AI Coding
Posts tagged with AI Coding.
Categories
Tags
Filters1
Categories
Tags
Showing page 2 of 4 (31 total posts)

Ways to Make the Most Out of Claude Fable 5 (2026)
Get more from Claude Fable 5: pick the right effort level, plan with Fable while cheaper models implement, and claw back costs with caching and batching.

Web Scraping in the AI Age: What Actually Changed
Web scraping in the AI age broke twice over: LLMs killed the CSS selector, and AI crawlers exploded while referral traffic collapsed. Here is what changed.

Run Claude Code From Your Phone: The 2026 Remote Setup
Run Claude Code from your phone two ways in 2026: official Remote Control with a QR scan, or SSH and tmux over Tailscale for API keys and overnight runs.

Cut MCP Round-Trip Overhead by Looping Inside the Tool
MCP round-trip overhead can balloon a task from 2,000 to 150,000 tokens. Move the loop inside one MCP tool to collapse N calls into a single round-trip.

Host a Minecraft or ARK Server With Claude Code
Skip the $25/month managed hosts. Use Claude Code to self-host a Minecraft or ARK game server in 15 minutes with zero DevOps knowledge required.

I Audited 8 Months of AI-Generated Code. Here's What Nobody Talks About.
After auditing 8 months of AI-generated commits across 3 projects, the problems aren't bugs. They're patterns no linter or test suite catches: copy-paste architecture, false confidence, and tautological tests.

Best MCP Servers Worth Installing (And 5 That Waste Your Context Window)
The best MCP servers for Claude Code ranked by real context cost. 8 worth keeping, 5 that waste your context window, and the exact config I run daily.

Why the Most Productive Developers Aren't the Loudest AI Users
The METR study found AI tools make experienced developers 19% slower. The most productive developers use AI selectively and quietly. The loudest adopters ship the least.

AI Agents in Production: What Actually Works After 6 Months
Most AI agent projects die between demo and production. After 6 months running agents at scale, these are the patterns that survived: model routing, trace-based debugging, loop detection, and hard cost ceilings.