Everything here is free, and none of it is hype.
Frameworks, checks, templates, and guides for using AI inside real business workflows. Start with whichever matches the question you're actually asking this week.
Knowing whether your process, data, and team are ready to build on.
Concrete applications by business function, and what makes each one work.
A short, opinionated walkthrough of picking a first use case you can ship — and the traps to avoid.
The operating layer underneath it all: process, data, tools, ownership.
Plain-language foundations: what current AI can and can't do for a business.
From "we should use AI" to a working system: the concepts, the vocabulary, and the order to do things in.
The terms that actually matter — agents, RAG, context, evals — explained for operators, not researchers.
Designing workflows where AI does a step — not the whole job.
Map a workflow end to end — inputs, decisions, handoffs, outputs — and mark where AI assists and where people review.
Decide which outputs need a person's sign-off, where review sits in the flow, and how to keep it fast.
Wiring repeatable steps to run themselves — with or without AI in the loop.
Worked examples across sales, ops, finance, and support — what the workflow looks like before and after.
Getting reliable output for real tasks — briefs, checks, and structure.
Prompt patterns for repeatable work: briefs, structure, examples, and checks that make output dependable.
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