Add real AI skills.
Be Kreative.

3–5 stakeholder interviews. We capture your challenges, current tools, workflow pain points, security concerns, and what you actually want AI to do.

By the end of Day 1: we know where your time and money are leaking.

We map 3–7 of your core workflows and score each one on pain, frequency, ROI potential, feasibility, and risk.

By the end of Day 3: every automation opportunity in your business is on one scored list.

We rank the opportunities into automate now / automate later / avoid — with honest ROI estimates, not hype.

By the end of Day 4: your top 3 automations are ranked, with the numbers to justify them.

A 60-minute readout call in plain English, plus your 30/60/90 roadmap and a recommended first build with measurable payback.

By the end of the sprint: you know exactly what to do first, what it costs, and what it returns.

You will understand what AI is, what an LLM is, what these tools are good at, and where they fail.

By the end of Hour 1: you will have a fundamental understanding of how LLMs work and how AI can fit into your daily work.

You will learn how to write better prompts using context, examples, roles, constraints, and clear instructions.

By the end of Hour 3: you will be able to prompt an LLM for real tasks with more confidence and better results.

We review the major AI tool categories and identify what is useful, what is hype, and what fits your situation.

By the end of Hour 5: you will have a better understanding of which AI tools are worth your time and which ones to ignore.

You will turn one repeated task, problem, or frustration into an AI-assisted workflow.

By the end of Hour 7: you will have one working AI workflow built around something you actually need.

We clean up your workflow, answer questions, review common mistakes, and create your next-step plan.

By the end of the class: you will leave with a practical AI starting point, a clearer understanding of how to use AI, and a workflow you can continue building on.

We begin by reviewing your organization’s goals, challenges, current tools, current AI usage, workflow pain points, and team readiness.

By the end of Step 1: you will have a clearer understanding of where AI can help, where it should not be forced, and which areas deserve attention first.

We identify the most practical AI opportunities across your organization. This may include writing, research, communications, customer support, operations, training, content creation, automation, or internal knowledge management.

By the end of Step 2: you will have a prioritized list of AI use cases based on usefulness, ease of adoption, and business value.

We map out the recommended tools, prompts, workflows, and processes that make sense for your team. This includes what to use, when to use it, and how each tool fits into the larger workflow.

By the end of Step 3: you will have a custom AI stack blueprint designed around your organization’s actual needs.

We build practical prompts and repeatable AI-assisted workflows your team can use. These are designed around real tasks, not generic examples.

By the end of Step 4: you will have working AI workflows that support your team’s day-to-day work.

We test the workflows, simplify the process, remove confusion, and refine the stack so it is easier for your team to understand and use.

By the end of Step 5: your AI stack will be clearer, more practical, and better aligned with how your team actually works.

We provide a walkthrough of the AI stack, explain how the workflows fit together, and deliver supporting documentation so your team is not left guessing.

By the end of the project: your organization will have a practical AI starting point, a clearer tool strategy, repeatable workflows, and a roadmap for continued AI adoption.