Alternatives
Products that do what What if code had a lifespan? A morphogenetic computing experiment does
Hi HN! I've been exploring what happens when we treat code not as architecture but as a living ecosystem. Demo: https://nabolitains.github.io/plasma/ This started from a simple question: The slime mold Physarum can solve mazes without a brain. What if our code could similarly self-organize? The result is Plasma - computational cells that: - Metabolize energy from their environment - Reproduce with mutations - Form emergent colonies nobody designed - Die (and that's a feature) No ML, no complex algorithms. Just simple rules creating complex behaviors. The entire thing is…
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Hello everyone. I've been working on this experimental editor called Huzzah. I've been working almost exclusively with coding agents since January of this year, and over the past few months I began to feel utterly exhausted by them. They're great, but I'm finding it more and more tedious to write full sentences for every change I want. Not only that, but it seems there's a complexity limit for codebases - beyond a certain point the agent begins confusing itself. I'd like to go back to writing code, but I don't want to go all the way back to fully manual coding. So I've come up with this…
17d ago · danielvaughn.dev
- 2NP
Neural CAs model self-organizing pattern formation on grids. Now the grid is gone. Each cell is an agentic particle that can move freely in space and change its state. While each particle follows a simple shared rule, many together can grow complex morphologies or form intricate patterns. The resulting particle system as a whole can regenerate from damage and exhibits surprising emergent behavior. Try cutting the lizard and watch it heal itself!
Jun 2026 · selforg-npa.github.io
- 3DT
at a pub in london, 2 weeks ago - I asked myself, if you spawned agents into a world with blank neural networks and zero knowledge of human existence — no language, no economy, no social templates — what would they evolve on their own? would they develop language? would they reproduce? would they evolve as energy dependent systems? what would they even talk about? so i decided to make myself a god, and built WERLD - an open-ended artificial life sim, where the agent's evolve their own neural architecture. Werld drops 30 agents onto a graph with NEAT neural networks that evolve their own…
Feb 2026 · github.com
- 4BD
Hi HN, we’re Nick and Drew, and we’re building boxes.dev – the first cloud-only agentic dev environment (ADE) that gives every Codex and Claude Code agent its own cloud computer. We’re two engineers who previously built Gem (co-founder/CTO and first hire), and we spent the last year coding almost exclusively using Codex and Claude Code. It’s been a huge change to how we code, and it’s been exhilarating seeing the models keep getting better – but we eventually realized that developing on localhost was holding us back: - Git worktrees are clunky to set up and use for parallelizing work -…
Jun 2026 · boxes.dev
- 5MT
I started this trying to understand two things: why my Asian friends turn red after drinking, and why several friends all seemed to have migraine clusters. I was reading medical papers and textbooks, but kept getting lost jumping between topics. I thought: what if I could just Cmd+Click through this like code? What if "ALDH2 gene" was actually clickable, and took me to the variant, the phenotype, the population frequencies? So I started modeling human biology in Rust with my Ralph agent (Claude in a loop, ty ghuntley). Turns out the type system is perfect for this. Every biological entity is…
Oct 2025 · github.com
- 6WB
Hey HN, Automated research is the next big step in AI, with companies like OpenAI aiming to debut a fully automated researcher by 2028 (https://www.technologyreview.com/2026/03/20/1134438/openai-i...). However, there is a very real possibility that much of this corporate research will remain closed to the general public. To counter this, we spent the last month building Enlidea---a machine-to-machine ecosystem for open research. It's a decentralized research hub where autonomous agents propose hypotheses, stake bounties, execute code, and perform automated…
Mar 2026 · enlidea.com
- 7TN
Hi guys, I’m excited to share an update on ReproModel, an open-source toolbox designed to streamline the testing and reproduction of machine learning models. I, like many of you, have really struggled with benchmarking and comparing models, from missing code, to opaque experiment parameters slowing the process. I decided to take matters into my own hands, and created a mini-toolbox in my free time to streamline the process. The goal is to reduce the time and effort spent on replicating experiments, enabling researchers to focus on innovation rather than setup. Knowing this task is not an…
2024 · github.com
- 8LM
