• 10 July 2026

  Access is the moat, not the algorithm

  When any competitor can generate equivalent agent code, the scarce asset is permission to write into a customer's production systems and the accountability that earns it. Why outcome-aligned pricing and embedded delivery are the structures that win and keep that access.
• 8 July 2026

  The context flywheel: how each engagement makes the next one cheaper and the agents better

  In AI services, code is becoming copyable and cheap, so it cannot compound into a moat. What compounds is accumulated context: the library of exceptions, document variants, and write-back patterns that each deployment teaches the shared agent infrastructure. This post states that loop literally and argues why it is a context flywheel a new entrant cannot buy.
• 6 July 2026

  Where value accrues when the code is free: the cost anatomy of an AI services engagement

  When model inference and code generation cost almost nothing, the dominant terms in an AI services engagement become context acquisition and the human-in-the-loop exception tail. A line-by-line walk of which costs fall toward zero and which stay.
• 3 July 2026

  Why an agent does discovery and delivery better than a consultant does either

  A consulting engagement loses information at every handoff between discovery, redesign, build, deployment, and monitoring. One agent holding the whole arc removes the self-report gap and the handoffs at once, which is where the accuracy and the speed come from.
• 1 July 2026

  Forward-deployed agents, not just forward-deployed engineers

  The third-layer story has centered the scarce human forward-deployed engineer. The next move is that agents do most of that work, observing, mapping, building, and monitoring, while a small human core keeps the judgment and accountability that model capability relaxes but does not remove.
• 29 June 2026

  Code was never the moat: context is the only durable asset in AI services

  The deliverable a services-as-software firm sells and the asset that makes it defensible are two different things. As model inference collapses in price, the code an agent runs commoditizes, and the durable moat moves to the observed, accumulated context of how a specific business actually runs.