HOSTSecond deep dive today. From shoe design to the factory floor. Changshin and Palantir, and what connecting one chain really means.
PART 1 · THE DEAL — A SIGNED CONTRACT, NOT A LETTER OF INTENT
LEOOn November the 4th, South Korean shoemaker Changshin and Palantir signed a formal contract — not a letter of intent — to put Palantir's Foundry, the data platform, and AIP, the agent layer, into Changshin's development and production operations.
HOSTBefore signing, the two sides ran a validation round at an AgentCamp, using Changshin's real data, and built the first workflows together. Deployment is the next step. Contract value, term, which factories first, which systems it connects to: none of that has been disclosed. Nike is not a party to the deal.
LEOSome background numbers, about the company, not the project. Changshin was founded in Busan in 1981. It employs about 80,000 people worldwide. By April 2025 it had made one billion pairs of shoes in total. Korean media report it makes about 69 million pairs a year for Nike.
PART 2 · THE CHAIN — DEVELOPMENT, SAMPLING, SCHEDULING, EXECUTION
HOSTThe point is not AI designing shoes. It is connecting one chain: product development, sampling plans, factory scheduling, and execution. Decisions from development and results from the floor go into the same data. Problems surface earlier, teams argue less across functions, and what one generation of products teaches in production carries into the next.
LEOA Palantir executive put it this way: at every step, Changshin itself controls how AI is used. That line made it into the press release, which tells you it was a negotiating point, not small talk: whose hands hold the data, who approves each action — say it first.
HOSTOne discipline warning. Some articles online say the system will connect to ERP, predict equipment failure, or swap materials automatically. That is Palantir's general product brochure applied to this deal. The two companies' release and the Yonhap report name no system at all — no ERP, no MES, no PLM. Do not treat that as this deal's promise.
LEOAnd there are no outcome numbers at all. No lead time, no cost, no quality, no rework figures. The only fair conclusion right now is: the validation worked, the contract is signed, deployment has just begun. The real test comes when the first factories publish actual data.
PART 3 · THREE LESSONS
HOSTThree lessons to take away. First, connect the chain before you talk about intelligence. Most factories do not lack a tool for one step. They lack the data link between development, sampling, and production: a change reason never reaches the floor, a floor problem never returns to design. The value here is the connection, not any single agent.
LEOSecond, run a small validation with your real data before you sign a big order. Changshin did exactly that: real data, engineers from both sides, first workflows working, then the deployment conversation. That order works for buying any industrial AI.
HOSTThird, no baseline means no acceptance. It published no outcome numbers, and that is itself the reminder: before any AI project, measure today's lead time, defect rate, and rework rate. Without a baseline, you cannot say afterwards whether it was worth it.
LEOSources: Business Wire, the official release, November the 4th, 2026. And Yonhap News. That is the deep dive. Back to today's flagship.
Before any industrial AI project: measure today's lead time, defect rate, and rework rate. No baseline, no acceptance. 上任何工业 AI 之前,先量出今天的提前期、不良率、返工率。没有基线就没有验收。