Category

AI & Dev Tools

Reviews of AI coding assistants, agentic tools, and the workflows that make them useful.

• Cursor SDK Review: Building AI Agents With Known Limitations

  Cursor's new SDK exposes the same agent runtime that powers the editor. We break down what ships, where the documentation lags, and when the limitations matter for production code.

  2026-05-12

• OpenAI Codex Chrome Extension: Browser-Native AI Coding Agent Tested

  OpenAI's Codex Chrome extension puts its coding agent inside your browser tab. We tested the workflow patterns that pay off, the limits worth knowing, and how it fits next to Codex CLI and IDE agents.

  2026-05-12

• OpenCode vs Claude Code: Why 157K Developers Are Hedging Against Anthropic

  A measured comparison of OpenCode and Claude Code, the lock-in math behind the split, and a decision framework for picking one, the other, or both.

  2026-05-12

• Qwen 3.6 Plus API: Pricing, Benchmarks & Developer Access Guide (2026)

  A measured developer review of Alibaba's Qwen 3.6 Plus API — pricing vs GPT and Claude, 1M-token context behavior, coding benchmarks, and the access paths that actually work.

  2026-05-12

• OpenAI Codex vs Claude Code: Hands-On Python Benchmark for Devs

  We pointed Codex and Claude Code at the same Python codebase across refactoring, debugging, and agentic tasks. Here is what each tool shipped, where each one wins, and what the speed-vs-cost tradeoff actually looks like in practice.

  2026-05-12

• ModelScope Review: Alibaba's Model-as-a-Service Platform for AI Developers

  A hands-on review of ModelScope, Alibaba DAMO Academy's open-source model hub. Covers SDK setup, model discovery, ms-swift fine-tuning, and how it compares to Hugging Face for Qwen-family and DAMO research workflows.

  2026-05-12

• AdamsReview: Multi-Agent PR Reviews for Claude Code, Reviewed

  AdamsReview orchestrates multiple Claude Code agents for PR reviews. We break down how multi-agent review catches what single-pass LLM reviews miss, and where it fits in your pipeline.

  2026-05-12

• AI Note-Takers and Legal Risk: What Developers Should Know in 2026

  Otter, Fireflies, and Granola are facing class actions over consent and data retention. Here's what developers integrating AI transcription need to audit before shipping.

  2026-05-12

• Claude as a User-Space IP Stack: What an ICMP Ping Benchmark Reveals About LLM Latency

  Adam Dunkels wired Claude into a user-space TCP/IP stack and benchmarked it against ICMP ping. The latency floor it reveals is the most honest stress test we have for agentic Claude API workflows.

  2026-05-12

• yt-dlp: The CLI Video Downloader Developers Actually Use in 2026

  yt-dlp replaced youtube-dl as the default for programmatic video and audio extraction. Installation, format selectors, the Python API, and the production gotchas we hit running it across three real workflows.

  2026-05-12

• Build Your Own X: 10 Project-Based Tutorials That Actually Teach You How Software Works

  The build-your-own-x GitHub repo has 350k+ stars for a reason. Here are 10 from-scratch tutorials — databases, compilers, Git, neural nets — that teach how the tools you use every day actually work.

  2026-05-12

• Ratty Terminal Emulator: Inline 3D Graphics for Developers

  A measured look at Ratty, a terminal emulator pitching inline 3D graphics. Where the category fits, which workflows benefit, and what to verify before you switch.

  2026-05-12

• AI Coding Agents Must Reduce Maintenance Costs, Not Just Write Code

  Why evaluating Copilot, Cursor, and Claude Code by lines generated misses the point — and how to measure whether your AI tooling is adding or removing technical debt.

  2026-05-12

• Mythos AI Found a Real Curl Vulnerability — What It Signals for Security Audits

  Daniel Stenberg confirmed Mythos surfaced a real bug in curl, one of the most-reviewed codebases on the planet. Here's what that means for AI-assisted security review in your pipeline.

  2026-05-11

• Running Local LLMs on M4 Mac with 24GB RAM: What Actually Fits

  A measured guide to running 7B-32B local language models on a base M4 Mac with 24GB unified memory. Model size math, real tokens/sec numbers, and when Ollama, llama.cpp, or MLX is the right tool.

  2026-05-11

• Why Developers Are Quietly Turning Off Copilot and Cursor

  A measured look at the backlash against AI coding assistants — what the METR study and cognitive offloading research show about when hand-coding actually produces better engineers and better code.

  2026-05-11

• Why Local AI Should Be the Default for Developers in 2026

  The case for running models on your laptop instead of paying per-token API bills: where local AI (Ollama, LM Studio, llama.cpp) wins on cost, latency, and privacy, and where the cloud still earns its keep.

  2026-05-11

• Cursor vs VS Code: We Ran Both for 30 Days

  A practical 30-day comparison of Cursor and VS Code across multi-file edits, agent workflows, and pricing — based on actual usage.

  2026-05-11