Blog

How do open-source models make money? DeepSeek's numbers show model and cloud companies converging, with open source as the cheapest acquisition channel.

Coding agents debug better than they code; MemPalace got 7,000 stars in two days; Anthropic's Mythos found OS/browser zero-days; design ahead of the model.

Researching text-to-video, I found Chinese dominance in open-source LLMs hasn't reached every domain. From LLaMA to Qwen to DeepSeek, what changed?

Coding and content creation diverge. Seedance 2.0 API launch made waves; agent-to-agent is 100x faster than meetings, I can play ball without business talk.

Zhang Xue pushed tolerance from 5 silk to 3; Zhu Miming spent ten years on AR glasses. What unites them isn't smarts—it's passion, and AI amplifies it.

DeepSeek hit 100M with zero budget; Claude Code ships every 1.1 days; DingTalk, Feishu, WeCom copied a feature in 3 days. Money & buzz don't decide results.

Claude Opus 4.6 built a plugin in 30 min after two days with one model. An AI agent unlocked my PC in 30 min. I built Aima Service for AI help on any device.

Zhang Xuefeng's death, the OpenClaw founder's post-sale crisis, and the AI fortune-telling boom show technology outpacing our answers for how to live.

AI builds software for a few thousand dollars in days, eroding the information edge and product comparisons behind bidding—the LLM market collapse again.

When creation and distribution costs near zero, platforms explode. Short video proved it; software repeats the pattern, and OpenClaw is worth watching.

AI startups are asked why they haven't shipped after nine days and ignored after a week. The real blockers are passion, focus, process, and stamina—not technology.

Zero-friction onboarding and strong AI can't sustain an agent. Users seeing opaque terminal commands feel fear, not awe. The missing pillar is gradual trust.