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  Features: 3 oscillators, Moog ladder filter (24dB/oct), dual ADSR envelopes, LFO, glide, noise generator, 4 multitimbral channels, 19 presets, rotary
  knob GUI, virtual keyboard with mouse + QWERTY input, and MIDI support.

  No external GUI frameworks — just tkinter, numpy, and sounddevice.

very much inspired by karpathy's microgpt of the same name. it's (by default) a 4000 param GPT/LLM/NN that learns to generate names. this is sorta an educational tool in that you can visualize the activations as they pass through the network, and click on things to get an explanation of them.

https://archive.ph/p81wc

I run a generative AI infra company, unified API for 600+ models. Our team started deploying AI agents for our marketing and lead gen ops: content, engagement, analytics across multiple X accounts.

OpenClaw worked fine for single agents. But at ~14 agents across 6 accounts, the problem shifted from "how do I build agents" to "how do I manage them."

Deployment, monitoring, team isolation, figuring out which agent broke what at 3am. Classic orchestration problem.

So I built klaw, modeled on Kubernetes: Clusters — isolated environments per org/project Namespaces — team-level isolation (marketing, sales, support) Channels — connect agents to Slack, X, Discord Skills — reusable agent capabilities via a marketplace

CLI works like kubectl: klaw create cluster mycompany klaw create namespace marketing klaw deploy agent.yaml

I also rewrote from Node.js to Go — agents went from 800MB+ to under 10MB each.

Quick usage example: I run a "content cluster" where each X account is its own namespace. Agent misbehaving on one account can't affect others. Adding a new account is klaw create namespace [account] + deploy the same config. 30 seconds.

The key differentiator vs frameworks like CrewAI or LangGraph: those define how agents collaborate on tasks. klaw operates one layer above — managing fleets of agents across teams with isolation and operational tooling. You could run CrewAI agents inside klaw namespaces.

Happy to answer questions.

Target auditory - self hosted cicd systems with devops using general programming languages instead of yaml

Link to the article - https://github.com/melezhik/DSCI/blob/main/introduction.md

Disclosure - Feel free to ask me any questions or provide constructive feedback - I am the tool author

Thanks

https://github.com/fosrl/pangolin) is an open-source tool for identity-based remote access to internal resources - an alternative to Cloudflare ZTNA, Zscaler, and Twingate.

It’s different than existing approaches: mesh VPNs (Tailscale, ZeroTier, etc.) create flat overlay networks where ACL and IP space management becomes complex at scale and every device can talk to every other device, while corporate ZTNA solutions (Zscaler, Cato, Netskope etc.) are closed-source and add latency by forcing traffic through a central server.

Pangolin takes a resource-centric approach. You deploy lightweight connectors that bridge to specific resources (private web apps, SSH, databases, CIDR ranges). Admins delegate resource-access to specific users and roles. It uses WireGuard with NAT hole-punching for peer-to-peer connections and traffic goes directly between the user and connector instead of through a central server. It supports native clients (Mac/Windows/Linux/iOS/Android) plus identity-aware, browser-based access when a client isn’t required.

Pangolin has a cloud and is optionally self-hosted. The Community Edition is AGPLv3. The Enterprise Edition is also open-source under the commercial license which enables free personal/small business use.

Everything, from the server to the clients, is fully open-source and you can even self-host the whole stack. We’d love to hear what you think and I'm happy to answer any questions!

https://github.com/knadh/oat

Related: https://nadh.in/blog/javascript-ecosystem-software-developme...

With some `runtime.Callers` I can usually find the spot by just swapping the existing Mutex or RWMutex for this one.

Sometimes I switch the

  mu.Lock()
  defer mu.Unlock()

with the LockFunc/RLockFunc to get more detail

  defer mu.LockFunc()()

I almost always initialize it with `deadlog.New(deadlog.WithTrace(1))` and that's plenty.

Not the most polished library, but it's not supposed to land in any commit, just a temporary debugging aid. I find it useful.