Life in the moment is a lot easier if you don't second-guess yourself. I think this is why many people (and probably ~all people, if tired) crave simplistic solutions.
I like to make a subagent take the "devil's advocate" take on a subject. It usually does all the arguing for me as to why the main agent has it wrong. Commonly results in better decisions that I'd have made alone.
Asking the agent to interview on why I disagree helps too but is more effort.
What we're doing at Cloudflare (including some of what the author works on) samples adaptively. Each log batch is bucketed based on a few fields, and in each bucket if there's lots of logs in each bucket we only keep the sqrt or log of the number of input logs. It works really well... but part of why it works well is we always have blistering rates of logs, so can cope with spikes in event rates without the sampling system itself getting overwhelmed.
> if they can't explain what they want to do clearly and why, it probably shouldn't be done. Quality goes up by slowing down.
I kind of agree. Without what you describe, teams often get lost. But I’ve also seen that approach keep teams stuck in comfortable local minima. Sometimes you’ve got to take risks.
I agree, it's an interesting view. I found it quite positive about the culture in that part of Splunk. The writer parachuted in, threw their weight around, bruised a bunch of people, but lost out to another manager who openly acknowledged the contributions of their people.
The effect is really cool. I like the idea of visualizing data flowing through work systems like this. I think I'll go for 3D-printed or laser-cut panels instead though - would work out cheaper. Thanks :)
Ordering satellite imagery and counting cars is just a weekend project. The last time I looked at ordering imagery, the main obstacle was the minimum order size, so it'd actually scale better for monitoring every store car park than for looking at a single car park.
I like to make a subagent take the "devil's advocate" take on a subject. It usually does all the arguing for me as to why the main agent has it wrong. Commonly results in better decisions that I'd have made alone.
Asking the agent to interview on why I disagree helps too but is more effort.