Writing
Practical writing on AI automation, LLM systems, Python for business, and workflow engineering. No hype. No fluff. Just what actually works.
A practical breakdown of where AI automation delivers the highest ROI in business operations — and what the real implementation looks like.
A prioritization framework for identifying which business processes to automate with AI — and which ones to leave alone.
Why most AI agent demos fail in production — and the engineering patterns that make agents actually work.
How business analysts can use Python to automate reporting, data workflows, and analysis — without becoming full-time developers.
What LangChain actually is, why it matters, and how it relates to the AI workflows your business could be running — without the jargon.
How to combine Python, the Salesforce API, and LLMs to build a CRM that actually maintains itself.
The specific skills that make a BA with technical chops indispensable on AI implementation projects — and why pure developers often miss the business-critical details.
A no-nonsense checklist for evaluating AI automation consultants — the questions that separate practitioners from theorists.