AI, Bit by Bit — Byte-Sized Insights for Professionals, Creatives, Builders & Enthusiasts

AightBits

Bits of Prompt Engineering

This track is a good place to start for those wanting to improve their prompting skills through understanding LLM techniques and basic operation under the hood.

Missing Fingers, the Telephone Game, and Lying LLMs

Introduction to In-Context Learning

Introduction to Chain of Thought (CoT) Prompting

Introduction to Tree of Thought (ToT) Prompting

How Iterative Prompting Can Elevate Lightweight LLMs to the Heavyweight Class

Pattern Priming in Prompting: How to Shape LLM Output with Statistical Cues

Parameters & Context: Tool & Material, Not Long-Term & Short-Term Memory

Introduction to Named Entity Recognition (NER)

Understanding Sampler Settings in AI Text Generation

What is Tokenization?

Who is AightBits?

Dave Ziegler

I’m a full-stack AI/LLM practitioner and solutions architect with 30+ years enterprise IT, application development, consulting, and technical communication experience.

While I currently engage in LLM consulting, application development, integration, local deployments, and technical training, my focus is on AI safety, ethics, education, and industry transparency.

Open to opportunities in technical education, system design consultation, practical deployment guidance, model evaluation, red teaming/adversarial prompting, and technical communication.

My passion is bridging the gap between theory and practice by making complex systems comprehensible and actionable.

Founding Member, AI Mental Health Collective

Community Moderator / SME, The Human Line Community