I like this “scaling” thought experiment technique very much in a variety of problems I face. It often makes things clearer to think in those terms.
However, I think the 100, 1k, 100M approach might have drawbacks to finding the _best_ solution because the final iteration carries forward assumptions from the previous iterations. In CS terms, we may arrive at a local maximum this way, instead of the global max.
In startup terms, generally it's necessary to start with a MVP, from which you build on. The iterative approach is effective at ensuring you make progress toward the problem you're solving, but I agree, the risk is that you might end up carrying forward or "inheriting" problematic assumptions which can impede your ability to effectively solve the larger problem in the long run.
On the flipside, the iterative approach at the very least will help you understand the problem domain thoroughly from multiple perspectives (iterations), even if that means you periodically need to throw out all of your work and start again from scratch.
Awesome to see more and more folks putting their energy into, well, energy.
Have you considered how much good individuals can do by making better choices for the environment versus how much good we can do as a society by implementing things like a carbon tax? Many (most?) of the barriers to dealing with anthropogenic climate change can only be overcome with sufficient political will. It might be better long-term to urge people to vote for the "right" policies than to fall into the trap that individuals can fix the world's climate through lifestyle changes alone.
Thanks for the response. I do think about the issues you're touching on. While it didn't make it into this post because of HN character limitations, part of the “What’s Currently in Place” section on the page I linked to includes:
"Advisors that include one of the most noteworthy climate scientists in the world, the firm that ran data for President Obama's and Bernie Sanders' Presidential campaigns and a marketing strategist who developed a "primal branding" framework that's used by companies like Apple and Nike and YouTube"
And while energy was an obvious starting point for me, the aim would be to make ANYTHING that has an individual / consumer touchpoint and can significantly lessen the effects of climate change one or two or three degrees easier... and then scale it.
However, I think the 100, 1k, 100M approach might have drawbacks to finding the _best_ solution because the final iteration carries forward assumptions from the previous iterations. In CS terms, we may arrive at a local maximum this way, instead of the global max.