What projects? You are starting from a completely different baseline than the average hypothetical UBI recipient.
I think UBI advocates may have a point once you're 2-3 generations into some sort of UBI system. But bootstrapping that system is not possible, most people will revert to do nothing of value to society, no projects, nothing.
According to google, "approximately 57% to 67% of American adults are living paycheck to paycheck."
This doesn't mean they are poor. As their income goes up, so does their spending.
Also according to google, "Approximately 60% to 80% of professional athletes face severe financial distress or go broke within a few years of retirement, particularly in the NFL and NBA. Data suggests 78% of NFL players experience financial hardship within two years of retirement, while about 60% of NBA players are broke within five years."
and:
"though often debated, statistic suggests that up to 70% of lottery winners go broke or face financial distress within three to five years, more conservative estimates indicate about one-third (roughly 33%) declare bankruptcy."
Personally, I think that high schools should have a required course in finance and accounting.
I do something very similar. I have an "outside expert" script I tell my agent to use as the reviewer. It only bothers me when neither it OR the expert can figure out what the heck it is I actually wanted.
In my case I have Gemini CLI, so I tell Gemini to use the little python script called gatekeeper.py to validate it's plan before each phase with Qwen, Kimi, or (if nothing else is getting good results) ChatGPT 5.2 Thinking. Qwen & Kimi are via fireworks.ai so it's much cheaper than ChatGPT. The agent is not allowed to start work until one of the "experts" approves it via gatekeeper. Similarly it can't mark a phase as complete until the gatekeeper approves the code as bug free and up to standards and passes all unit tests & linting.
Lately Kimi is good enough, but when it's really stuck it will sometimes bother ChatGPT. Seldom does it get all the way to the bottom of the pile and need my input. Usually it's when my instructions turned out to be vague.
I also have it use those larger thinking models for "expert consultation" when it's spent more than 100 turns on any problem and hasn't made progress by it's own estimation.
Don't worry, when the Millennia's and Zoomers are running the world, Alpha and Beta will be writing the exact same cruft as above, and the cycle will continue forever.
* Workflows are only registered once pushed to main, impossible to test the first runs in a branch.
* MS/GH don't care much about GHES as they do github.com, I think they'd like to see it just die. Massive lack of feature parity.
* Labels: If any of your workflows trigger from a label, they ALL DO. You can't target labels only to certain workflows, they all run and then cancel, polluting your checks.
* Deployments: What is a deployment even doing? There is no management to deploy.
* Statefulness: No native way to store state between runs in the same workflow or PR, you would think you could save some sort of state somewhere but you have to manage it all yourself with manifests or something else.
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