Claude's AskUserQuestion: "No response after 60s – continued without an answer"

I've been using a SQLite DB to organize actionability so I don't get stuck in the way that GitHub issue tries to work around. Any questions about which route to take that arise during agentic work are logged to a queue along with a set of plausible candidate routes, a probability assigned to each candidate of whether I will choose that option (including "other/none"), a "resource cost" assessment of the route (e.g., token spend, time), a "stability cost" (e.g., high potential to disrupt things or mainly self-contained), and a set of tasks that describe any downstream work that is dependent on the route chosen.

What Claude does next then depends on the results of a tiny optimization program that tries to maximize the expectation value of agent productivity per unit resource (tokens, time, etc.) conditional on how long it will take me to answer the question (e.g., if Claude has a question for me at 1 AM, there probably won't be a response for another 6-7 hours).

"Agent productivity" is of course a bit nebulous, consisting of a somewhat ad-hoc amalgamation of factors, but in general Claude's actionability loosely corresponds to cases like:

- 2-3 possible routes, each with roughly equal probability of being the one I select, low resource costs, minimal risk of instability, few downstream dependencies: implement each route in parallel

- 2-3 possible routes, one with a much higher probability of being chosen, minimal risk of instability, many downstream dependencies: implement just the top route

- Hundreds of possible routes: block until user response

- 1 possible route, high risk of instability, many downstream dependencies: block until user response

Generally speaking, there should be an active queue at all times and agents should be working on anything that's not blocked in the queue with maximal parallelization.

You can always come back later if the design was wrong - you can't undo 7 wasted hours because you didn't notice an agent ask a question at the beginning of the day.

A year ago everyone thought that humans should review every agent command before executing them. Every major company realized that was dumb and now most enterprise agents run in a sandbox without being babysat.

This is just an extension of the same principle. As models get better you can trust them to make the right architectural choice more often. The likelihood of a human missing a prompt or not wanting to babysit the agent is higher than the agent choosing the wrong option.

Most users that just want their agent to do the damn thing.

Users that want to babysit their agents can always turn the setting off. That is not most users.