Prompt Engineering Accelerator for AI

Modern AI systems can be astonishingly powerful—but only when guided with well-crafted prompts. This 90-minute session provides a fast-paced, practical deep dive into the core elements of effective prompting and the techniques that consistently produce better, more reliable outputs from LLMs. Attendees will learn the building blocks of strong prompts, explore how to design and iterate prompts for specific goals, and understand when to apply different prompt types including role-based, structured, constrained, few-shot, and chain-of-thought patterns. The session concludes with practical frameworks for evaluating prompt quality, measuring effectiveness, and building repeatable prompting workflows. Ideal for developers, analysts, and technical leaders who want to accelerate their AI effectiveness immediately.

Large language models can solve a broad range of problems, but the difference between mediocre and exceptional results often comes down to how prompts are designed. This session equips attendees with a practical, accelerative approach to prompt engineering—focusing on patterns, structure, and evaluation rather than guesswork.

We begin by breaking down the essential elements of a prompt, including task definition, context, constraints, persona/role setup, and output formatting. Attendees learn how these components shape the model’s reasoning process and influence the reliability and clarity of generated responses.

The session then explores core prompt types used in real-world AI workflows: role-based prompting to guide behavior, structured prompts for predictable formatting, constrained prompts for compliance and safety, few-shot prompts to teach patterns, and chain-of-thought approaches for deeper reasoning. For each type, we discuss practical examples, strengths, limitations, and the scenarios where each method excels.

To ensure prompts are not only functional but optimized, we introduce a measurement framework covering clarity, consistency, controllability, correctness, and cost. Attendees learn how to evaluate prompt performance, iterate intentionally, detect failure modes, and quantify improvement using simple metrics and qualitative benchmarks.

By the end, participants leave with a toolkit of immediately applicable techniques and a systematic mental model for designing, refining, and validating AI prompts—empowering them to work more effectively with models across development, data analysis, automation, writing, and problem-solving tasks.

1. Introduction (5 minutes)
   •Why prompting still matters in 2026
   •The shift from “magic words” to systems-thinking in prompt design
   •Goals of the session

2. Foundations of Effective Prompting (10 minutes)
   •The core elements of a prompt
   •Task
   •Context
   •Constraints
   •Role/persona
   •Output format
   •How LLMs interpret instructions

3. Designing Prompts for High-Quality Results (15 minutes)
   •Framing the problem correctly
   •Precision vs. flexibility
   •Reducing ambiguity
   •Encoding domain knowledge
   •Strategies for decomposing complex tasks

4. Prompt Types and Techniques (30 minutes)

Role-Based Prompts
•When to use personas
•How roles steer behavior and tone

Structured Prompts
•Templates, sections, and predictable formats
•Ideal for analysis, coding, automation, compliance

Constrained Prompts
•Using rules, boundaries, and limitations
•Preventing drift and controlling style

Few-Shot & Pattern-Teaching Prompts
•Teaching the model via examples
•Balancing length, clarity, and guidance

Chain of Thought (CoT)
•Getting transparent reasoning
•When CoT helps vs. when it harms
•Alternatives: stepwise prompting, self-critique

1. Selecting the Right Prompt Technique (10 minutes)
   •A decision tree / mapping prompt type to problem type
   •Combining techniques in layered prompts

2. Measuring Prompt Success and Effectiveness (15 minutes)
   •Evaluation criteria: clarity, consistency, correctness, controllability, cost
   •Using test cases and benchmarks
   •Iteration loops
   •Identifying failure modes

3. Closing Takeaways + Q&A (5 minutes)
   •A reusable checklist for prompt engineering
   •How to continue improving prompts in real workstreams
   •Audience questions

About Brent Laster

Hi, I'm Brent Laster - a global trainer and book author, experienced corporate technology developer and leader, and founder and president of Tech Skills Transformations LLC. I've been working with and presenting at NFJS events for many years now and it is always exciting and interesting.

Through my decades in programming and management,I've always tried to make time to learn and develop both technical and leadership skills and share them with others Regardless of the topic or technology, my belief is that there is no substitute for the excitement and sense of potential that come from providing others with the knowledge they need to help them accomplish their goals.

In my spare time, I hang out with my wife Anne-Marie, 4 children and 2 small dogs in Cary, North Carolina where I design and conduct trainings and write books. You can find me on LinkedIn (linkedin.com/in/brentlaster), Twitter (@brentclaster) or through my company's website at www.getskillsnow.com.

More About Brent »