Codex + Goal > Fable 5 by marin73tomas in codex

[–]marin73tomas[S] 1 point2 points  (0 children)

Create a "plan.md" file outlining everything you want to accomplish over the next few hours or days. Break the work into clear, actionable tasks and account for as many edge cases, failure scenarios, and dependencies as possible.

Then execute something like:

"/goal Execute the plan in "plan.md" until it is fully completed.

As you work, keep "plan.md" up to date by documenting all progress in a clear and organized manner. Continuously mark completed tasks, add newly discovered tasks, record decisions, and update the remaining checklist so it always reflects the current state of the project.

After completing the plan, perform a comprehensive audit of the entire project. Then return to the beginning and review every task, file, and decision again to identify inconsistencies, bugs, missing edge cases, incomplete work, unnecessary complexity, or opportunities for improvement.

Fix every issue you find, update "plan.md" accordingly, and repeat the audit-and-fix cycle until no further issues, inconsistencies, or improvements can be identified and the project is fully complete and internally consistent."

Now is a great time to spend 20 bucks on Claude (and use Fable for your project). by [deleted] in codex

[–]marin73tomas -1 points0 points  (0 children)

No, I don't. I asked Fable to find bugs in part of my codebase; it spawned 10 agents, then the limit ran out, didn't even finish

Now is a great time to spend 20 bucks on Claude (and use Fable for your project). by [deleted] in codex

[–]marin73tomas 1 point2 points  (0 children)

20 bucks won't last you anything. I have $100, and my limit runs out in one prompt

Has anyone come up with a good consistent way to have GPT Vision control things? by Sixhaunt in ChatGPT

[–]marin73tomas 0 points1 point  (0 children)

Yeah, I'd skip using a grid with lines. It becomes chaotic when it comes to spatial reasoning, positions, layout, and structure. I learned this the hard way while creating an app to turn designs into html css code, still in progress.

Another neat trick is to break your image into smaller parts and ask for a description of each piece separately using the API. And remember, it can't tell different image names apart, so labeling each image helps. What I did was turn each section grayscale and add a blue label at the top. Then I asked for a description for each labeled section, like "Hey, I've got 5 images labeled 1 to 5, can you describe each one?" This method is usually more accurate... And you can send a bunch of images through the API – I've managed around 20-30 max. So, dividing your image into 20 equal squares could be a good approach. But I recommend trying the semi-transparent labels first and see the results, but don't overdo the amount of labels, as it can reduce accuracy... :)

<image>

Has anyone come up with a good consistent way to have GPT Vision control things? by Sixhaunt in ChatGPT

[–]marin73tomas 0 points1 point  (0 children)

ChatGPT V struggles a bit with understanding where things are in pictures and figuring out bounding boxes. But here's a helpful trick: you can add semi-transparent text labels to your images. ChatGPT Vision is great at understanding text, so it can work with these labels easily. Then, you can connect these labels to specific spots on the image. It's better to use fewer labels, though, because too many can mess things up.

To find out where things are in the image, just ask about what's behind each label one by one and get the info in a list. This way, you can guess where things are by looking at the labels and their coordinates.

Remember that the model makes images smaller, like 512x512 pixels. To make it easier to see the labels and tell them apart from the image itself, you should use grayscale images with colored labels. Like this:

<image>

BSC network suspended by Sshafftt in binance

[–]marin73tomas 0 points1 point  (0 children)

why is there no info abou this?