Make carbon a product metric
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.
By Writam Bugga · · 2 min read
Product teams already live by metrics: latency, uptime, cost per request, conversion. Carbon can sit in the same dashboard. It is measurable, it can be budgeted, and it responds to product decisions.
What it looks like in practice
- A carbon-per-request number next to cost-per-request, using the SCI specification.
- A carbon budget in the spec, next to the performance budget.
- Energy impact in acceptance criteria for AI features.
- Model choice informed by comparable ratings such as the Hugging Face AI Energy Score.
The reading list behind the post
- A lifecycle emissions study of AI hardware that includes manufacturing, not only electricity.
- Mistral's contribution to a global environmental standard for AI, one of the first model-level LCAs published by a lab.
- The Wall Street Journal on new chips designed for AI's energy problem.
- A carbon ROI perspective on scaling AI with sustainable energy systems.
- Read AI's guidance for drafting an AI policy, a reminder that governance and footprint belong in the same policy.
Why it matters for hiring
A metric only changes behaviour if someone owns it. In most climate tech companies, that owner is a product manager who can talk to engineers about PUE, to finance about cost and to compliance about reporting. That is the job I keep describing in the Climate PM practice.
First shared on LinkedIn. See the original post on LinkedIn
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