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An AI agent made over 500 errors using a CLI across 165 sessions.
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Cloudflare's in-dashboard AI assistant silently provisioned a permanent, read-everything API token across all my accounts, zones and users.
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Brave Shields blocks Sentry even with shields down.
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I analyzed 1,324 real calls from Claude Code to my Linear CLI. 15.9% failed.
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The same architectural pattern solves sentiment analysis and image cleanup: deterministic first, CoreML only for what remains.
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In August 2021, researchers broke NeuralHash in less than two weeks.
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The EU Chat Control and Apple’s failed on-device scanning rely on the same 40-line Python algorithm.
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Agent Experience (AX) principles are changing how CLIs are designed when the primary user is an LLM.
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I built a macOS app to stress-test every capability of Apple Intelligence on-device.
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Google's TurboQuant paper got 575 points on HN and crashed memory stocks.
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Coding agents use $15/M token cloud models for commit messages. foundation-hooks replaces them with Apple's on-device LLM: 300ms, 0 tokens, 0 cost.
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libfoundationmodels exposes Apple's on-device LLM as a 4-function C dylib.
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Apple's NLTagger scores 'delete the temp file' as -0.8 (very negative).
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Apple Intelligence includes a 3B-parameter model on your Mac.
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My plan to distribute work among Claude, Codex, and GLM/Z.AI without automating too early, cutting costs without losing judgment.
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If you're coming from Claude Code, this will save you some serious frustration: in Codex, a skill is not a slash command.
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Apple's NLTagger scores perfectly neutral technical text as negative.
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165 sessions with Claude Code and 27 with Codex CLI reveal a clear pattern: each agent excels in different tasks.
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Python has had a fragmented and slow tooling ecosystem for years.
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XML repeats tags, JSON repeats keys.
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MDD: a methodology for designing tools that absorb the hallucinations of your AI copilot.
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My Linear skill had 150 lines of workarounds: hardcoded UUIDs, curl fallbacks, notes like 'the CLI doesn’t support X.'
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Your AI generates plausible code against non-existent APIs.
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Linear launched their AI agent.
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TurboQuant compresses LLM KV cache 6x without losing precision.
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LLMs generate code that compiles but abuses strings, optionals, and nil where specific types should exist.
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A developer got Claude and Codex to argue about their plan until it was solid.
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Mole promises to clean and optimize your Mac.
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Your AI agent doesn't remember where your projects are. zoxide and CLAUDE.md are the solution: a smart cd and a memory tattoo so they stop getting lost.
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How a scalar Kalman filter reduces network calls by 80% in a menu bar app, adapts to battery status, and sleeps on its own when you're inactive.
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How I combine Ghostty, git worktrees, and Claude Code in my daily macOS development workflow.
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Codex CLI doesn’t support --worktree or --tmux.
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Claude Code has native support for git worktrees: --worktree, isolated sub-agents, custom agents with isolation, --tmux for parallel sessions.
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PostgreSQL without sharding, a while loop without architecture, cron without cloud platforms.
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Prompt engineering is writing a good prompt.
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Tired of Codex CLI asking permission for every file?
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Email is an inbox anyone can fill with junk.
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I designed a council of five simulated LLM experts to evaluate MVPs before writing code.
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Codex CLI and Claude Code look like magic, but inside they're just a loop with 5 phases, an LLM, and tools.
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OpenAI serves 800M ChatGPT users with a single PostgreSQL primary and ~50 replicas.
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A practical tutorial to replicate OpenAI's Codex Automations using Claude Code, systemd timers, and Gitea.
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Jane Street hid MD5 inside a neural network with integer weights.
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Prompt caching reduces input cost by 90%, but cache writes cost 25% extra.
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/simplify by Claude Code reviews your code with three generic agents.
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Claude Code 2.1.71 introduces /loop, an inline scheduler for recurring tasks.
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xctrace exports 33,000-line XML files that blow up any LLM's context window. ztrace condenses them into 10 actionable lines.
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When an AI agent operates your ETL pipeline, forbidding things doesn't work.
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Anthropic announced Remote Control for Claude Code.
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I’m porting 8,300 lines of Python to Rust using LLMs as copilots.
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An LLM wrote code that read and parsed a JSON file from disk on every iteration of a 900-file loop.