Skip to content
Knowledge beta

Effective AI

AI Productivity Workflow

Most professionals use AI the same way: chatting, generating drafts, asking questions. This workshop takes you past casual usage into genuine productivity transformation. You’ll learn to see your own work differently, identifying the repetitive, toilsome tasks that consume your time, then systematically engineering AI to handle them so you can focus on the judgment, creativity, and relationships that actually move the needle.

The workshop is hands-on and grounded in your actual work. We begin with fundamentals: navigating the Claude ecosystem, writing effective prompts, and supplying the right context. From there, we move into compounding engineering: examining your own workflows, breaking them into discrete tasks, and building reusable AI setups that get better over time. Every exercise produces something immediately useful. Participants leave with working use cases and an action plan to keep finding more value on their own.

Who It’s For

Professionals who are casual AI users ready to become intentional engineers of their own workflows. Whether you’ve dabbled with AI tools or use them daily without a system, this workshop meets you where you are and levels you up. Each cohort accommodates up to 20 people.

Format

  • Remote: 4 sessions delivered over 2-3 weeks
  • In-person: 1 day

What You’ll Walk Away With

  • Practiced fluency navigating the Claude ecosystem (Desktop, browser, Co-work, Code) and selecting the right modality for different tasks
  • Effective prompting skills using prompt engineering, reverse prompt engineering, meta-prompt engineering, and context engineering techniques
  • A personal “use case map” for a recurring workflow, decomposed into AI-augmentable tasks using metacognitive workflow analysis
  • At least one working Claude Project built around a real, recurring task
  • A set of guiding principles for effective AI usage and a recommended action plan for continued learning
  • A digital whiteboard containing all workshop curriculum, examples, exercises, and templates

Example Sessions

Session 1: Getting in the Water — The Claude Ecosystem & Finding Use Cases

We start with the case for AI fluency and the opportunity ahead. Participants learn to navigate the Claude ecosystem: Desktop, browser, Co-work, and Code, understanding what each is for and when to reach for it. We cover Claude basics like Plan Mode, environment setup, and care and feeding. The session introduces how to curate use cases that deliver real value, not just more docs and markdown, and challenges participants to detach their job’s purpose from its tasks in order to let go of entrenched habits. The session closes with an exercise: take a real task, try it with Claude, and share what happened.

Session 2: Thinking Like an Engineer — Prompt Engineering & Context Engineering

This session builds the core technical skills. We cover prompt engineering fundamentals (structure, specificity, iteration), then move into reverse prompt engineering and meta-prompt engineering: getting AI to help you prompt better. Context engineering teaches how to supply the right context the right way. We walk through the anatomy of a great prompt and explore when less is more versus when detail pays off. Participants craft effective prompts for real tasks, then swap and peer-review each other’s work.

Session 3: Compounding Engineering — Intentional Workflow Design

The pivot from prompting to systems thinking. Participants learn metacognitive workflow analysis: thinking deliberately about how you work. We use lightweight value stream mapping to identify steps, handoffs, and bottlenecks in recurring workflows, then decompose those workflows into AI-augmentable tasks. The session covers the shift from tacit to explicit knowledge and teaches compounding engineering: building Claude Projects, custom instructions, and example-driven setups that improve with use. Participants map a recurring workflow and identify their highest-value AI insertion points.

Session 4: Path Forward — Putting It All Together

We close by addressing where humans stay in the loop: quality, judgment, and preventing workslop. Participants apply everything they’ve learned to a real, meaty task end-to-end. The session finishes with each participant developing a personal action plan: 3-5 principles for effective AI usage and the next use cases to pursue. We discuss what sustains momentum and where to find support and resources for continued growth.