Three article series, plus a dictionary of traditional vegetables
Insights — every structure connects to one conclusion
Climate change, fossil resources, the Mythos era, enterprise IT taxes, drone warfare, healthcare and pensions, regulation redesign — AI changes how we work, farm, and live; this series unpacks the structure beneath.
Read 15 chapters →Tools for the free person of the AI era
Office for paperwork, Java/C# for business systems — but AI runs on Python and text. Markdown, JSON, Mermaid, Python, Linux — practical practices for keeping AI as a colleague. Includes hands-on examples with code and output.
Start with the prologue →A textbook you dialogue with, not just read
A new kind of textbook you read with Claude beside you. Learn the migration to Debian through dialogue, tailored to your own situation. At the end of each chapter, ask Claude "given what I've read, what should I do."
Start from the prologue →When phosphate fertilizer stops coming — economics decides the farming method
Phosphate fertilizer supply is contracting through three routes at once. Conventional agriculture's economics break down; the only viable path is farming that lets soil microbes take over the work. We track this structurally using World Bank, USDA, and MAFF primary data. Includes Cuba's "Special Period" as the world's only nationwide case study of fuel-and-fertilizer collapse.
Start with the prologue →Le Verdure Italiane — Mediterranean bounty and the stories of its food culture
From DOP and IGP certified varieties to regional landraces, a structured database covering the history, cultivation, and cuisine of 69 traditional Italian vegetables — built with AI research agents. (Currently in Japanese.)
Browse the dictionary →Boris Cherny, who built Claude Code, calls himself a "builder" and has not written a line of code by hand since last November. "Coding is solved," he says. But what does "humans will no longer be needed" overlook? Building an app is a cycle — finding structure, forming a hypothesis, and verifying it against reality. AI is not a partner that hands you the right answer; it is a tool that gives you the speed to keep up with change. From beside a field in Tokushima, where phosphate fertilizer is running out, and by way of Socrates, the printing press, and a Second Renaissance, this piece asks what it really means to build in dialogue with AI.
Microsoft CEO Satya Nadella wrote on his personal blog about "model overhang — capability outrunning our ability to put it to real-world use." But if that diagnosis is right, the place to invest is not $190 billion a year of infrastructure but the side that uses the capability we already have. AI chief Suleyman has openly said the goal is to "ultimately eliminate" what Microsoft pays Anthropic — exposing a structure in which the intelligence running underneath can be silently swapped out. Ironically, the very "intelligence that can replace an engineer" they spent so much to build has become the best partner for users who want to leave the cloud and self-host. With ONLYOFFICE, Ryzen AI Max, and open-weight models, this piece asks whether you can take a Microsoft 365 (Standard + Copilot) equivalent back into your own hands.
Microsoft's AI-first strategy is creating two problems. The first is internal to Windows 11 PCs — long-term support is not guaranteed past 2029, and the "AI PC" branding is largely cosmetic. The second is the bigger one this strategy itself produces: explosive data center expansion driving electricity demand and emissions. Windows 10's October 2025 end-of-support could push up to 400 million PCs into the e-waste stream, around 88 million tonnes CO2e from manufacturing alone. Microsoft's electricity use is up 168% since 2020 and total emissions are up 23.4%. Doubling data centers in two years while pledging carbon-negative by 2030 is structurally incompatible.
Windows 10 support ended in October 2025. Hundreds of millions of PCs are flagged "not compatible with Windows 11" — yet the hardware is fine. The same hardware runs Linux normally, and old PCs are arguably better suited to Linux. The "Linux is hard" reputation reversed twice in the AI era: AI is unusually good at teaching commands, and Flathub now offers a cleaner GUI app store than the Microsoft Store. With AI beside you, Linux commands are no longer hard. Now is the time to try Linux.
The widely circulated advice — \"in the AI era, become a specialized engineer; hold a deep specialty AI cannot take, like security or ML\" — misreads the structure. AI is absorbing the whole layer of software engineering, not a particular subdomain. The medieval analogue: telling a serf, \"become a more specialized serf and you will be free.\" Freedom comes from stepping out of the lord's structure of control, not from deeper specialization. Software engineer → builder, software engineering → liberal arts, employment → free person — these three transitions are unfolding inside the Second Renaissance (the historical turning point of the AI era, with the LLM playing the role of the printing press). Creation and upheaval are two faces of the same time, and Trump is the canonical figure on the upheaval side. The article compresses aiseed.dev's eleven-chapter \"AI-Native Ways of Working — Software\" sub-series into three pairs of words.