#Agent-first LLM
9 related articles
·7 min
Harness Engineering: Why a Powerful Model Isn't Enough — Here's What Really Matters
A data-deletion disaster reveals the biggest AI Agent risk: the problem isn't the model, it's Harness design. Learn context management, process standards, and permission isolation.
Read more →
·3 min
GPT 5.6 Deep Dive Review: The Most Capable Model Yet — But Also the Most Confusing to Use?
GPT 5.6 brings major capability upgrades and new SOUL/TERRA/LUNA tiers — but also confusing entry points, hidden quota consumption, and a chat window crammed into a floating widget. A deep-dive review.
Read more →
·2 min
Deep Dive into Tencent Hunyuan Hy3: How a 295B MoE Model Cracks the Agent Deployment Challenge
Tencent Hunyuan Hy3 launches with a 295B MoE architecture activating just 21B params and 256K context. Hallucination cut from 12.5% to 5.4%, MRCR nearly doubled, with MTP and EAGLE decoding and Day-0 SGLang support.
Read more →
·5 min
Pylon Sync: An In-Depth Look at the Full-Stack Realtime Framework Built for AI Agents
Pylon Sync is an "Agent-First" full-stack realtime framework that treats AI Agents as first-class design citizens, reducing coding errors via strong conventions.
Read more →
·5 min
Cursor Reshapes AI Programming: Cloud Agents, the Origin Platform, and a Custom-Built Foundation Model
Cursor launches three major products: cloud agents on mobile, Origin — an agent-native Git platform challenging GitHub, and a custom foundation model with 10-20x compute. AI coding enters the Agent-First era.
Read more →
·3 min
Three-Layer Workflow Optimization for Claude Code: Requirements Extraction, HTML Specs, and Embedded Verification in Practice
Anthropic engineer Arno shares a Claude Code workflow: AI-driven requirements extraction, HTML specs over Markdown, and DOM-embedded verification to boost AI-assisted coding efficiency.
Read more →
Deep Dives·3 min
Single-Agent vs Multi-Agent: A Three-Step Decision Framework for Choosing the Right Architecture
Based on Anthropic's engineering practices, a detailed three-step decision framework for single-agent vs multi-agent architecture: bottleneck identification, technical feasibility, and business value filtering.
Read more →
Tech Frontiers·1 min
Google Anti-Gravity 2.0 Explained: The Multi-Agent Development Platform Replacing Gemini CLI
Google Anti-Gravity 2.0 officially replaces Gemini CLI with a desktop app, CLI terminal, and SDK. Powered by Gemini 3.5 Flash, it supports multi-Agent parallel collaboration and one-click Managed Agents deployment.
Read more →
Expert Opinions·2 min
Karpathy on the Future of Programmers in the AI Era: Outsource Thinking, But Not Understanding
OpenAI co-founder Karpathy explains why taste, judgment, and deep understanding remain irreplaceable for programmers in the AI era, plus startup opportunities in agent-native infrastructure.
Read more →