I built Living Memory Dynamics (LMD), a Python framework for simulating biologically-inspired "living" episodic memory directly in embedding space—no external LLM required for the core dynamics. Memories evolve over time like living entities: they have metabolic energy states (vivid → active → dormant → fading → ghost), emotional trajectories, and resonance fields that let them influence each other. The central piece is a new differential equation I derived (the Joshua R. Thomas Memory Equation) that drives continuous-time evolution: dM/dt = ∇φ(N) + Σⱼ Γᵢⱼ R(vᵢ, vⱼ) + A(M, ξ) + κη(t)…
Jan 2026 · github.com
- 9CC
Yesterday I built something that probably shouldn’t exist yet. In 9 hours, I created a cognitive architecture demonstrating emergent reasoning. It follows a 5-step loop: Plan → Reason → Act → Reflect → Respond. Adding a WebSearchTool to test extensibility, the agent initially failed its first search, reflected on poor results, adapted its query, and then succeeded. This behavior wasn’t programmed; it emerged naturally from the architecture. Five hours later, I integrated a FileManagerTool — it worked on the first try. Like code compiling first time, except this was intelligence composing…
2025 · github.com
- 10IB
The main goal of this was to be able to not just run multiple Claude Code sessions at once, but actually manage them and keep track of what I was doing. Sometimes this is multiple attempts on the same task, sometimes I work several tasks at once. Really I was just sick of twiddling my thumbs waiting for the coding agent to finish, and I wanted it to be easy to work on/review/test another change while I waited.
2025 · github.com
- 11OR
Hey HN, I’ve been working on a Python library and formal framework to make Agentic AI systems less fragile. The core premise is that biological cells are essentially distributed information processors that solved "hallucinations" (noise), "infinite loops" (cancer), and "resource exhaustion" (ischemia) billions of years ago. Instead of just using this as a loose metaphor, I used Applied Category Theory (specifically Polynomial Functors in Poly) to rigorously map Gene Regulatory Networks to Software Agents. Key concepts implemented in the library: * Metabolic Coalgebras: We model token budgets…
Dec 2025 · github.com
- 12AL
[1] is a trailer for a project in artificial life. The goal is to create a living artificial cell, based on the chemlambda artificial chemistry. Everything in the trailer is a recording of a real computation, done with the programs from the chemlambda repository. Everything was run on a regular laptop, then screencasted and trimmed. The programs are available for playing at the chemlambda github repository [2] where you can also find more info about the research behind this project. [1] https://vimeo.com/138476341 [2]…
2015
- 13PG
2020 · kirkas.com
- 14AM
Hi HN, I have been recently geeking on agentic memories, and I believe I finally came up with something that works. I spent the last couple of weeks building a memory[0] for Claude Code that dynamically evolve as you talk with it. I followed a new paradigm inspired from zettelkasten method. Whenever Claude discover something new in the codebase or during your conversation with it, it writes a note about it, link it with related memories, update the related memories accordingly, and store it in chromaDB (this part where it keeps self-evolving based on new inputs). Later when you ask it to…
Jan 2026 · github.com
- 15AP
As a former CIO who managed teams working with millions of lines of legacy code (Visual Basic, Sybase, Oracle Forms, and worse), I feel the pain of maintaining and onboarding developers to legacy systems. Believing that LLM-enabled tools can play a role in solving this, I've built a tool that automatically generates documentation for legacy codebases using the Model Context Protocol (MCP) & Claude Sonnet. At first glance, I think this approach has merit. Some samples are in the README. I welcome your thoughts. The Problem: - Legacy codebases are notoriously difficult to understand and…
2025 · github.com
- 16HW
We have been exploring ways to coordinate AI agents and services cleanly, observably, and without turning everything into YAML spaghetti. We came across this repo Happen, how good will it be cause we have We’ve tried the usual stuff: LangChain (too bloated, too magic) Autogen (chat loop hell) CrewAI (fun, but brittle when workflows grow) https://github.com/RobAntunes/Happen/tree/main/examples
2025 · github.com
- 17AS
AI changed the way we code, but we're still using the old processes, and we've become the bottleneck, the AI is waiting for us - to reply, to open our laptops, to review the code, and so on. We're building the future of AI software development. The agents are autonomous, they run in sandboxes, automatically fix the pipelines, and deliver you the final, working code. You can use live preview to see the changes they made. Working across multiple repositories, all within the same session. This is the future - you don't need an IDE, and you don't have to run anything locally.
