Theory of Constraints Introduction

[Elliot]

@Dface

@Elliot

Doing two hours of work somewhere else to save an hour at the constraint can be efficient.

That’s interesting. Even tho we found the constraint that doesn’t mean it’s all on it. Like, a part of the system can give the constraint a lot of work to do. If the constraint works at a certain rate and has a lot to do then it has a big burden I think. I think another way is to not give the constraint enough to do maybe?? I don’t that’s right. Maybe the constraint is only working a few hours a day but can work at other hours too.

say the constraint is AI tokens. then it’d be efficient to carefully spend a lot of time figuring out the best prompts to give the AI. your time has excess capacity.

if AI tokens are cheap and your time is the constraint, then instead you should give the AI prompts a lot more casually, experimentally and repetitively (try multiple similar prompts) and let it do more work instead of you.

if the constraint is a big oven that can only 3 8-hour batches per day, then you could do quality control before the oven so fewer broken parts go through the oven, so the oven is used more efficiently.

@Dface

@Elliot

Notably, don’t do this earlier. It’s usually more efficient to make other changes first.

I wonder why it’s more efficient to make other changes first. When I play Marvel Rivals, I focus on increasing the capacity to find my target or understand their strafing pattern first. I think I always focus on increasing the capacity first. Maybe it’ll be easier for me to make things more efficient for the constraint. I gotta find the constraint reliably first tho.

the idea is the constraint is hard/expensive to improve/increase or else it wouldn’t be the constraint (you would have already improved it). this doesn’t apply in very early stages of things before the system is stabilized and the constraint stops changing much.