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...

Architectures since GPT-2 still ride transformers. They crank memory and performance withRoPE, swapGQAforMLA, sprinkle in sparseMoE, and roll sliding-window attention. Teams shiftRMSNorm. They tweak layer norms withQK-Norm, locking in training stability across modern models. Trend to watch:In 2025,..

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...

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..

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...

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 ..

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 ..

Salesforce’s AI Metadata Service (AIMS) just got a serious speed boost. They rolled out a multi-layer cache—L1 on the client, L2 on the server—and cut inference latency from 400ms to under 1ms. That’s over 98% faster. But it’s not just about speed anymore. L2 keeps responses flowing even when the b..

Modern AI broke the rulebook. By spitting outstochastic outputs from unbounded inputs, it flipped software dev from a game of precision to one of probability. Old tools—funnels, SLO dashboards, crisp A/B tests—don’t quite fit anymore. They were built for systems that behaved. Today’s AI stacks mov..

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..