Hey, well first off, congrats on making the greatest product ever probably.

I absolutely see fable and opus 5.5 misunderstanding intent, but that just seems to be a feature of necessarily underspecifying in a written prompt. Just today, I gave opus 5.5 a simple task to spin up a new environment for work. It read the ticket, which was decently specified and knowing the codebase as well as "Ghasp... reading the code" I had to correct it about 5 times to do it in a way that I would have expected it to. Getting the pipelines right, environment variables, and configs. It was all relatively straight forward imo. Then I had to prompt it to clean up its corrections, because it left a workflow variable in the github action that some intermediate step required but the final solution didn't. I definitely would not have caught that if I didn't read the output. Idk, there seems to be a natural limit as to how much it can infer and I have no idea how to fix it. I did write about it [here](https://javiergonzalez.io/blog/the-assumption-problem/) though.

It happens with Opus when I leave too much up to interpretation and the AI doesn't do what I had envisioned but didn't specify. Like sure, what it did may be a technically correct solution but it's not the correct solution that allows for further development of my idea. I'm not sure how others do their projects but I start small with proof of concepts and develop in layers until the project does what I want. I use plan mode first to layout everything I can think of that I ultimately want and describe features in the best detail I can manage. I work with Claude to figure out the best framework or find whatever existing projects can serve as a starting point. The first milestone is the proof of concept, take the framework/existing project and build something that does the bare minimum of what I need in the way I want it done then build a test suite to make sure it works. Once that's proven out, we start adding more features (both mine and the ones Claude has suggested) and adding/revising tests along the way. For small things, I won't bother with a plan since I generally already know what I want or any ambiguities can be solved in a single response. But for larger things, I try to take a waterfall approach with well defined milestones.

If I knew exactly how I was going to build something, I would have built it myself. But since there's some ambiguity in the portions of the project I'm less familiar with, I rely on the plan to not only help me understand the decisions Claude has made for me but to keep Claude constrained to the decisions I've made. It's very frustrating to waste tokens on having to refactor something because

I don't think me giving the model bad instructions is something a smarter model can solve. I use plan mode constantly (with opus/fable), and at least once a day I'll say something too vague or just dumb and it will sketch out the "wrong" solution in it's plan.

Which is fine because it just put together a plan and didn't spend 10 minutes rearchitecting everything.

I use fable 5.1 (tried opus but it lied to me 3 times in quick succession and ignored me in another)

This is weird to ask because I feel like of course the model isn't omniscient? Isn't the whole point of iterating on a plan to assess impact, risk, know your (the user) variables, user impact, product impact, etc for making a change? I cannot count the times even in the past few months where I start a conversation with my C suite because their desired outcome would have a potential negative impact elsewhere for other products or users.

Is this just not something that comes up at Anthropic?

Hi! Taking this moment to gripe; forgive me...

5.5 and 5.1 have major Rain Man (savant) syndrome. Excellent at many hyper-technical things, absofuckinglutely boneheaded at anything that a human (or an earlier model) would understand - like how to write copy, what a human would expect in a given situation, various types of norms...

it's infuriating because it's a sophies choice - dumber model but better human understanding, or better technical model that you have to explain things to over and over like a toddler.

That also makes it easier to adversarially review the plan (I have Fable write the plan, then review it with Astra and another Fable instance).

This is the process I generally use too. Small plans you can just ask for, and big plans you work through building a plan.md file before you build it.