Benchmarks, playbooks and stack guides for AI-native agencies.
11 posts
Agencies inherit half-built prototypes and ship them to production. Here is the agency-side framework for choosing an AI app builder whose database actually survives client handoff, scored across six platforms with worked numbers from a June 2026 retainer.
June 2026 rate cards for AI agency builds split by archetype: solo operator, 3-person team, 8-person team, 20-plus-person studio. Discovery, build, retainer, audit, and white-label bands per archetype, plus a worked example on what to charge for a 6-hour AI-agent build.
Four serious productization patterns for AI agencies in 2026 (audit sprint, subscription retainer, fixed-price build, white-label platform) scored on margin, risk, discovery, scalability and agent leverage. With a worked agency scenario for each.
A six-criterion tier list of the AI app builders that survive a client handoff in 2026, scored for source-code ownership, deployable target, bundled vendors, MCP provisioning, white-label flow, and the maintenance cost the client inherits.
The 2026 fixed-price SoW for AI app builds: five clauses generic templates miss, a decision matrix tied to agent-leverage, and a worked SoW excerpt for a $14,000 build.
The 2026 EHR formula has the same structure as the classic one and a different set of inputs. AI builders collapse delivery hours but introduce five new categories most P&Ls miss. Here is the formula, four-archetype benchmarks, a worked traditional-vs-AI example, and the five moves that actually raise EHR.
Most best-of lists score AI app builders on demo flash. The criteria that move agency margin are different: white-label depth, code ownership, programmatic provisioning, and how billing flows. A seven-criteria scorecard with the 2026 agency-resale math.
Where AI actually moves agency margin — and where it just adds noise. A framework for applying leverage to delivery, sales and operations, with the realistic efficiency gains and margin math behind each.
The roles an AI-native agency actually needs, the order to hire them in, and US/EU compensation brackets — plus the utilization and bill-rate math that tells you when each hire pays for itself.
Six repeatable models for turning bespoke AI work into productized offers — fixed-scope sprints, subscriptions, audits, white-label platforms and more — with price points and margin profiles for each.
A pricing ladder for AI builds — hourly, fixed-scope, value-based and outcome-based — with the dollar ranges, margin math and risk controls to move up it without torching trust.
