lowkey just stumbled upon a clip of michael foree breaking down why models hit a wall with huge amounts of data. he explains how
context engineering is basically the workaround to stop the system from losing the plot. it's not just about bigger windows, but more about
how u structure the input. i used to think
prompting was enough but this makes a strong case for learning specific engineering techniques. anyone else trying to master this or is it too much extra work? turns out being a
good engineer is all about managing that bottleneck.
more here:
https://stackoverflow.blog/2026/07/24/no-dumb-questions-ai-bottleneck/