AISynq

The feed

The things that would otherwise be a LinkedIn post.

One position per post, each one arguable. Open the ones you disagree with, because those are the ones with the reasoning underneath. No account, no algorithm, and every post has a permalink you can send to somebody.

10 posts

  1. Not building it21 August 2026

    The largest single win on a programme worth roughly $100M a year in operational value involved no model at all.

    #no-model-at-all
  2. Proving it worked20 August 2026

    Your AI prioritisation matrix scored that project 8.4. Ask the person who wrote the 8.4 where it came from.

  3. Proving it worked19 August 2026

    The operators had already built the ranking. It lived in their heads and a spreadsheet three of them maintained. Nobody had ever asked them to write it down.

    #nobody-asked-them
  4. What it costs18 August 2026

    Per-seat pricing on a feature with a per-use cost breaks quietly, at exactly the moment customers start liking it.

    #per-seat-per-use
  5. Building it17 August 2026

    The evaluation set is the cheapest line on any AI build estimate and the first one teams cut.

  6. Diligence15 August 2026

    "We could switch model providers easily." When did you last try?

  7. What it costs14 August 2026

    Two quotes for the same AI build differ by five times. It is almost never the model work.

  8. Diligence12 August 2026

    Search for an AI due diligence checklist and you get a generic venture template with an AI heading pasted on.

  9. Proving it worked11 August 2026

    You shipped it without taking a baseline. You can still build one afterwards, from data you already have.

  10. Not building it8 August 2026

    A real share of what gets scoped as an AI feature is a rules problem, a search problem, or a form with too many fields.

Next step

If one of these described a problem you recognise more precisely than you would like, that is the conversation.

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