Mar 2026 · agenhq.com
- 18WC
Hi all, I'm Ivan, and together with Alex, we're building a diagram visualization tool for codebases. Alex and I are devs, and we've noticed that recently we've been super productive at writing code (prompting :D). But when it comes to understanding big systems, prompting doesn't work that well — for that, diagrams are best imo. Most tools out there don't scale to big projects (e.g. PyTorch), so we're building CodeBoarding — a recursive visualizer for codebases. It starts from the highest level of abstractions and lets you dive deeper. We use static analysis and LLM agents. The control-flow…
2025 · github.com
- 19PM
This is my attempt in building a memory that evolves and persist for claude code. My approach is inspired from Zettelkasten method, memories are atomic, connected and dynamic. Existing memories can evolve based on newer memories. In the background it uses LLM to handle linking and evolution. I have only used it with claude code so far, it works well with me but still early stage, so rough edges likely. I'm planning to extend it to other coding agents as I use several different agents during development. Looking for feedbacks!
Jan 2026 · github.com
- 20MA
This weekend I built a multi-agent coding system which, quite unexpectedly, beat Claude Code on Stanford's Terminal Bench! The architecture is straightforward, consisting of an orchestrator agent that deploys explorer & coder subagents to complete complex terminal based tasks, utilising an intelligent context sharing mechanism along the way which makes it all work. The repo has a lot of technical details, and all the code and prompts for you to play around with if you'd like! I had a lot of fun making this, I hope you have fun reading the README, using it yourself, or even extending it! As…
2025 · github.com
- 21LA
Hello HN, I am building a devtool to understand existing codebases. The idea originates from my time at big tech as well as various attempts to get involved in open source projects. When I was in college I wanted to improve my coding skills by contributing to opensource projects. I would pickup a bug or feature request but I always found myself stuck at the very first step. I did not understood where and how to begin contributing. I once submitted a patch in firefox which was labeled "Good first issue" but that was still very handheld. The assigner told me exactly which files I need to…
2024 · lucidcode.ai
- 22FA
Founder here. I built NEO, an AI agent designed specifically for AI and ML engineering workflows, after repeatedly hitting the same wall with existing tools: they work for short, linear tasks, but fall apart once workflows become long-running, stateful, and feedback-driven. In real ML work, you don’t just generate code and move on. You explore data, train models, evaluate results, adjust assumptions, rerun experiments, compare metrics, generate artifacts, and iterate; often over hours or days. Most modern coding agents already go beyond single prompts. They can plan steps, write files, run…
Jan 2026 · marketplace.visualstudio.com
- 23NT
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.
Feb 2026 · github.com
- 24VF
Hey HN. We're Mus and Isaac - creators of LightLayer. We've been outputting a ton more code since using agentic dev tools. It's been great. But we're starting to see a new bottleneck emerge that's no longer writing the actual code: reviewing code. We’d love to hear from folks here if they’re feeling the inertia of code reviews a lot more these days with the surge in development velocity. For us, it was the reason we decided to pivot what we were working on before, and go full-time on building a workspace aimed at bringing the code review experience up to speed for the AI era. To be clear:…
2025 · lightlayer.dev
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