Interesting. When it comes to how easy it is to check an agent's work, I think there is also another layer to be verified - the intent. We have a lot of tooling for static analysis and automated deterministic tests of the code, but drift in intent or vision is hard to detect.
After leaving agents unsupervised for longer periods of time, the biggest questions tend to be "how did it arrive at this conclusion?" and "did we drift from the initial vision?" and "were there obstacles that changed the course of the workflow?". Typically these questions are hard to answer as you only review the final state of the workflow.
I recently built an issue tracker that does offer time-traveling as a core feature. Somewhat unexpectedly this turned out to provide a much sought for overview allowing for a better workflow audit. Detailed some of these experiences here:
https://dev.to/ljtn/vision-drift-addressing-the-next-problem...
Would be interested to hear your thoughts. I guess vision drift would classify as something that is hard to reverse, because you often don't realize it has happened until much later.
There are so many other factors. Will people be pissed if they expected your output and got AI slop instead? Will you lose context on something that you really need to understand?
Interesting. When it comes to how easy it is to check an agent's work, I think there is also another layer to be verified - the intent. We have a lot of tooling for static analysis and automated deterministic tests of the code, but drift in intent or vision is hard to detect.
After leaving agents unsupervised for longer periods of time, the biggest questions tend to be "how did it arrive at this conclusion?" and "did we drift from the initial vision?" and "were there obstacles that changed the course of the workflow?". Typically these questions are hard to answer as you only review the final state of the workflow.
I recently built an issue tracker that does offer time-traveling as a core feature. Somewhat unexpectedly this turned out to provide a much sought for overview allowing for a better workflow audit. Detailed some of these experiences here: https://dev.to/ljtn/vision-drift-addressing-the-next-problem...
Would be interested to hear your thoughts. I guess vision drift would classify as something that is hard to reverse, because you often don't realize it has happened until much later.
There are so many other factors. Will people be pissed if they expected your output and got AI slop instead? Will you lose context on something that you really need to understand?