Given the high cost of errors, you need to have a very high level of safety and a very high level of confidence on day one before you deploy your first robot, before you drive your your first autonomous mile.
the research on photographic memory does show that even people who have very strong visual memory will make memory errors. So it's not that you know it's exactly photographic but their visual memory is exceptional.
I think this is kind of leads to another way that Rust really helps with reliability, which is that if you're refactoring, I think Rust is really good at telling you all the places you need to update. I've done this sometimes where I would refactor something. I change the code. I change the return type or whatever it is, and then I just fix the compiler errors and until the compiler stops shouting. And then once I've done that, I've updated every place I need to update.
exceptions are an inherently poor way of handling errors because they make it easier to write bugs which won't be immediately obvious on casual code inspection
With an orchestrated army of agents, there is no bottleneck, no human pain. These tiny little harmless booboos suddenly compound at a rate that's unsustainable. You have removed yourself from the loop, so you don't even know that all the innocent booboos have formed a monster of a codebase. You only feel the pain when it's too late.
An agent has no such learning ability. At least not out of the box. It will continue making the same errors over and over again. Depending on the training data it might also come up with glorious new interpolations of different errors.
So, they they they still make mistakes, but but um um I've I've tested these tools, you know, on on on on um like little tasks that I can do and and sometimes they pick up errors I make, sometimes I pick up errors that they make. It's it's about a tie right now.
This is what leads to slop JS/TS software. Treating errors generically like this is a mistake. It leads to fragile software, poor telemetry/observability/debugging, and as a result worse experiences
Scientists have run studies where they deliberately add errors to papers, send them out to reviewers, and simply count how many errors the reviewers catch. Reviewers are pretty awful at this.
So we we want people, that's the way we break out of fixation, is we notice the anomalies. The way we get stuck in fixation and making fixation errors is we explain away the anomalies, hold on to the original wrong impression until it's far too late.
Over-specifying the design also leads to estimation errors. Counterintuitive as it may seem, the more specific the work is, the harder it can be to estimate.
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