🤖 AI / Claude Code

Overview

This track focuses on how large language models (Claude) can augment human thinking and software development. The emphasis is on prompt design, workflow patterns, and reflective evaluation, rather than raw output generation.

Focus Areas

• Prompt Engineering: Designing prompts for reasoning and clarity
• AI Workflows: Integrating Claude into coding and analysis loops
• Experiments: Testing limits, failure modes, and strengths

Contents

• Prompt Patterns – reusable prompt designs
• Workflows – AI-assisted development flows
• Experiments – evaluations and observations
• Reflections – what works, what doesn’t, and why

How I Use AI

I treat AI as a cognitive partner, not a replacement. The goal is to improve reasoning quality, speed up iteration, and surface alternative perspectives while maintaining human control.

How This Connects to My EDA & Career Work

My exploration of AI and Claude Code builds on decades of experience in complex engineering decision-making, verification sign-off, and cross-functional technical leadership.

Rather than treating AI as a replacement for engineering judgment, I focus on using it to augment reasoning, clarify design intent, and accelerate iterative problem solving in technically constrained environments.

This mirrors many real-world EDA scenarios, where ambiguity, competing constraints, and incomplete information must be navigated through structured thinking and disciplined methodology.