Live Workshop

Prompt Engineering for Business Operations

A practical 3-hour workshop designed for SMB operators, managers, and team leads who want to stop wasting time on bad AI prompts and start getting consistent, usable results on the first try.

Learn the exact framework that reduces prompt iteration from 3-5 attempts down to 1.

Individual - $297 Group Class - $1,997

What You'll Master in This Workshop

Four core competencies that transform how you interact with AI tools

Token Architecture

Understand how LLMs actually process text as tokens, not ideas, and why the first 50 tokens determine your entire output quality.

Rules → Role → Goal Framework

Master the exact sequence that eliminates guesswork and delivers consistent, professional results every single time.

5 Business Templates

Walk away with immediately usable prompt templates for sales emails, documentation, job postings, financial analysis, and meeting prep.

Iteration Reduction

Learn the techniques that cut your prompt refinement from multiple attempts down to getting it right on the first shot.

Course Details

Duration

3 hours (or 2x 90-minute sessions)

Format

Live workshop via Zoom or in-person

Materials

Templates and cheat sheets included

Audience

Business operators and team leads

What You'll Receive

Token architecture cheat sheet

15 business prompt templates

Company implementation checklist

Recording of the session (if live virtual)

The Problem

Why Most Teams Waste 60% of Their Time on Bad Prompts

You're asking AI to "be creative" or "make it professional" without defining what those terms actually mean for your business context. You start prompts with social pleasantries like "Hi, can you help me with..." or "I'm looking for some ideas on..." These opening words waste your most valuable tokens on noise instead of direction.

Here's what most people don't understand: LLMs don't "understand" your intent. They break your text into tokens—sub-word units—and predict the most probable next token based on everything that came before. Your opening tokens set the trajectory for the entire response. Think of it like navigation: a 1-degree error at the start puts you miles off course by the end.

The Real Cost: Teams spend 60% of their AI interaction time iterating on poorly structured prompts. That's not a training problem—it's an architecture problem. You're treating LLMs as magic boxes instead of steerable prediction engines.

The Core Framework

Sequence Architecture

Every effective business prompt follows the same sequence. This isn't about being polite or creative—it's about aligning with how the model actually processes information.

Rules

Set constraints, format requirements, and eliminate unwanted paths before processing begins.

Role

Activate the relevant knowledge domain. Different roles pull different language patterns and expertise.

Goal

Define measurable success criteria. Vague goals produce vague outputs.

Context

Provide relevant data only after the framework is established.

"Rules first clears the whiteboard. If you put rules at the end, the model has already committed to a direction and will resist course correction. This sequence isn't arbitrary—it's how token processing actually works."

Real Business Example

Customer Complaint Response

Typical Approach (Bad)

Can you help me write a response 
to this angry customer? They're 
upset about a delayed shipment 
and want a refund. Make it 
professional but friendly.

Result: Requires 4-5 iterations to get usable text. Output is generic, overly apologetic, and doesn't actually solve the problem.

Sequence Architecture (Good)

Rules:
- No apologies beyond first sentence
- Offer solution before explanation
- Use "we will" not "we'll try"
- Max 4 sentences total

Role: Customer service manager 
with authority to resolve

Goal: Retain customer, process 
refund/replacement within 24 hours

Context: Customer ordered $340 
product Dec 15, expected Dec 22, 
not received by Dec 28. Frustrated, 
mentions competitor prices.

Draft response.

Result: One iteration. 52 tokens. Actionable response that keeps the customer.

The Output That Works

5 bullet points max. Each includes: topic, position, data point, anticipated objection. Under 200 words total.

Role

Strategic advisor preparing executive for negotiation

Goal

Executive enters meeting with clear positions and counter-arguments

Avoid These Pitfalls

Common Mistakes That Kill Your Prompts

Putting Constraints at the End

When you place rules after the context, the model has already committed to a processing direction. It will struggle to backtrack and often ignores late constraints entirely.

Fix: Always start with rules. They're not an afterthought—they're the foundation.

Using Subjective Goals

Phrases like "make it good," "be creative," or "sound professional" mean different things to different people. The AI has no shared context for these subjective terms.

Fix: Define measurable outcomes. Specify word count, response rate targets, completion time, or other concrete metrics.

Making the AI Guess Your Constraints

Hoping the model will figure out what you need wastes tokens and produces generic outputs that require multiple revisions.

Fix: Tell it exactly what matters upfront. Be explicit about format, length, tone, and boundaries.

Including Irrelevant Context

Extra information clutters the token sequence and dilutes focus. The model tries to incorporate everything you give it, even if it's not relevant.

Fix: Only include data that directly affects the output. Strip away background information that doesn't change the result.

Expected Results

Your Implementation Timeline

Within 24 Hours

You'll reduce prompt iteration time by 60%. The first time you apply Rules → Role → Goal → Context to a real business task, you'll see the difference immediately.

Within 1 Week

Your team will have created 5-10 company-specific templates for your most common tasks. These become shared resources that new team members can use immediately.

Within 30 Days

You'll have documented prompt standards that function as part of your operational playbook. New hires can follow these templates without extensive training.

Long-Term Impact

Teams report saving 8-12 hours per week on tasks that previously required extensive AI iteration. That's 400-600 hours per year per team member.

Workshop Guarantee

If you don't reduce your prompt iteration time by at least 50% within the first week, we'll refund your enrollment and let you keep all the materials.

Stop Wasting Time on Bad Prompts

This workshop gives you the exact framework that turns AI from a frustrating guessing game into a reliable business tool.

Individual Enrollment

Join an upcoming scheduled workshop

$297

3-hour live workshop via Zoom
Token architecture cheat sheet
15 business prompt templates
Implementation checklist
Session recording for review

Next session dates announced via email

For Teams

Private Group Class

Live training for your team, your schedule

$1,997 up to 10 people

Private 3-hour session for your team
Zoom or in-person (travel may apply)
All templates and materials included
Customize examples to your industry
Flexible scheduling

Schedule a Class

In-person available in Columbus, OH area