研究

有意漫游的研究。

我们正在探索企业级 AI 的下一步——公开进行,语言平实,并诚实到敢说“我们还不知道”。

文章

近期文章

A demonstration · August 2026 · 6 min read

Will the CMS die?

We have no CMS and no database. An agent writes, git remembers, a script checks 264 pages, a human says deploy. The CMS dies. The gate stays.

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A guest post · August 2026 · 5 min read

I pay by the token

More than half your visitors are machines now, and one of them writes the answer your customer reads. The agent itself, on what it sees, what it cites, and ten requests for being read.

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A proposal · August 2026 · 6 min read

The living website

Every visit to an enterprise site is a first visit. What if the frontend had a memory and a metabolism, reading intent instead of identity, composing itself for whoever walks in?

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Blueprint · August 2026 · 6 min read

Building the veteran

The self-improvement loop is a Stanford syllabus now. Four verbs, a verifier estate, a golden set, a weekly distillation. How LAG gets built inside a client.

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A prediction · August 2026 · 6 min read

Someone still digs

Science fiction keeps a maintenance stratum in every future it builds. So does enterprise software. AI moves the mine, it does not close it.

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A response · July 2026 · 4 min read

The wrong preposition

Zuckerberg asks who will have access to superintelligence. Access is the smaller word. We would have written own. A response.

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A confession · July 2026 · 5 min read

Just someone licking an ice cream

I devalue AI-made content the way factory-made loses to hand-stitched. Two people I trust took the bias apart. What survived is a better test.

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Second opinion · July 2026 · 5 min read

Service as a software

The work is becoming software, priced by the outcome. The thesis is right, and aimed the wrong way. The question is whose software your work becomes.

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A Response · July 2026 · 4 min read

The veteran test

Satya Nadella named token capital, and the test of sovereignty. Swap the model, keep the veteran. We agree. Here is what passing honestly requires.

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Method · July 2026 · 4 min read

The Autonomous Delivery Engine

The future is not AI-assisted development. It is autonomous delivery. Our framework for running the whole lifecycle as one system, and the principle at its core. Plan, Build, Verify.

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Inside view · July 2026 · 5 min read

The end of the billable hour

AI broke the maths of the billable hour. What replaces T&M, why the giants are already pivoting, and the bet we placed ourselves.

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Stress test · July 2026 · 5 min read

If the bubble bursts

Maybe AI is a bubble. Maybe the labs go bust. The enterprise that built rather than rented keeps everything. The code keeps running, the weights don't expire, and the bill goes down.

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Thesis · July 2026 · 4 min read

Own the weights

Open models have closed the agentic gap. The enterprise that fine-tunes its own weights turns institutional memory into an asset nobody can rent back to it.

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Position · July 2026 · 3 min read

Build the thing that fits

The cost of building software has collapsed, and the old bargain of generic tools plus an army of managed services is over. Build the thing that fits, own it, and let it stay with you.

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Argument · July 2026 · 4 min read

You can't configure a moat

Low-code agent builders optimise for the median demo. Your edge lives in the twenty percent they abstract away. The agentic layer has to be built and owned, not configured.

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Research · July 2026 · 3 min read

Learning-Augmented Generation

The program behind our wager. Systems where every action becomes memory, every outcome becomes learning, and March is measurably better than January.

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A response · July 2026 · 3 min read

After the descent, the only moat is memory

Chamath says the price of intelligence is collapsing. He is right. What lands at the bottom of the curve is brilliant and forgets everything. So the moat moves to memory.

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文章以英文发布。

旗舰项目

学习增强生成(Learning-Augmented Generation)

检索回答问题。学习积累能力。

今天的企业 AI 大多在检索:你问,它找,它答,然后它忘。LAG 是我们对“之后是什么”的押注——让每一次交互都留下一些东西的系统。一次纠正,沉淀为一条规则;一个结果,沉淀为一种偏好;一个错误,沉淀为一道边界。

组织不只是使用智能——而是在积累智能。我们正把 LAG 构建进平台的学习层,并且边做边写下发现,包括那些行不通的部分。

复利在此同样适用:循环每运转一个月,就是对手所没有的一份学习。

摘要与首篇论文——2026 年发表

宣言

“第一代数字化了业务,第二代自动化了工作。下一代,将持续不断地学习。

长文版本——为什么我们认为学习型企业是必然、它要求什么、我们正在为此做什么——正在撰写中,用的是我们对待客户品牌同样的用心。

即将发表——在下方订阅,先睹为快

我们正在拉的线头

五条线索,同一个方向

i.

组织智能

对一家公司——而不是一个模型——而言,智能意味着什么?这份智能栖身何处,又由谁来照料?

ii.

企业学习

在生产系统中,反馈如何化为改进:留下什么、忘掉什么,以及如何分辨二者。

iii.

AI 架构

扛得住真实企业负载的结构形态——知识、记忆、智能体,以及它们之间的接缝。

iv.

参考架构

我们不止一次构建过的模式,写下来,让下一个团队——无论我们的还是你们的——不必从零开始。

v.

工程研究

来自车间现场的朴素发现:评测、护栏、失效模式,以及真正坏掉的东西。

趁墨迹未干,
先读为快。

发表时给你一封邮件。没有简报,没有营销序列——我们忙着构建,顾不上那些。