark suite, autonomous repair loop, browser validation, and organizational learning. Also audited the current architecture to identify what already exists, what needs refactoring, and what should be built next before writing more code.
Might be on final stages, making sure the agent doesn’t blows up in users hands. Taking time but needs to be done, Hope I can ship it by this week
This week I focused on making Hack-A-Gent stable and release-ready instead of adding new features. I cleaned up dead code, removed unused files, improved CLI logging and error messages, and verified the project with a full build and test pass. The CLI now parses real hackathon pages, plans projects, and gracefully falls back when AI providers are unavailable. I also ran end-to-end tests on real hackathon URLs to identify the final issues before release. The remaining work is improving template fallback and validation so every generated project is immediately usable, bringing Hack-A-Gent closer to its first stable release.
Today was mostly about making Hack-A-Gent more reliable instead of adding new features. I finally tracked down a long-standing parser issue that turned out to be an architectural problem: the CLI and the analysis pipeline were using two completely different parsers. I merged everything into a single parser, updated the production build to include it, and verified that all parser regression tests and the full test suite still pass. After that, I confirmed the CLI now extracts real judging criteria like Impact and Innovation instead of mistakenly treating navigation links as judging criteria. With parsing in a much better place, I shifted focus toward hardening the overall pipeline by planning phased reliability work around generation, auto-repair, validation, and recovery so the goal is no longer just generating code, but consistently producing projects that typecheck, build, run, and are ready for submission.
Spent this session improving Hack-A-Gent’s reliability and generation pipeline. Fixed a major architectural issue where generated apps were being overwritten by fallback templates, allowing AI-generated pages to be preserved correctly. Also resolved several runtime and build issues, improved validation, and verified the full pipeline by generating, building, and running a real hackathon project successfully. The next focus is improving project quality so the generated apps are more original, context-aware, and competitive in real hackathons.
This is session I added a better parser so I get almost 99% accuracy and also made many improvements in the code generation. Almost done and drained out from all this
Today’s work focused on stabilizing Hack-A-Gent for a production-ready release. I fixed the Improvement Pass so it now completes the full critique -> patch -> build -> judge cycle with measurable score improvements, strengthened template fallback generation with complete project scaffolding and improved styling, added automatic generation of deployment assets like LICENSE and vercel.json, and implemented comprehensive child-process lifecycle management to ensure the CLI exits cleanly after execution. I also streamlined the interview flow by removing unnecessary prompts, improved validation, and verified the project with a clean TypeScript build and extensive unit and feature test coverage.
Major progress today! I completed the Phase 1 stabilization of Hack-A-Gent by resolving all remaining test and build issues (1721/1721 tests passing, clean TypeScript build). I also performed a deep forensic investigation into the AI generation pipeline and discovered a critical issue where the router was rejecting recoverable LLM responses before they reached the JSON extraction layer. With the core architecture now stable, the focus shifts to eliminating unnecessary template fallbacks and improving the quality of AI-generated hackathon projects.
Fixed a pretty annoying bug today. HAG can now actually reach Nemotron during auto-repair after NVIDIA 503s. One step closer to a full successful run.
I have realised that using NVIDIA NIMS is the issue, my app is almost working. , but the providors is failing at this point. I will try using gemini and openrouter to chek if it will work or not. I guess I will not be able to. And I also need to update my README.md for some reason it looks like AI written, I will write it in a funny way now.
Heyyy, I have updated my README.md and also fixed my failing tests by now. I guess I am ready to ship Hack-A-Gent for Ship#1
Got 208/208 tests to pass. Also I have implemented the providor for LLM as Gemini(Primary) -> Openrouter -> NVIDIA. So that maximum success rates can be achived. Also for anyone to test out HAG, just use README.md from github to install HAG, then setup up your API keys in the .env (don’t worry it’s all local), and you are ready to go.
Greeting! I have made 1 bid decision and ported the whole hag to python scipt using external libraries instead of building every agent myself. But for this we need gemini-cli configured with a paid account(which I dont have!). Sad, but I am happy rest all of hag works without any issues
Ships:
What did you make? Hack-A-Gent — an AI coding agent that can plan, write, test and fix code for a hackathon project. What was challenging? Getting the agent to fix its own mistakes without breaking existing code. Cross-file dependencies and keeping shared code safe were probably the hardest parts. What are you proud of? I got it to go beyond just generating code and actually test and repair what it creates. How do I run it? Clone the repo, run npm install , create a .env with your Gemini API key, then run npm run dev . Start with a small coding task and let the agent work through it....
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My awesome macropad! by @Pisly | Stardance
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Title: My awesome macropad! by @Pisly | Stardance
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