From Productivity to Agency

Over the past few weeks, I’ve been working on Neural Field, a personal AI news and intelligence site tracking AI, gaming, sports, and world-model trends.

From cloud experiment to owned workflow

It started as a hobby experiment built with Perplexity Computer, a way to test whether one person could create a lightweight intelligence center across sources, languages, and domains.

Recently, I moved the workflow to a more self-sustaining, entirely free system powered by GitHub Actions, using Claude Cowork to help rebuild and automate the process codelessly.

A few updates:

• Morning brief with human-voice TTS
• Improved filtering and labeling for relevance
• Cleaner refresh logic
• A workflow I can inspect, control, and keep improving

The bigger reflection: agentic AI is moving us from productivity to agency.

Why agency matters

Productivity is about doing more with less time. Agency is about having more control over what we see, how we learn, what we build, and how we make decisions.

That matters because access to intelligence has never been evenly distributed. Some people have research teams, global networks, language advantages, or more time. Most people don’t.

But agentic AI can help close that gap.

It can help individuals and small teams gather signals, connect patterns, translate context, and turn scattered information into usable insight. That’s why I distilled the Neural Field workflow into an Agent Skill (Claude Cowork Skill) that others can reuse, adapt, or repurpose.

What becomes possible next

To me, the next wave of AI is not just about automation. It is about giving more people the ability to build their own intelligence systems around their curiosity, work, and purpose. So they will be able to see the unseen, solve the unsolved, and connect the previously disconnected.