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Five years from GitHub Copilot to Claude Code. The more the direction proved itself, the harder life got for the earliest believers. Small models, workflows, standalone IDEs—foundation models swallowed them layer by layer. What remains sellable is clear; it just isn't software anymore.

A friend asked whether I should take an offer as an AI transformation expert. After a three-hour conversation, I wrote down my verdict: don't skimp during the vanguard phase, don't touch IDEs, and don't let your agent become a black box. GPT-5.5 launched two weeks ago; in the remaining 10 weeks, the world will be stunned by a wave of unexpected breakthroughs.

I spent two days automating with the Codex app, burned through a Pro account, and made virtually no progress. Switching to Codex CLI's Goal feature fixed everything immediately. At first I thought the model had gotten dumber, but then I realized: the agent form factor is solidifying, and humans shouldn't be chained to the screen anymore.

GPT-5.5 dropped today, just a month and a half after 5.4. Opus 4.7 came out last week, just two months after 4.6. What's even funnier is that GPT finally started talking like a human, while Opus stopped doing so. At this pace, even the half-life of judgment itself is getting shorter.

V4 capabilities sit around the Opus 4.6 tier, but pushing FP4 to production, making million-token context the default, and day-0 adaptation for domestic chips is a disaster for everyone in the inference infra business. Add GPT-5.5, Vision Banana, and LPM 1.0 into the mix, and this week has crammed in more new releases than the entire past quarter.

It started when my son quietly told me that he often couldn't get the little red flower for character recognition at school. I used a coding agent to build him a PAW Patrol-themed literacy game, all in about a day and a half. The most surprising part wasn't that my son refused to stop playing—it was my wife's reaction. For the first time, she truly felt that AI had landed right in our living room.

Price is fundamentally a supply-demand regulator, yet LLMs are stuck in a peculiar position—supply is locked by chip controls, while demand is pulled into completely different shapes by three types of users. The Coding Plan model, which once seemed self-evident, is now being repeatedly challenged.

Opus 4.7 dropped last night, so I didn't get any sleep. Got up, took it for a spin, casually sent a few PRs to OpenClaude that got merged into main, and pushed Qwen3-30B prefill on Strix Halo to near DGX Spark levels. Once agents are this capable, how many things one person can do simultaneously becomes a very concrete question.

Anthropic introduced real-name verification, and China is in an uproar. But honestly, this is no surprise. The AI industry has been in a state of war since 2023—chip bans, military contracts, model blockades. It's all too similar to the Qing Dynasty during the Industrial Revolution.

GitHub is becoming Xiaohongshu, and WeChat Official Accounts are becoming GitHub. A dumpling shop owner vibe-codes a skill, a Hollywood star is the first author on a GitHub repo, and it's trending on Moments to distill colleagues into skills. But skills might not be the point—agent interoperability is.

Aima Service refactoring retrospective. The product is like an emergency room—users don't care about the decor, only whether the doctor can treat them. Ran Claude Code and Codex in alternation for over a week, delivering 1.3 million lines of code. Looking back, the moat of code volume may already be gone.

While researching text-to-video models, I realized that Chinese models' dominance in the open-source language model community hasn't extended everywhere. Looking back over the past three years, from LLaMA to Qwen to DeepSeek, what has the open-source community experienced? And what is it waiting for now?

DeepSeek hit 100 million users with zero budget. Claude Code ships a version every day. DingTalk, Feishu, and WeCom copied the same feature within three days. The underlying logic of product competition has changed—money and volume are no longer decisive weapons.

Zero-friction onboarding plus extremely powerful AI intelligence—two pillars can't hold up a product. When users see an agent executing incomprehensible commands in the terminal, their first reaction isn't awe, it's fear. The missing pillar is progressive trust.

MiniMax surpassing Baidu in valuation is inevitable—Baidu doesn't even have a decent API. Traffic is shifting from humans to Agents. Infrastructure not built for Agents will eventually be used by neither humans nor machines.

When an idea takes only a few hours to validate as a product, when traditional price anchors begin to fail, when the AI tsunami has already risen to chest level—the value systems we know are being reconstructed.

The processes and systems accumulated by large companies have become burdens in the AI era. A small team of three to five people uses the exact same tools as ByteDance or Google—this is the once-in-a-decade window for entrepreneurs.