I made a tool after being stuck in dependency hell
Hi HN, I built Hypermod to help developers automate large-scale code migrations. If you've ever had to upgrade dependencies, refactor thousands of files, or apply the same fix across multiple repos, you know how painful and time-consuming it can be. Hypermod makes this process faster and more reliable by combining static analysis, AI-powered codemods, and GitHub automation. Why I Built This I've spent years working with large codebases where upgrading dependencies or migrating frameworks was a nightmare—lots of manual work, brittle scripts, and coordination across teams. Existing tools like…
What it does
In the maker’s words, at launch
Hi HN, I built Hypermod to help developers automate large-scale code migrations. If you've ever had to upgrade dependencies, refactor thousands of files, or apply the same fix across multiple repos, you know how painful and time-consuming it can be. Hypermod makes this process faster and more reliable by combining static analysis, AI-powered codemods, and GitHub automation. Why I Built This I've spent years working with large codebases where upgrading dependencies or migrating frameworks was a nightmare—lots of manual work, brittle scripts, and coordination across teams. Existing tools like codemods and regex-based find-and-replace help, but they often fall short when dealing with complex transformations across multiple repositories. I wanted something that could automate the entire process while integrating directly into CI/CD. What’s Different - Works in a GitHub Action: Unlike other tools that clone your repo to an external server, Hypermod runs directly in a GitHub Action, keeping everything secure and within your workflow. - AI-Powered Codemods: Generate migration scripts automatically based on before/after code samples. - Multi-Repo Support: Apply transformations across multiple repositories at scale. - Customizable Transformations: Use static analysis and AST-based codemods to apply complex changes reliably. - Safe & Auditable: All changes go through Git, so you can review and test before merging. Try It Out You can test it out in our sandbox editor without signing up. If you want to run it on your own repos, there’s a free plan for open-source projects and a Pro plan for private repos. Would love to hear your thoughts—feedback, ideas, or pain points you’ve had with code migrations!
Does the same job
all alternatives →
- RARemake – A server-rendered framework for building CRUD web apps fast2020 · ▲47
I wanted to have a framework that would let me build web apps faster than ever before. I didn’t care if it was a little hacky or didn’t use best practices — I wanted to be able to get a multi-user application out the door in hours instead of months. I researched the CMS space for months before deciding to build something from scratch. My goal was to be 90% done building a web app once I had the static HTML and CSS finished. I’m not a big fan of building out API endpoints over and over again for every new app, fiddling with a database, or doing lots of config. What I ended up with was a…
- IBI built a tool that helps you understand new codebases faster2025 · repoiq.be · ▲7
After years of struggling with onboarding to new projects, I got tired of spending weeks just trying to grasp the basics of a codebase. The README rarely tells the whole story, and "just read the code" isn't practical for large repos. I built RepoIQ to create personalized learning paths through any GitHub repository. It analyzes the codebase structure, identifies key components, and creates a step-by-step guide tailored to your learning needs.
- DADependabot – Automated Dependency Update PRs for Ruby, JS, Python and PHP2017 · dependabot.com · ▲51
- IBI built a GitHub application that generates documentation automaticallyDec 2025 · codesummary.io · ▲6
Hi HN, A lot of the dev teams I have worked with had a lot of issues with their documentation. In fact, some of my easiest clients to get were from clients that had "black box" solutions that devs no longer at the company had created. Personally, writing documentation is like grinding nails on a chalkboard. I have been having a lot of fun with building solutions that can run in a distributed way, not something a dev needs to run themselves. And after a significant amount of testing and building out several different solutions, I finally have a solution that is easy to set up and runs in the…
- DPDocker pulls more than it needs to - and how we can fix itMar 2026 · dockerpull.com · ▲8
Hi all! I've built a small tool to visualize how inefficient `docker pull` is, in preparation for standing up a new Docker registry + transport. It's bugged me for a while that updating one dependency with Docker drags along many other changes. It's a huge problem with Docker+robotics. With dozens or hundreds of dependencies, there's no "right" way to organize the layers that doesn't end up invalidating a bunch of layers on a single dependency update - and this is ignoring things like compiled code, embedded ML weights, etc. Even worse, many robotics deployments are on terrible internet,…
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com


Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com


Launched alongside, March 2025
the whole month →
Mimic Human Research & Save Findings in AI Knowledge Base
AI · 2025 · sider.ai




