Product Strategy

2026 September Thought Notes 220 notes this month | recorded from 2026-09-01 to 2026-09-10 Themes: AI and Agent Systems 105 · Daily Notes and Everything Else 44 · Product, Engineering and Open Source 34 · Self-Knowledge and Psychology 16 · Travel, Places and Cities 8 · Reading, Ideas and History 7 · Business, Investing and Career 3 · Content, Craft and Recording 2 · Body, Health and Daily Life 1 Everything from the month is kept here, filed by theme, each entry carrying its original timestamp. ...

2026 August Thought Notes 484 notes this month | recorded from 2026-08-04 to 2026-08-31 Themes: AI and Agent Systems 212 · Daily Notes and Everything Else 118 · Product, Engineering and Open Source 96 · Self-Knowledge and Psychology 36 · Business, Investing and Career 9 · Content, Craft and Recording 6 · Reading, Ideas and History 4 · Travel, Places and Cities 3 Everything from the month is kept here, filed by theme, each entry carrying its original timestamp. ...

Quick Navigation Start with the long read: 9 sections in the body above. 17 archived notes this month, filed under 7 themes: Daily Notes and Everything Else · 6 AI and Agent Systems · 4 Self-Knowledge and Psychology · 2 Content, Craft and Recording · 2 Business, Investing and Career · 1 Travel, Places and Cities · 1 Reading, Ideas and History · 1 For most of July I was in Shenzhen, and I also stopped briefly for a few days in other cities in Guangdong. ...

Quick Navigation Start with the long read: 12 sections in the body above. 34 archived notes this month, filed under 7 themes: Self-Knowledge and Psychology · 13 Daily Notes and Everything Else · 5 Business, Investing and Career · 5 AI and Agent Systems · 4 Product, Engineering and Open Source · 3 Content, Craft and Recording · 2 Reading, Ideas and History · 2 Prologue: A slack surface, and high density underneath In June I came back from Laos to Shenzhen. ...

2025 July Thought Notes 226 notes this month | recorded from 2025-07-02 to 2025-07-30 Themes: Self-Knowledge and Psychology 51 · Daily Notes and Everything Else 47 · Product, Engineering and Open Source 30 · Travel, Places and Cities 30 · AI and Agent Systems 23 · Reading, Ideas and History 18 · Business, Investing and Career 15 · Content, Craft and Recording 7 · Body, Health and Daily Life 5 Everything from the month is kept here, filed by theme, each entry carrying its original timestamp. ...

2025 June Thought Notes 181 notes this month | recorded from 2025-06-02 to 2025-06-15 Themes: Self-Knowledge and Psychology 55 · Daily Notes and Everything Else 34 · Product, Engineering and Open Source 27 · AI and Agent Systems 19 · Reading, Ideas and History 17 · Content, Craft and Recording 15 · Travel, Places and Cities 6 · Body, Health and Daily Life 6 · Business, Investing and Career 2 Everything from the month is kept here, filed by theme, each entry carrying its original timestamp. ...

2025 May Thought Notes 84 notes this month | recorded from 2025-05-03 to 2025-05-25 Themes: Self-Knowledge and Psychology 29 · Product, Engineering and Open Source 19 · AI and Agent Systems 10 · Reading, Ideas and History 9 · Travel, Places and Cities 6 · Daily Notes and Everything Else 5 · Business, Investing and Career 5 · Body, Health and Daily Life 1 Everything from the month is kept here, filed by theme, each entry carrying its original timestamp. ...

Introduction and self-positioning Annual Preface and Background 📅 Hi! 2025 ~ TIP: This article has a high density of information and is highly subjective. I have tried to include fewer opinions and more descriptions of my experiences, including my own experiences traveling, reflections on things I have experienced, and some experiences in making products. Experience is valuable, and I hope to leave more room for you to be touched and think. Just choose the content that interests you from the TOP. ...

A model needs a tool to check project status. A user asks, “What’s blocking the demo project?” The model understands the question, but has no way to read the project’s state. The experience we want is straightforward: the user adds their project service, authorizes access once, then returns to the same conversation and gets an answer grounded in data. What this article verifies Sources were checked as of October 3, 2026, using Nango source and client version 0.71.12. The local examples use Node.js 22+ and have been tested for tool discovery, input validation, and request/response handling, including a local replacement for the proxy adapter. Project data is synthetic; the experiment does not call a model or execute real OAuth and proxy requests through Nango Cloud. The public-server sections provide integration steps to test in your own account. Rolling documentation, pinned source, and cloud deployments may differ; a dependency version does not prove protocol support, and customer stories establish only their stated use cases. The available evidence also does not establish that external MCP tools are automatically imported into Nango’s Action catalog. ...

