I went looking for sustainable products and found a data problem
How a 2024 search for trustworthy eco-friendly products became two years of learning about EPDs, LCA, carbon data and the concept built around the gap.
Journal
Thoughts and working notes from October 2024 onward. Where an original date was not recorded, the entry shows the month only.
How a 2024 search for trustworthy eco-friendly products became two years of learning about EPDs, LCA, carbon data and the concept built around the gap.
A market reading of digital EPD infrastructure: why moving declarations from PDFs to structured data matters, and where product opportunities sit.
A working playbook for building carbon thinking into everyday product management: daily habits, the first month, and growing into climate leadership.
Most carbon tools are built for enterprises, but small and medium businesses carry much of the supply chain. Why that gap matters, and what tools could do.
A field guide to measuring and reducing the footprint of software, websites and AI: open standards, calculators, data sources and where each fits.
LCAs are less like a chemistry degree and more like learning to cook. Think of one as a health check-up for a product, and start small.
Running Apple Watch field recordings through Google DeepMind's Perch model to see whether consumer devices can feed research-grade biodiversity data.
A reading of national and corporate climate targets against 1.5°C, from UNEP, UNFCCC, IEA and SBTi data, gathered as the base for an explorer concept.
Product management is evolving and so is business. A practical guide to life cycle assessment for leaders who will never run one themselves.
If we can track latency and cost per request, we can track carbon per request. A reading list and a case for treating emissions as a first-class metric.
Co-leading a first life cycle assessment workshop in Seattle for 60+ consultants and sustainable design professionals, and what the room taught me.
Sustainability standards are maturing and becoming infrastructure. A reading across regions, and what it means for product and operations teams.
ESG reports describe a company. LCAs describe a product. As reporting gets more product-specific, the two are converging, and that is where the data gap shows.
An AI agent looks like one chat box. Underneath sit a dozen layers of infrastructure, each with its own footprint. How LCA thinking helps map them.
Token optimization is everywhere. Carbon optimization is not. Why data center efficiency has plateaued while AI demand keeps climbing.
Notes on the SCI specification, what it asks product teams to measure, and the product strategies that lower the footprint of AI features.