Focused on sharing high-quality AI content and practical implementation, helping people learn with fewer missteps and become stronger through AI.
This guide explains the Chrome DevTools Protocol (CDP), its history, core domains, how to launch Chrome with remote debugging, connect via WebSocket, manage sessions and target objects, and why higher‑level libraries are needed for reliable browser automation by agents.
Anthropic engineers increased daily code merges by eight times without changing models, hardware, or team size, simply by giving Claude a fully engineered context before it acts, a practice the article calls "context engineering" that replaces traditional prompt engineering.
Tencent’s free Marvis AI assistant, launched May 2026, operates at the OS level to read and write files, adjust system settings, perform remote Android control, and build searchable knowledge bases, promising to automate up to 80% of everyday computer work.
Despite the rise of million‑token long‑context models, hybrid retrieval‑augmented generation (RAG) solutions saw a 200% quarterly procurement surge while naive single‑vector RAG was abandoned by over 70% of firms, highlighting a mature, multi‑generation RAG technology stack that remains indispensable for enterprise AI.
Multiple mid‑to‑large R&D teams report that senior architects can boost requirement review and code iteration efficiency by over 40% with AI, while novices see a three‑fold increase in rework, highlighting the need to convert hidden expert knowledge into standardized, verifiable Agent processes rather than relying solely on prompt collections.
This guide explains how to craft effective prompts for ChatGPT, ChatGPT Work, and Codex by defining clear goals, providing background, specifying output formats, setting boundary rules, leveraging linked data sources and plugins, personalizing settings, and iteratively refining results with concrete examples for daily conversation, office tasks, and code scenarios.
Anthropic’s Q2 2026 internal review shows Claude Code boosting daily merged code lines eight‑fold, yet this surge uncovers new bottlenecks in verification, responsibility tracing, and collaboration, prompting a systematic redesign of engineering processes.
In an interview, Instagram head Adam Mosseri explains how AI is reshaping team structures, talent requirements, platform strategy, algorithm design, and content governance, emphasizing the continued importance of human judgment, taste, and transparent sourcing in a rapidly automated social ecosystem.
The article analyzes why Claude Code often ignores constraints in CLAUDE.md, identifies four root causes—including incomplete rule loading, vague descriptions, context overload, and lack of hard enforcement—and proposes a five‑layer governance architecture with concrete migration and troubleshooting steps.
The article analyzes why many enterprises’ AI Loop implementations amplify workflow chaos, presenting Deloitte survey data, a clear distinction between Agents and AI Loops, a five‑element engineering foundation, risk classifications, and a step‑by‑step, low‑risk rollout framework to ensure safe, measurable AI adoption.
