Field notes from inside the work — GEO, agent deployment, evals, and what actually survives contact with production. Written by the engineers doing it, not a content team.
Search is splitting into two motions — the blue-link index and the answer engine. This is the field guide we use to make a company the source an LLM quotes, not the one it skips.
Yes, you can deploy AI agents on PHI workflows — if the architecture is built for it from day one. BAAs, minimum necessary, audit trails, and the deployment patterns that pass review.
ReadCitation rate is the share of your category's buying queries where an AI assistant names you. Here's how to define it, measure it honestly, and what 'good' looks like by market position.
ReadHow a support agent actually reaches majority autonomous resolution without torching CSAT: the tier design, the escalation logic, and the eval discipline — with real deployment numbers.
ReadWhen a buyer asks an AI assistant for a vendor, the answer isn't ranked — it's assembled. Here's what the engines actually retrieve, what they trust, and how to become the company they cite.
ReadStraight numbers: what a production AI agent actually costs to build and run, what drives the price up or down, and where teams overspend. From a firm that publishes its prices.
ReadModel, orchestration, retrieval, evals, observability, guardrails — the six layers every production agent needs, what we use at each layer, and where teams cut corners they regret.
ReadPilot purgatory is an engineering problem, not an ambition problem. Here are the eval, ownership, and rollback gates that separate a demo from a deployed agent.
ReadA model you can’t measure is a model you can’t trust in production. How we build evals before we build the agent.
ReadWhat it actually means to embed engineers in your operation — and why it beats a deck-and-walk-away consultancy for the 20–500 person company.
ReadA step-by-step teardown of how we measure a brand’s presence across answer engines, and the gaps that are cheapest to close first.
ReadPHI, audit trails, and human-in-the-loop by design. The guardrails we put around agents in regulated workflows.
ReadSupport triage, onboarding, and renewal risk — ranked by time-to-value from real deployments.
ReadWhat changed in production AI this month. The signal, pulled from inside real deployments — not the hype feed.
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The agent patterns, model releases, and tooling that actually reached production this month.
Eval results and benchmarks from real deployments — what moved, what regressed.
GEO shifts: who answer engines started quoting, and why.
If you’d rather see it work than read about it, a 30-minute discovery call is the fastest path.
