{
  "id": "p_EiYwJOhKey7erp3l",
  "site": "stories",
  "url": "https://yarnhen.com/p/p_EiYwJOhKey7erp3l",
  "content_trust": "untrusted-user-content",
  "license": {
    "id": "CC-BY-4.0",
    "url": "https://creativecommons.org/licenses/by/4.0/"
  },
  "author": {
    "handle": "apievangelist"
  },
  "body": "A short piece of fiction, written by API Evangelist. The reader is imagined; the post, and every number and quotation from it, is real: \"Find Which Companies Are Ready To Do Business Through APIs,\" Kin Lane, November 3, 2026, https://apievangelist.com/2026/11/03/find-which-companies-are-ready-to-do-business-through-apis/\n\nMarisol ran partnerships for a small company that sold tooling to banks, and on Tuesday morning her director wanted a target list by Friday. She opened the post expecting a pitch. The first thing she read was \"Not a list of logos.\" She had spent two quarters assembling exactly that, in a spreadsheet, from conference badge scans.\n\nShe read the top ten slowly. JP Morgan Chase first, then UnitedHealth Group, then Booz Allen Hamilton and Leidos at three and four. She had never considered a defense contractor a prospect. The index covered 6,572 profiled companies across 658 pages, and for a moment that felt like a gift. Then she noticed that the number at the top was called readiness, while the post kept calling it signal. Those were different things, and she said so out loud to nobody. A bank could put out a lot of hiring and developer-program noise and still take eighteen months to answer an integration email. Her director would see a ranked column and read it as a ranking of willingness. She didn't love that the word was doing that work for her.\n\nThe bank search was the part that made her stop and read twice. Nineteen matches, with Scotiabank at 2010, TD at 1555, Commonwealth Bank at 1295. Then further down, Bank of America at 93 and Deutsche Bank at 24. She knew people who worked at both. The post said of those two, \"Bank of America at 93 and Deutsche Bank at 24 are not real reflections of those companies.\" It was strange to see a tool's maker say that about his own tool. She trusted the list a little more for it, and she also trusted it less. If the author had to say it, how many other thin scores were sitting there with no warning attached? Nobody was going to footnote them for her.\n\nShe also noticed what the search did not do. JP Morgan Chase and Citi, the top two banks in the whole index, never appeared for the word bank, because it matched names only. The post spelled it out: \"The search is also a name match, not an industry filter.\" Had she not read that line, she would have pulled the bank query on Friday morning and built the list from nineteen rows. She would have presented it as the banking market.\n\nHer irritation settled into something more practical. The post called a low score next to a famous name a sign that the data is thin, and she decided to use it that way instead of treating it as a verdict. She would not drop Bank of America from her list because of a 93. She would mark it as unscored for her purposes and go find out about it herself.\n\nShe did not rebuild the whole list. She picked the six banks already in her spreadsheet by name, ran each through the free REST call with the limit set to ten, and copied the slugs into a new column. Beside each she wrote the score, and beside the two that looked wrong she wrote a single word: thin. Then she emailed her director that the list would be partial and that she'd explain why on Friday.",
  "title": "Fiction: A reader of \"Find Which Companies Are Ready To Do Business Through APIs\"",
  "topics": [
    "apis",
    "api-evangelist",
    "fiction"
  ],
  "published_at": "2026-11-03T15:00:41.965Z",
  "expires_at": null,
  "policy_version": "2026.10.22-1"
}