Three articles that changed how I work

I used to read a lot of AI and EdTech news and not do much with it. Interesting articles would pile up in tabs, I’d skim them, feel informed, and move on. None of it connected to anything I was actively working on.

So I built a lightweight journal system. Each entry captures an article or development, tags it to whichever project it’s relevant to, and includes a short statement explaining why it matters to that project specifically. A Chrome extension handles quick capture, Claude Code handles entry creation. It’s been running for a few months across four active projects.

Three of those entries actually shaped decisions. An OECD report on the AI skills gap validated the target population for our AI Entrepreneurship Portfolio. If the gap is widening, the need for accessible AI-enhanced tools is growing with it. LinkedIn data on rising entrepreneurship in historically underserved populations was direct validation for our product’s target users. And a Harvard/Perplexity study showing that 57% of real agent usage is cognitive and learning work, not task automation, validated the AI coaching model we were building. If people naturally gravitate to agents for learning, an intentionally designed coaching agent has stronger product-market fit than a task-completion tool.

Any of those articles could have been interesting reading and nothing more. The difference is the connection statement. Forcing myself to write down why this matters to a specific project turns passive consumption into something I can actually use when a decision point arrives. I share relevant findings with my team too, which has become a regular way I contribute beyond my direct project scope.

The system only works if I do it consistently. A weekly cadence is enough. The goal isn’t comprehensive coverage, it’s staying oriented so that when someone asks “why this direction?” I’ve already been thinking about the landscape.