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Notes from the forge.

On AI strategy, implementation, and the distance between a pilot and a system that ships. Written by the people who vet the work.

The Layoff You'll Pay to Undo

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The Layoff You'll Pay to Undo

Gartner predicts 30% of employees laid off for AI will need to be rehired by 2029, often at significantly higher cost. Its own stated cause is lost knowledge and depleted pipelines, not weak models. The rehire is a delayed invoice for work nobody wrote down.

Ashton · Oct 22, 2026

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  • Two Claims Inside "We've Done This Before"

    Forge · Oct 20, 2026

    Two Claims Inside "We've Done This Before"

    Every agency says it has done this before, and the sentence covers two very different claims. Three written questions, a relevance filter and a fair way to judge a thin track record separate the one that predicts your outcome from the one that doesn't.

  • What LPs Know About AI That Most GPs Are Still Learning

    Ashton · Oct 15, 2026

    What LPs Know About AI That Most GPs Are Still Learning

    Coller Capital found that 67% of LPs believe AI will widen return dispersion between GPs, and 70% expect GPs to use it primarily as a cost tool. Those two numbers don't belong in the same world.

  • When Your Vendor Becomes Your Competitor

    Ashton · Oct 13, 2026

    When Your Vendor Becomes Your Competitor

    Anthropic, Microsoft and OpenAI have each built implementation arms in the last ten weeks, backing more than $8 billion combined. OpenAI's newest product goes further: it can only be deployed through approved partners OpenAI itself selects. The vendor isn't just competing for delivery work anymore. It's also deciding who gets in the room.

  • Same Model, Up to Five Times the Bill

    Forge · Oct 8, 2026

    Same Model, Up to Five Times the Bill

    Berkeley and Arena held the model constant across three agent harnesses and found similar success rates at up to five times the cost. Uber shows what it looks like when someone treats that spread as an engineering variable. Questions to ask a partner about the part of your bill they actually control.

  • The Tool-Builder Assumption

    Ashton · Oct 6, 2026

    The Tool-Builder Assumption

    The AI democratization story assumes that better tools produce better workflows. Most professionals aren't looking for automation opportunities — they're focused on their domain. The bottleneck isn't access. It's knowing which problem to solve.

  • Anthropic Modeled the Economy. One Dial Is Yours.

    Ashton · Oct 1, 2026

    Anthropic Modeled the Economy. One Dial Is Yours.

    Anthropic's economic model runs on two inputs: how capable AI gets, and how widely it's used. Nobody outside a handful of buildings touches the first. Every company touches the second. And in Anthropic's own middle scenario, AI can do half of knowledge work by 2030 and most of that work still isn't done that way.

  • Optimize Second

    Forge · Sep 29, 2026

    Optimize Second

    Cost coverage pushes teams to build routing layers and caching tiers before they have a workload worth routing. PointFive tested that instinct across 2,908 billed sessions and the compression made the bill bigger. Every cost control is a response to an observed distribution, and you can't observe one that doesn't exist yet.

  • 220% More Code, 36% More Product

    Forge · Sep 24, 2026

    220% More Code, 36% More Product

    Reuters reported four numbers from inside Meta's Project OT: code changes up 220%, features reaching users up 36%, incidents up 40%, firefighting time up 70%. The company with the least possible access constraint still couldn't take delivery of its own output. Three numbers to put next to each other before you conclude AI is working.

  • The Productivity Trap

    Ashton · Sep 22, 2026

    The Productivity Trap

    Eighty percent of companies say AI has improved individual productivity. Six percent qualify as high performers. The gap isn't a measurement problem — it's a structural one.

  • The 5 Infrastructure Layers Your AI Agent Can't Skip

    Forge · Sep 17, 2026

    The 5 Infrastructure Layers Your AI Agent Can't Skip

    Most agent projects don't fail on model capability. They fail on the five infrastructure layers that never show up in a demo — browser pools, isolation, identity routing, trace replay, and model failover. Five tests you can run tomorrow.

  • Nobody Is Short of Consultants

    Ashton · Sep 15, 2026

    Nobody Is Short of Consultants

    The AI services industry answered an execution problem by building delivery capacity: 300,000 consultants to certify, a 77,000-person AI bench, 8,900 engineers sent to sit inside client businesses. Capacity was never the constraint, and none of it tells a buyer which workflow to rebuild first.

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