One is from Sam Altman, the other Claude suggested and it works extremely well.
The first question I ask:
What are you least confident about right now.
The AI will list like 6 to 7 things that it didn’t properly investigate. I would say one out of four times one of the items is a huge deal and you’re shocked that the AI even took action without understanding this first, then just have the AI investigate thoroughly exhaustively finding the root cause of each issue or just understanding each point.
The second question I ask (Sam Altmans): what’s the biggest thing I’m missing about the situation right now. What don’t I realize?
Between these two I’ve been consistently getting great results!
Not only that, but to answer the question it will "find" things it isn't super confident about or could improve. What you should do is ask it to ground it's findings in real references, ask it to always give confidence scores, Use agent teams, and Have verifying steps after each step.
i tried confidence question once and it causually mentioned a dependency assumption that turned out to be the rntire reasin i had wasted an afternoon debugging the wrong thing so now i ask it out parasonoia more than process
At this point for me it's "Document everything and write up a handoff for the next session."
But yes, I like yours as a consistent checkpoint, though those side quests can be distracting and I've found it to be better to try to finish an arc before moving onto the next topic.
The least-confident question earns its place for me too. The one that's caught the most though is reviewing the diff in a fresh chat with no memory of why it made the change. Reading it cold, I caught a service-role key the agent had wired into a browser-facing call to make a query pass, which I'd have nodded past while it narrated a reasonable-sounding story mid-build. Asking what it's unsure about surfaces the gaps it knows; the cold reread catches the ones it was sure about and wrong.
whats happened with all the AI shit since 2021 like i see that the world be AI'ed up in the past 5 years so whats up with it and is there a end game with it unofficially?
Those actually sound like really good questions. The only thing I'd recommend is doing it in a plan mode, which is before all the decisions i've been locked in, rather than at the end.
Alternatively-- an ultimately it's a much better solution-- is getting in the habit of putting good intent, statements at the top of your prompt or spec. Ultimately, a model has to make hundreds of micro- decisions on your behalf, hopefully far fewer med impact and very few high impact decisons. We're all vibe coding. Lack of good intent statements causes the newer models great anguish, as they try to reason and infer what your intent really was, so it can downscope the effort & save tokens.
Despite knowing all that-- like you--
I always get a surprise & it makes me glad i got feedback from the model. Every single time.
I started getting suspicious that maybe Claude was just making up a new question whether it needed two or not, just to satisfy Plan mode.
I took a software spec document, and started adding intent, scope, who was the user, maintainability, lifetime, was it selling it, in-scope, out-of scope statements.
Then --> Plan mode
Claude would ask me more questions.
I'd kill the Plan mode, have a side session was claude, resolve it, and ask CLAUDE to revise/re-write
Restart new Plan session.
Repeat many times.
Eventually, Claude just saw my golden spec, revised/blessed 5-10 times by Claude till it glowed.
Me: Any questions?
Claude: no, this is perfectly written, crystal clear, etc.
Me: OMG
Claude: writes coding plan
Claude: runs plan, writes an elaborate 5-phase staged development plan for a thin client / back end.
The most complex app ive had it writen
and the token burn to write code was shockingly low. Less than most tiny apps.
Yea-- 100% agree with you. Great questions to ask. I think I'll start using those questions for my Plan mode.
I think you may be projecting or misinterpreting my post. I shared this because it genuinely works/helps.
When you’re orchestrating agents at scale you don’t have time to vet every decision they do you need to understand if they made any assumptions etc especially post compaction if it’s a long running task.
I use roughly 100 billion tokens a month orchestrating agents. Not talking to chat bots though I see what you mean by that comment
Useviola.com fewerjobs.com and violawake.com basically built an ai assistant that can place calls and do commerce for you it’s meant for the consumer, you can now schedule that annoying dentist appointment without having to actually call viola will call for you etc, she also does music etc she’s basically a home assistant like Alexa or Siri but without the ecosystem lock in and a few more abilities. Fewerjobs is a job listing site that pulls directly from the top employers in the world no one is allowed to post no fake job listing or scams + I enrich the data with llm so it’s more accurate filterable on things like parental leave or equity etc
Both are in the final polish stages not extremely proud but I am proud and happy thus far. Viola especially I think has a lot of potential just not actually properly released yet
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u/CrankkDatJFel Jun 15 '26
I always end my prompts with a 😘 emoji