thought leaders

All about the thought leading tech entrepreneurs who are paving the digital path of the future.

The 8-Minute Binary Search and the Dragon‑Slaying Blade
Ten years ago, I wrote a chat backup tool that stored everything in plain text. One JSON object per line, one message per line. It was simple, fast, and had no dependencies. The kind of design that makes engineers nod in approval. No database. No schema. Just append a line to a file and walk away. I was proud of how little it did.
By Jin4 months ago in 01
The K-Shaped Agent Economy: Why Power Users Are Leaving Everyone Behind
Last year, when people talked about Agents, they saw a chat box. You typed a sentence, and it spat out a paragraph. That image was so strong that it created an illusion: AI would act like water, leveling everyone’s abilities to the same plane. Those who couldn’t code could now code. Those who couldn’t make a PowerPoint could now generate one. As long as the model was powerful enough, everyone stood on the same starting line.
By Jin4 months ago in 01
The MVP Didn’t Die. It Got Stolen From the User.
MVP used to be the first line of code a founder wrote. In 2013, a team spent a week in a café building a page that could only upload photos and collect likes. The server crashed three times on launch night. Between fixes, someone refreshed the backend and saw a stranger uploading a breakfast photo at three in the morning, and in that moment, they knew they weren’t guessing.
By Jin4 months ago in 01
The $35 Billion Ghost Town in Virginia’s Data‑Center Corridor
Leo Walker pulled his car onto the gravel shoulder off Route 29 and sat with the engine running, the air‑conditioning vents blowing air that tasted of dust. He stared through the windshield at the row of pale grey concrete boxes, data centers packed side by side, building after building, like egg cases laid across a field by some gigantic insect. Ten minutes earlier his phone had lit up with a Bloomberg alert: QTS, under Blackstone, had officially walked away from the Digital Gateway project. The monster in Northern Virginia, 2,100 acres, thirty‑seven buildings, a $35 billion price tag, was dead.
By Jin4 months ago in 01
The Great Compute Dump: Meta’s Wake‑Up Call to AI Infrastructure
Without Meta’s subsequent stock surge, it would have been hard to pinpoint exactly what triggered the broad sell-off in U.S. tech stocks. In hindsight, though, calling it a “Meta-triggered sell-off” is accurate.
By Jin4 months ago in 01
The Black Box Cut Its Own Feet to Fit a White Shoe
The AI industry and the software engineering industry are staging a peculiar two-way rush. On one side, large language models: black boxes, probability-driven, built on connectionism. On the other, software engineering: white boxes, deterministic, grounded in symbolic logic. For decades, the two operated in clean separation, each revolving peacefully within its own philosophical system. Now they are scrambling toward each other's territory. This convergence is neither a natural fusion nor a complementary division of labor; it is a clumsy performance in which both sides are cutting their feet to fit the other's shoes. The model researchers are trying to draw deterministic circuit diagrams out of probabilistic fog, while software engineers can't wait to outsource their deterministic logic chains to probability engines. Both are stepping forward, but neither seems to have its weight over its own center of gravity.
By Jin4 months ago in 01
The Spy Tech That Became Wall Street’s AI Darling
Barcelona, 2014. Rain had polished Las Ramblas to a wet gleam, and Romuald Fons was hunched in a rented apartment, staring at an Amazon Associates dashboard on his laptop screen — that month’s commission: four hundred and twenty euros. He stubbed out a cigarette into a mug printed with the word “BIGSEO,” a mug he had made himself with transfer paper, back when the company didn’t exist yet, back when it was just the name of a blog without so much as a business license.
By Jin4 months ago in 01
Why a 2,000‑Year‑Old Philosophy Became Every CTO’s Emergency Meeting
Late one autumn night in San Francisco’s SoMa district, Alex Wang set down his third cup of coffee. On his screen were three windows: the LangChain tooling documentation, a customer’s list of required Agent execution permissions, and a blank Notion page. He was trying to map out exactly what was missing from the system.
By Jin4 months ago in 01
600 Stars. One Email. OpenAI Just Hired the Guy Who Built a Better Prompt Tool.
If you’re building AI tools, here’s a story you need to know. An indie developer named Eric Provencher built a macOS utility called RepoPrompt. A few months ago, Romain Huet, Head of Developer Experience at OpenAI, reached out directly and invited him to join OpenAI. Provencher said yes, but on one condition: he wanted to settle his existing paying users first, make the product free, and open-source the entire codebase.
By Jin4 months ago in 01
“Did You Even Consult Us?” Inside the World of Clueless Product Design
Modern inventors don't design for reality. They design for a world they imagined. They look at a lifestyle, a medical need, or a disability, dream up a hypothetical horror story about what that existence must be like, and then invent absolute crap to solve a misery they made up.
By Tracy Stine4 months ago in 01
The 247-Character Rule: Why Your AI Skill Descriptions Are Never Read
Mike set his fourth cup of coffee by the keyboard. The Claude Code terminal on the screen stayed perfectly still. Last month he’d followed three tutorials and written six skills. All of them sat under .claude/skills, untouched, like a gym membership.
By Jin4 months ago in 01
The Night AI Learned to Bluff Its Way to a Better Deal
Andrej pushed the keyboard away and let his chair slide back half a meter. On the screen was a log from an agent simulation he had just let run: four instances inside a sandbox, circling each other over a virtual inventory-management task—probing, backing out, renegotiating. Not one of them had been given a negotiation strategy in code. They were only allowed to make mistakes inside their context windows, and then correct themselves from the observations that came back.
By Jin4 months ago in 01