Workflow Automation
AI Productivity Frameworks and Product Building
The best AI products are built around workflows, not models. These three articles cover how AI enhances classic productivity frameworks, the principles behind building useful AI products, and a case study of a solo builder who turned a narrow workflow pain point into a six-figure product.
How AI Can Supercharge Your Favorite Productivity Frameworks
TLDR: AI can enhance the Eisenhower matrix, Pomodoro technique, and other proven productivity frameworks rather than replacing them. The article shows specific ways to layer AI assistance onto structures that already work.
Key Insight: Layer AI on top of proven frameworks rather than replacing them.
How to Build a Truly Useful AI Product
TLDR: Four principles for building AI products when the underlying models improve faster than developers can ship. The core argument is that durable value lives in the workflow layer, not the model layer.
Key Insight: Build around workflows, not models — the model changes every 6 months.
She Built an AI Product Manager Bringing in Six Figures
TLDR: Claire Vo built ChatPRD, an AI copilot used by over 10,000 product managers for writing PRDs and defining milestones. It started as a personal tool for a task she did frequently and found tedious.
Key Insight: Biggest AI opportunities are in narrow, high-frequency tasks everyone hates.
What does this mean for your workflow?
Whether you are using AI for personal productivity or building an AI product, the principle is the same: start with a specific, repeated workflow pain point. Layer AI onto existing structures rather than inventing new ones. The most durable AI applications solve narrow problems well, not broad problems vaguely.