For a Personal Agent to earn repeated use, the user has to genuinely carry less of the mental load. If handing over an operation still means chasing progress, rereading results, and nagging it to fix mistakes, the delegation is not complete. One Instinct user documented his own stress test on Reddit: buying snacks across apps and monitoring flight prices, and also researching startups. He was satisfied with part of the results, but he also hit long waits between steps and website verification that required a human to step in. He was willing to let the agent find things and compare prices, and willing to let it prepare an order, but not yet ready to hand over his credit card and let it pay freely. Original stress-test post ...

The same support demo needs a WeChat version, a WhatsApp version, and different people and photos. The dialogue barely changes, but the image has to be rebuilt. IMStage keeps those changes inside an editable scene for product demos, teaching materials and fictional stories. Describe a moment in IMStage . AI opens the workspace and generates the dialogue and imagery. You can then edit messages, people, photos and layout directly, or ask for another change in plain language. ...

Calling Claude Tag a Slack bot misses its most consequential product decision. It turns a channel into a place where an agent can be authorized, remember, and keep working: a team shares one executor; each task runs asynchronously in a thread-level sandbox hosted by Anthropic; Agent Proxy injects external credentials at the network boundary; and the result returns to the public thread with a traceable record. The Claude Tag documentation describes these mechanisms in unusually concrete terms. ...

At the beginning of 2026, my GitHub contribution graph stayed nearly blank for several weeks. A few months later, the same graph showed hundreds of contributions in a single week. In July, this blog published 55 articles in Chinese , while GitHub’s contribution calendar recorded 733 contributions. Those numbers prove neither quality nor user value, much less a business result. GitHub also makes clear that contributions may include qualifying commits, pull requests, issues, reviews, and other activity; the number cannot simply be relabeled as a commit count. GitHub’s profile contributions reference ...

“Is common sense the same as the mechanism underneath?” That was where I got stuck while testing ideas across several industries. I had also reviewed the published work of 22 frontier AI teams and more than 70 people whose work is public. A pattern kept returning: pursue one long-running question, define what good work looks like, connect papers, code, and products, then turn production failures into the next round of tests. But the pattern still did not tell me where industry analysis should begin. ...

This is a thought experiment-style simulated interview. The respondents are composed of organizational psychology and organizational economics perspectives, and do not represent any real individuals’ original statements. In my June 2026 monthly review, I wrote: Incentive structures colonize personality. At that time, I studied several founders and observed myself. An organization initially selects a particular narrative, user model, and revenue framework primarily to launch a business. Years later, that structure reverses to filter what members can see, what they are willing to acknowledge, and which behaviors persist. ...

This piece is a thought experiment conducted through simulated interviews. The interviewees are composed of social psychology, editorial practice, and creator research perspectives and do not represent any real person’s original words. In November 2025, I recorded the phrase: “The creator’s loss: the scarcity of positive feedback.” In April 2026, I wrote: “Understanding generates positive feedback.” Together, these two sentences shift the question. Do creators truly seek only praise? When one hundred people like a piece but none articulate the contradictions it addresses, that void persists. Conversely, a single reader who precisely identifies how a detail altered their judgment—without public dissemination—might reignite the creator’s resolve to continue. ...

This piece is a thought experiment-style simulated interview. The respondents are composed of cognitive science, archival studies, and product design perspectives and do not represent any actual expert’s original words. In May 2026, I stopped using flomo. That month had no daily reminders, no faint sense of debt from “today’s notes still pending,” and no rapid conversion of thoughts into cards. Surprisingly, life didn’t thin out. Instead, Laotian cities, caves, injuries, strangers, and bars coalesced in late May into a more complete self-reading than fragmented pieces. ...

This is the sixth essay in Reckoning with Reality. The previous essay separated fast feedback from slow results. This one turns to a question that technological progress makes easy to neglect: when an old bottleneck disappears, where does the new one appear? Whenever a new tool arrives, people first imagine what it will eliminate. AI makes writing faster, code cheaper, translation nearly instantaneous, and video production possible without a full team. Work that once took days can now be completed in minutes. ...

This is the fifth essay in Reckoning with Reality. The previous essay asked what kind of action can produce evidence. This one examines the speed at which evidence arrives—and how speed quietly changes our goals. A friend told me that content and retail have one enormous advantage: fast feedback. Change the opening today and the view count responds within hours. Adjust the price or the page and clicks or sales may change at once. Compared with spending months building a product in private, only to receive a faint response at launch, this rhythm does make it easier to preserve morale. ...

