Most workflow diagrams describe intent, and a platform needs behavior. Here is how to write decision rules and draw diagrams you can build from, with a template and a checklist.
Seven generative AI use cases with a line to revenue, each with a tool, a first step for this week, and what the research does and doesn’t show.
How to get AI drafts that sound like your client: real samples, a one-page voice profile, a Claude or ChatGPT project that loads both every time, and a three-phrase check on every draft.
A complete summary of Robert Cialdini’s Influence: all six principles plus unity, the seventh added in 2021, with the research behind each, where it hasn’t held up, and one honest way to use it in your marketing.
A written SOP is most of the spec for an AI agent. Eight steps to convert one, with a design studio’s proposal process as the example: 31 of 34 matches in testing, then proposals out in hours.
Most AI agents only get checked for whether they ran. A weekly routine and seven metrics to check they were right, with client cases where a healthy-looking number hid the problem.
How I built an AI campaign generator that turns one brief into a tested set of assets, using a dated input bundle, narrow prompts, a claims review and a holdout test, plus the places it broke on me first and a plan you can build Monday.
Learn marketing automation by designing the decision logic first, then building one measurable workflow in a tool you can operate yourself.
AI market forecasts are useful for direction, but opportunity is the gap between projected spending and realized ROI. This playbook shows founders how to test demand, account for trust constraints, and turn forecasts into weekly operating decisions.
Open rate is a noisy proxy for attention. I explain the email metrics tied to cash and inbox access, starting with revenue per recipient and inbox placement, with formulas, benchmarks and a one-screen dashboard a solo operator will use.