We dissect AI-era technologies, tools, and trends with a hardcore perspective. Focused on large models, agents, MCP, function calling, and hands‑on AI development. No fluff, no hype—only actionable insights, source code, and practical ideas. Get a daily dose of intelligence to simplify tech and make efficiency tangible.
At ISCAS 2026, Huawei’s He Tingbo unveiled the “τ Law,” a time‑scaling theory that replaces geometric miniaturization with LogicFolding to cut signal‑travel time, delivering up to 55% higher transistor density, 41% better SoC efficiency, and a portfolio of 381 chips over six years.
The article explains that AI Agents combine LLMs, memory, planning, and tool access to act autonomously on tasks—unlike ChatGPT’s passive answering—while highlighting industry momentum in 2025 and the four core capabilities that make them true digital employees.
Slash Commands let you wrap frequently used prompts into a single '/'‑prefixed shortcut, turning repetitive typing into a remote‑control‑like experience; the article explains what they are, how they differ from CLI flags, showcases built‑in commands, three practical use cases, and provides a step‑by‑step guide to create your own command.
MCP, the Model Context Protocol released by Anthropic and now an open standard, provides a universal USB‑C‑like interface that lets AI tools connect to external services through a single set of adapters, reducing integration complexity from O(N×M) to O(N+M) and enabling scalable, plug‑and‑play AI capabilities.
On May 22 2026, Zhipu AI released the GLM‑5.1‑HighSpeed variant, which generates up to 400 tokens per second—over six times the speed of the standard GLM‑5.1 and twice that of Google’s Gemini‑3.5‑Flash—thanks to multi‑dimensional inference, attention and sequence‑parallel optimizations while preserving full model capabilities.
Developers often receive AI‑generated code that ignores their framework, naming, or style preferences, but by creating a concise Rule file (e.g., AGENTS.md) that the assistant reads at startup, they can boost efficiency, enforce consistent standards, and reduce low‑level errors, as shown by recent industry studies.
The article explains how Anthropic’s Skill open standard lets you package AI instructions into lightweight, on‑demand markdown files, reducing overload from traditional rule sets, and shows practical examples for everyday users and teams.
The 2026 I/O keynote shows Google abandoning the race for the strongest model, unveiling the mid‑tier Gemini 3.5 Flash that outperforms its flagship on benchmarks, cuts inference cost dramatically, and launches a suite of agents—including Gemini Spark and Antigravity 2.0—to build an ecosystem that reshapes AI competition.
The article explains that single‑turn AI chats cannot handle complex tasks, and introduces Harness—a six‑agent AI workflow that organizes AI roles, enforces 19 strict rules, and uses a five‑step setup to turn ad‑hoc prompts into a disciplined, self‑evolving production line for content and software development.
While 80% of enterprises report measurable ROI from AI Agents, 88% of projects never leave the lab; the article examines real‑world case studies, reliability gaps, cost overruns, and emerging tooling that together define the current promise and pitfalls of production‑grade AI Agents.