This is the fourth essay in Reckoning with Reality. The previous essay examined how intelligent people use competence to escape. This one asks the next question: once we leave the study, what kind of action actually brings us closer to the facts? “Think less, do more” may be one of the hardest pieces of advice to dispute today. It sounds brave and direct, and it often works. Many people are stuck not because they lack ability, but because they never quite put their work into someone else’s hands. ...

This is the third essay in Reckoning with Reality. The previous essay examined the limits of profit. This one turns to a more personal question: why can greater ability sometimes make it harder to reach the facts? I used to think that avoiding something must look like scrolling on a phone, procrastinating, or doing nothing. Later I learned that the hardest form of avoidance to recognize is often remarkably diligent. It comes with thorough documentation, elegant architecture, an unbroken commit history, and late nights at work. ...

This is the second essay in Reckoning with Reality. The introduction began with a dinner-table argument. This essay asks only one question: what exactly does profit record on its scorecard? “If a business makes a lot of money,” my friend said, “that means it creates value.” My first impulse was to argue. Then I realized that calling him wrong was easy. Explaining precisely where he was right, and where he went too far, was much harder. ...

This is the introduction to Reckoning with Reality, a seven-part collection of audits on profit, action, technology, and choice. A few days ago, over dinner with a friend, we began talking about what to do next. “The essence of entrepreneurship is making money,” he said. “If a business makes a lot of money, that means it creates value. If it keeps losing money, it is wasting everyone’s time and capital.” ...

Same product, different name, different score There’s something I’ve been watching for a long time without finding the right place to write it down. In the same product community, you’ll regularly see two small tools with nearly identical features. One launches and sinks without a trace; the other gets shared repeatedly and draws serious questions. Look at both product pages: similar craftsmanship, similar pricing, landing pages built from the same template, even. The real difference sits in the small line under the maker’s name — “maintainer of such-and-such project,” “has written about xx for three years.” ...

I wasted years on this one sentence “If the product is good enough, people will come.” I believed that line for years. It fits the engineer’s worldview: code is verifiable, performance is measurable, and there’s an objective difference between good and bad. If the difference is objective, then the good thing winning is just a matter of time — the market is efficient, it just needs a while. That was my logic through my open-source years. Write the project well, keep test coverage high, take the docs seriously, and then wait. Wait for stars, wait for issues, wait for someone to mention it in a blog post somewhere. Sometimes the wait paid off. More often it didn’t. And every time it didn’t, my first reaction was the same one: the thing isn’t good enough yet, go back and keep improving it. ...

One morning, and three things that shouldn’t exist One morning I got up, made coffee, opened my laptop, and found the agents I’d left running overnight all parked at “done”: one had added full multilingual support to a small tool of mine — Chinese, English, Japanese copy, an i18n layer extracted; one had built reading-progress analytics for my blog; one had refactored a CLI I wrote six months ago into a plugin architecture. The code was clean. The tests were green. ...

The fifteenth tool list changed the question Over six months, I read roughly twenty or thirty “AI-era super individual” tool lists. Around the fifteenth, the pattern became hard to ignore: the lists differed far less than the competitive advantage each one promised. I use most of the tools they recommend. The problem was not that the recommendations were bad. It was that ten thousand builders could install the same stack in the same week. Their absolute capacity might rise, while the distance between them barely moved. ...

Suppose you had to place a bet today on one direction in AI agents. What is the first question you should ask? Most people ask whether the thing can be built. By mid-2026, that is often the least interesting part. The colder question is: why has nobody made this opportunity routine yet? The answer is a useful filter. If nobody has solved it because everyone just noticed it, competition is probably coming. If nobody has solved it because the work is dirty, slow, and carries consequence, there may be something defensible—or there may be no market. The rest of the article is how I try to separate the two. ...

A counterintuitive signal: it starts prompting you Start with a question. Suppose one day you open your workspace and the agent isn’t sitting there quietly waiting for your next command. It speaks first: “I noticed section three of yesterday’s proposal is still unfinished. I drafted something in the voice you used last week — want to take a look now?” Is that thoughtful, or is it presumptuous? Over the past six months I’ve noticed a counterintuitive signal while following agent launches, primary sources, papers, and benchmarks: more products are experimenting with agents that do not wait for the next instruction. They use available context, estimate what is worth doing, and bring a suggestion forward. ...

A Year Later, Why Does AI Still Feel Like Extra Work? AI now writes copy, translates documents, summarizes meetings, and inspects spreadsheets. Yet one honest question cuts through the excitement: has it taken over a business step, or do you still explain the background, judge the answer, and decide what happens next every time? The model may be smarter. The person carrying the context and the responsibility often has not changed. ...