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AI Agents and Test Suites: Lessons from the Trenches

AI agents can help wrangletest suite maintenance—if you treat them likejunior devs. That means tight prompts, clear boundaries, and someone keeping an eye on them. Teams get better results when they feed agents sharp context and task them with small, scoped jobs instead of vague laundry lists... read more  

AI Agents and Test Suites: Lessons from the Trenches
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Why I chose OCaml as my primary language

OCaml’s grown up. Multicore support is in. So are user-defined effects. Under the hood, affine types, staged metaprogramming, and effect typing are steering it toward resource-safe programming—with actual thrust. Its type system still slaps: powerful modules, GADTs, algebraic types, and now first-c.. read more  

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Deeper theories of program design

A sharp teardown ofWindows vs. Unix file deletion semanticslands on this: Windows leans on read-write locks; Unix rolls with a looser, non-blocking vibe—more likeweakly-isolated DB transactions. It trades consistency for concurrency, dodging locks even if it means the rules get fuzzy. The post zoom.. read more  

Deeper theories of program design
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The great SQLite rewrite

Turso just dropped the alpha of itsRust-based SQLite rethink—rewritten from scratch to handle today’s mess:async APIs,built-in vector search, and actualconcurrent writes. Forget the old SQLite playbook. Turso’s version leans into modularity, bakes in deterministic tests, and still aims for SQLite-l.. read more  

The great SQLite rewrite
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How I Use Claude Code to Ship Like a Team of Five

Claude Code zips out Ruby functions, tests, and pull requests viaCLIprompts across multiplegit worktrees. It slays manual typing and ejects IDE plugins. It spins up ephemeraltest environmentsto replay bugs, pries open externalgemcode, and syncs branches, commits, and PRs in one go... read more  

How I Use Claude Code to Ship Like a Team of Five
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71% of Americans Say AI Could ‘Put People Out of Work Permanently’

Most Americans now see AI as a threat to their livelihoods, with71% fearing it could permanently wipe out jobs. The findings come from a new Reuters/Ipsos poll, which shows widespread anxiety across the US as AI threatens job security and challenges the future of employment. The World Economic Forum.. read more  

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Tiny Agents in Python: a MCP-powered agent in ~70 lines of code

A new demo walks through buildingTiny Agents in Python—just ~70 lines using theModel Context Protocol (MCP). No boilerplate. Just clean LLM-to-tool hookups with standardized agent configs. Agents plug into multiple MCP servers out of the box—from local filesystems to Playwright browsers—and handle .. read more  

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Context Engineering for AI Agents: Lessons from Building Manus

Failures make great teachers—especially for LLMs. Stuffing failed attempts right into the prompt helps agents recalibrate. It nudges their internal priors, cuts down on repeat mistakes, and sparks smarter behavior... read more  

Context Engineering for AI Agents: Lessons from Building Manus
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MCP Vulnerabilities Every Developer Should Know

MCP’s blowing up across platforms—but the security? Still sketchy. Think tool description injection. Botched OAuth. Open doors to supply chain attacks. The new MCP 2025-06-18 spec tries to clean house (no token passthrough, mandatory user consent), but most real-world setups either drag their feet .. read more  

MCP Vulnerabilities Every Developer Should Know
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Is GPT-5 really worse than GPT-4o? Ars puts them to the test.

OpenAI walked back its latest release after users flaggedGPT-5for sounding flat, hallucinating more, and losing creative spark. The fix? Rolling back to the friendlierGPT-4o. Head-to-head tests told a nuanced story:GPT-5nailed accuracy and structure across most prompts. But when the task called for.. read more  

Is GPT-5 really worse than GPT-4o? Ars puts them to the test.
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