Beyond Prompting: How to Communicate with AI
A Library 2.0 / Learning Revolution Workshop with Reed Hepler
OVERVIEW
The most common misconception about working with artificial intelligence tools is that success depends on mastering the perfect prompt—a precisely engineered set of instructions that will produce ideal results on the first attempt. This workshop challenges that assumption by introducing conversation steering, a more flexible and human-centered approach to AI collaboration that emphasizes ongoing dialogue, iterative refinement, and maintaining control throughout the interaction. Participants will learn that effective AI communication is not about finding magic words but about understanding what they want to accomplish, providing the necessary context and information, and guiding the conversation toward their objectives through multiple exchanges. The session will demonstrate how conversation steering differs fundamentally from prompt engineering, shifting focus from tool-centered techniques to objective-centered practices that keep humans in control of the creative and analytical processes.
Understanding conversation steering as a practice rather than prompt engineering as a technique carries significant implications for how librarians and faculty integrate AI into their professional workflows. When users approach AI interactions as conversations they can steer rather than commands they must perfect, they position themselves to maintain agency, correct course when outputs drift from objectives, and leverage AI capabilities without surrendering professional judgment. This workshop provides concrete frameworks for structuring AI conversations, including the COSTAR method (Context, Objective, Style, Tone, Audience, Response) and the Rhetorical Framework, both of which help users think through their purposes before and during AI collaboration. Participants will learn how to provide sufficient context in initial prompts while remaining prepared to clarify, redirect, and refine through subsequent exchanges. The workshop emphasizes that conversation steering is not merely a technical skill but a literacy practice—one that requires users to understand their own objectives clearly enough to recognize when AI outputs serve those objectives and when they require correction or redirection.
By the conclusion of this workshop, participants will possess practical conversation steering techniques they can apply immediately across all AI interactions in their professional contexts. Attendees will leave with conversation templates that structure initial prompts effectively, strategies for recognizing when AI outputs drift from stated objectives, and methods for redirecting conversations without having to start over. Participants will understand how to balance providing comprehensive information in initial prompts with maintaining flexibility for iterative refinement through ongoing dialogue. Most importantly, participants will recognize that conversation steering is a more sustainable and transferable skill than memorizing prompt formulas—as AI tools evolve, the ability to steer conversations toward human-defined objectives remains constant. This workshop ensures that librarians and faculty can communicate effectively with AI tools while maintaining the professional expertise and critical judgment that define their work.
LEARNING OBJECTIVES: Participants will be able to
- Distinguish between prompt engineering (tool-focused technique seeking perfect initial inputs) and conversation steering (objective-focused practice maintaining human control through ongoing dialogue)
- Apply the COSTAR framework and Rhetorical Framework to structure initial AI prompts that provide necessary context while remaining open to iterative refinement
- Implement conversation steering techniques that redirect AI outputs when they drift from stated objectives, including clarification strategies, constraint addition, and perspective shifts
- Evaluate AI outputs against stated objectives throughout multi-turn conversations, recognizing when to accept, refine, or redirect AI-generated content
The recording and presentation slides will be available to all who register.
DATE: Tuesday, July 21st, 2026, 2:00 - 3:00 pm US - Eastern Time
COST:
- $99/person - includes live attendance and any-time access to the recording and the presentation slides and receiving a participation certificate. To arrange group discounts (see below), to submit a purchase order, or for any registration difficulties or questions, email admin@library20.com.
TO REGISTER:
Use the payment box above to register and pay. You can pay by credit card. You will receive an email within a day with information on how to attend the webinar live and how you can access the permanent webinar recording. If you are paying for someone else to attend, you'll be prompted to send an email to admin@library20.com with the name and email address of the actual attendee.
If you need to be invoiced or pay by check, if you have any trouble registering for a webinar, or if you have any questions, please email admin@library20.com.
NOTE: Please check your spam folder if you don't receive your confirmation email within a day.
SPECIAL GROUP RATES (email admin@library20.com to arrange):
- Multiple individual log-ins and access from the same organization paid together: $99 each for 3+ registrations, $75 each for 5+ registrations. Unlimited and non-expiring access for those log-ins.
- The ability to show the webinar (live or recorded) to a group located in the same physical location or in the same virtual meeting from one log-in: $399.
- Large-scale institutional access for viewing with individual login capability: $599 (hosted either at Learning Revolution or in Niche Academy). Unlimited and non-expiring access for those log-ins.
REED C. HEPLER
Currently, Reed works as a Digital Initiatives Librarian at a college in Idaho and also has his own consulting firm, heplerconsulting.com. His views and projects can be seen on his LinkedIn page or his blog, CollaborAItion, on Substack. Contact him at reed.hepler@gmail.com for more information.
