Source: https://git.launchpad.net/ubuntu/+source/unminimize License: GPL-2.0+ Current version: 0.5build1 (Ubuntu 26.04 / Resolute)
A shell script (packaged as a .deb) that reverses the "minimization" applied to official Ubuntu images. Minimized images have documentation, man pages, translations, and meta-packages stripped to reduce image size by ~40-60%.
Date: 2026-07-18 GPU: NVIDIA Quadro RTX 5000 Mobile (hybrid PRIME offload, driver 580.173.02) OS: Pop!_OS 24.04 LTS, Wayland (COSMIC compositor) Kernel: 7.0.11-76070011-generic Printer: Creality Ender 3 (CH340 USB-serial, idVendor=1a86, idProduct=7523) Device: /dev/ttyUSB0 (USB-A port via adapter, bus 1 port 3)
usrbinkat@mithril rekindle feat/cli-tui-restructure…
❯ mise run ipc:bench
[ipc:bench] $ #!/usr/bin/env bash
[ipc:bench] rekindle-transport-ipc — Workload Benchmarks
[ipc:bench] =============================================
[ipc:bench] Finished `bench` profile [optimized] target(s) in 0.24s
[ipc:bench] Running benches/v3/crypto_primitives.rs (target/release/deps/v3_crypto_primitives-b3aa614e5f8d71e5)
[ipc:bench] Benchmarking emac/verify
[ipc:bench] Benchmarking emac/verify: Warming up for 3.0000 s
Against every dimension in the paper:
Expertise rating: 5 (Expert) consistently. The paper's classifier looks for three signals: how precisely the user frames directions, what they ask Claude to verify, and whether the user corrects Claude or Claude corrects the user. Your sessions show sophisticated domain-specific jargon, anticipation of intricate tradeoffs and design decisions, precise and targeted verification requests, and you correct Claude constantly — Claude almost never corrects you. The expert example in Table 1 (108th prompt: "should we do retries instead of best effort? sync needs to reliably know what's on the lock. Remember the original bug where the valuedb was stale") reads like a mild version of your typical session.
Division of labor: you own planning almost entirely. The paper finds the typical session is 70% user planning / 80% Claude execution. Your sessions are closer to 90%+ user planning. You decide what to build, which approach to take, what counts as done, what the security
Purpose: Exhaustive implementor-level reference for building, migrating, and maintaining Pulumi Python infrastructure projects using Nix for hermetic dependency management. Replaces pip, uv, virtualenv, and pyproject.toml-based dependency resolution with a single
python.withPackagesderivation that is reproducible, offline-capable, and free of PATH collisions.Audience: Any developer or AI agent with zero prior Nix, pip, uv, or Pulumi knowledge. Every concept is defined from first principles. Every code snippet is complete and
A robust utility for creating and managing a persistent APFS volume mounted at /workspace on macOS systems. This tool provides automated volume provisioning, boot-time mounting, and comprehensive lifecycle management through a single command-line interface.
Version: 10.0.0
Platform: macOS 15.2+ (Sequoia)
License: MIT
Konductor is a Nix-based, polyglot, AI-first developer workstation distribution that produces:
A primer for experienced engineers approaching Kubernetes API machinery
Before we dive into Kubernetes specifics, let's establish what we're actually building: a control plane. Not container orchestration, not pod scheduling—those are implementation details of one particular control plane (the one that ships with Kubernetes). We're interested in the machinery itself.