• (Placeholder) Systems thinking & feedback — book I reach for when I need to zoom out and think in loops, not lines.
• (Placeholder) Industrial data & controls — something that bridges control systems, sensors, and data engineering.

• Simple notebooks, good plotting tools, and a clear data log are still the most underrated “ML tools” I know.
• I’ll add specific libraries and platforms here once I’ve written about how I use them in real projects.

I’ll eventually collect talks, papers, and essays here — with a short note on why each link matters, not just a long list.

Podcasts I replay or send to teammates when a topic comes up — long-form interviews, industry shows, and the occasional story-driven series. I’ll add concrete titles and episodes as I keep a running list.

Open-source repos I’ve learned from or contributed to — reference implementations, small utilities, and bigger systems worth reading even if you don’t clone them. Nothing listed yet; this tab is a placeholder until I curate it properly.

Papers and technical reports I return to for foundations (time series, physics-informed models, reliability). I’ll add each with a one-line “why it stuck” note instead of dumping arXiv links without context.