Praxis, my personal take on Compound Engineering with AI
Hey HN! I really enjoy Every's approach to Compound Engineering (https://every.to/guides/compound-engineering), but their plugin is tightly tied to their project (Cora) and stack (Ruby/Rails). I also found the files too big, and they used more context window than what I would like for my personal use. So, with the help of Amp Code CLI, I've built my own take on the compound engineering workflow. I tried to keep it agnostic to project stacks and as efficient as possible, so the context window could be used in the best way. I also wanted it to be extendable (for…
What it does
In the maker’s words, at launch
Hey HN! I really enjoy Every's approach to Compound Engineering (https://every.to/guides/compound-engineering), but their plugin is tightly tied to their project (Cora) and stack (Ruby/Rails). I also found the files too big, and they used more context window than what I would like for my personal use. So, with the help of Amp Code CLI, I've built my own take on the compound engineering workflow. I tried to keep it agnostic to project stacks and as efficient as possible, so the context window could be used in the best way. I also wanted it to be extendable (for example, just drop your own subagents for review that are specific to your project). I also wanted to be easy to set up and update, so I made a simple CLI tool that keeps track of files in the `.agents` directory, updates when new versions are found in the repository, and displays a diff in the terminal before overwriting any customisations. I feel this matches well with my personal preferences when working with AI agents, but I would love to have feedback from more people.
Does the same job
all alternatives →- AWA working reference implementation of context engineeringApr 2026 · github.com · ▲46
I've been presenting at local meetups about Context Engineering, RAG, Skills, etc.. I even have a vbrownbag coming up on LinkedIn about this topic so I figured I would make a basic example that uses bedrock so I can use it in my talks or vbrownbags. Hopefully it's useful.
- NANew approach for CI/CD/compute system2025 · egdaemon.com · ▲22
I've been tired with the current options on the market for awhile and decided to do something about it after the running into the disaster that is MLOps at my last two startups and having to manage a multiple operation platforms both for my fellow ML engineers, the general application CI/CD and orchestration layers while simultaneously building the application itself. Its still extremely early for the product but its functioning and is well on its way. I'd love feedback on the approach and peoples thoughts on the problem space. Personally my irritations have been in the poor tooling,…
- CACoding Agents swarming your codebaseSep 2025 · infrastructureas.ai · ▲9
I built this because I was tired of creating pull requests in 20 repositories just to change a single line of workflow job version. With Infra as AI, just mention the change. Agents work on all repos in parallel, read the docs, make a bunch of PRs and fill in the description. You can see the demo of the actual dashboard in the landing. Let me know your thoughts :) It means a lot to me!
- NTNoodles – Turn any codebase into a diagram with Claude and Tree-sitterFeb 2026 · github.com · ▲6
I built a CLI tool that turns codebases and PRs into diagrams so you can quickly understand how things fit together. Originally made it because I couldn't follow my own AI-generated repos. Just shipped a big update: - Switched from D2 to Mermaid for rendering - Tree-sitter AST parsing + agentic flow instead of raw LLM calls. ~50x faster. - Works on any GitHub repo or PR, not just local - Dropped the web frontend, it's just a CLI now - Published as a pip package Still a ton to improve and I'm building fast. Feedback, issues, PRs all welcome.
- HPHopsule – Persistent Memory Layer for AI EngineeringMar 2026 · hopsule.com · ▲5
Hey Everyone, I'm neither the founder or affiliated with these guys. But when they showed me the product it really clicked a switch. I have been building products with AI since sonnet 4.0, and one of my issue, like many, consistency. Hopsule turns architecture decisions into enforceable context that AI tools must follow. Creates trackable, tasks which can be feed into your AI tools to do compound engineering. If you're building with Claude Code, Cursor, or Copilot. You can use their CLI or MCP.
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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
