The 4-week AI Readiness Workshop Series.

Learning outcomes

• Trainees write a 5-element prompt (role, task, audience, constraints, format) from memory
• Trainees identify which prompt pattern fits a given task (drafting vs. analyzing vs. structuring)
• Trainees ship their first reusable prompt template covering a real task they do every week
• Trainees understand and can articulate the difference between AI prompting and Google search

Modules

• 1.1 — What AI actually is, in 30 minutes

  0.5h

  Plain-English orientation. What an LLM is. What it is not. Where it works. Where it fails. The 30-minute model that orients the rest of the cohort.

• 1.2 — The 5-element prompt framework

  1.5h

  Role + Task + Audience + Constraints + Format. The framework practitioners use to write prompts that produce usable output on the first or second try. Live walk-through on attendees' actual tasks.

• 1.3 — Pattern library: drafting, analyzing, structuring, comparing

  2h

  Four prompt patterns that cover ~80% of professional work. When to pick which. Hands-on exercises applying each pattern to attendee-supplied work artifacts.

• 1.4 — Iteration loop and verification habits

  1h

  How to read AI output critically. The 3-iteration loop. Hallucination spot-check patterns. The verification habits that separate competent users from over-trusters.

• 1.5 — Async exercise — your first reusable template

  1-3h

  Each attendee builds and ships one prompt template covering a task they personally do every week. Peer review in a shared workspace.

Learning outcomes

• Trainees sort any piece of data into one of four sensitivity buckets (public / internal / regulated / secret) and pick the right tool for each
• Trainees apply the redaction pattern to a sample workflow without losing useful output quality
• Trainees draft a one-page AI acceptable-use policy applicable to their team
• Trainees can articulate what FAR 52.224-3 means for their use of AI on PII (for federal customers) or analogous obligations (commercial)

Modules

• 2.1 — The four-bucket data-classification framework

  1h

  Public / internal / regulated / secret. Where each bucket can go, where it cannot. Applied to AI tooling.

• 2.2 — Consumer plans vs. enterprise plans — the contract matters

  1h

  What an enterprise tier buys you (data-residency, training-opt-out, retention, audit logs). What you give up on a consumer plan. The procurement and legal questions to ask vendors.

• 2.3 — The redaction pattern

  1.5h

  Replacing specifics with placeholders before prompting. Mapping back after. Hands-on exercise on an attendee-supplied sensitive document.

• 2.4 — FAR 52.224-3 and analogous obligations for federal staff

  1h

  What the Privacy Training clause actually requires (for federal customers). Records-management obligations (NARA / 36 CFR Subchapter B). When PII or CUI is in scope, what changes.

• 2.5 — Drafting the one-page policy

  1-3h

  Each attendee drafts a 1-page AI acceptable-use policy for their team or business unit. Peer review and instructor critique.

Learning outcomes

• Trainees identify which of their recurring tasks fit each of the four AI-automation patterns (scheduled summarizer, email drafter, document classifier, briefing pack)
• Trainees prototype one automation workflow end-to-end using only the tools their organization already has
• Trainees measure baseline time per task and time after automation
• Trainees understand the limits of no-code and when to call an engineer

Modules

• 3.1 — Pattern 1 — the scheduled summarizer

  1h

  Daily / weekly summaries of an inbox, channel, queue, metric. Tool selection. Setup. Real-world cost.

• 3.2 — Pattern 2 — the email drafter

  1h

  Routine outbound email with human-in-the-loop. Draft folder pattern. Why this saves hours per week even for senior staff.

• 3.3 — Pattern 3 — the document classifier

  1.5h

  Inbound documents → classification → routing with the right metadata. The pattern most underused in small-business operations.

• 3.4 — Pattern 4 — the briefing pack

  1h

  Pre-meeting context auto-assembled and delivered to the calendar invite. Why this is the high-leverage one for senior staff.

• 3.5 — Build week — your prototype

  3-5h

  Each attendee picks one of the four patterns and builds the prototype on their own work data. Slack / email / Notion / Excel integrations covered. Daily check-ins with instructor.

Learning outcomes

• Trainees ship a personal prompt library of at least 5 templates covering their highest-frequency tasks
• Trainees present and demo their library to peers in a structured demo session
• Trainees receive structured feedback against the published rubric (L2 - learning outcomes)
• Trainees know how to extend the library on their own after the cohort ends

Modules

• 4.1 — Capstone scoping working session

  1h

  Group session: each attendee declares their 5 target tasks. Instructor helps shape scope for tractability.

• 4.2 — Library build — async

  5-7h

  Heads-down build week. Async instructor office hours twice per week.

• 4.3 — Capstone demo + peer review

  2h

  Each attendee demos their library in 5 minutes. Peer review against the rubric. Instructor feedback. Cohort photo and capstone artifact archive.