Prompt Engineering Accelerator for AI

In this intensive 3-hour hands-on workshop, you'll learn to master the art and science of prompt engineering. Learn systematic frameworks for constructing effective prompts, from foundational elements to cutting-edge techniques including multi-expert prompting, probability-based optimization, and incentive framing. Through five progressive labs using Ollama and llama3.2:3b in GitHub Codespaces, you'll build production-ready templates and see quality improvements in real-time. Leave with immediately applicable techniques, reusable prompt patterns, and a decision framework for selecting the right approach for any AI task.

Modern AI systems deliver many capabilities, but their effectiveness depends entirely on how well they're prompted. This intensive workshop transforms prompt engineering from trial-and-error guesswork into a systematic, measurable discipline. You'll learn proven frameworks for constructing effective prompts and learn cutting-edge optimization techniques that deliver quality improvements in real-world applications.
Through five hands-on labs in GitHub Codespaces, you'll work with Ollama hosting llama3.2:3b to implement each technique, measure its impact, and build reusable templates. Every concept is immediately validated with code you can deploy tomorrow.

What You'll Master
The workshop progresses through five core competency areas, each reinforced with a practical lab:
Foundations of Effective Prompting begins with the six essential elements every prompt needs: task definition, context, constraints, role assignment, output format, and examples. You'll systematically transform a poorly-constructed prompt into an optimized version, measuring quality improvements at each step. This foundation eliminates the guesswork and establishes a repeatable framework for all future prompt engineering work.

Pattern-Based Techniques introduces few-shot learning and Chain of Thought (CoT) reasoning. Few-shot prompting teaches models through examples rather than explanations, dramatically improving consistency on classification and transformation tasks. Chain of Thought makes reasoning transparent, improving accuracy on complex problems by 20-40% while enabling you to verify the model's logic. You'll build a classification system and compare zero-shot, few-shot, and CoT approaches with measurable accuracy metrics.

Advanced Structural Techniques combines role-based prompting, structured outputs, and constrained generation into enterprise-ready patterns. You'll create an API documentation generator that uses expert personas, enforces strict formatting requirements, outputs reliable JSON, and maintains 90%+ consistency across diverse inputs. This lab produces production templates with automated validation—patterns you can immediately deploy in your organization.

Cutting-Edge Methods explores two powerful techniques gaining traction in 2025-2026. Multi-expert prompting simulates a council of experts (technical, business, security) analyzing complex decisions from multiple perspectives, catching blind spots that single-perspective prompts miss. Reverse prompting flips the traditional interaction: instead of you trying to perfectly specify requirements, the AI asks clarifying questions to discover what you really need. You'll measure 40-60% improvements in decision quality and 80-90% gains in requirement clarity.

Probabilistic and Incentive-Based Optimization introduces the latest research-backed techniques for extracting maximum quality from language models. Stanford's breakthrough probability-based prompting—requesting multiple responses with confidence scores—improves reliability by 30-50% on ambiguous tasks. Incentive framing (yes, “This is critical” and “Take your time” actually work) increases thoroughness by 20-40%. Combined, these techniques deliver 50-70% quality improvements on high-stakes decisions.

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.

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