Anthropic engineer just dropped a brutal lesson:
"Biggest mistake in AI rn? Building graphs and loops without a self-improving eval agent. We did this at Anthropic. Cost us 2 years."
This is the kind of alpha that separates real builders from script kiddies. If you're shipping AI products without proper eval loops, you're basically flying blind.
The meta lesson: even top-tier teams at $ANTH make architectural mistakes that set them back years. Your competitive edge isn't just speed—it's building the right feedback systems from day one.
For AI crypto projects, this hits different. Most teams are rushing to launch without proper evaluation frameworks. That's how you get rugged by your own tech stack.
"Biggest mistake in AI rn? Building graphs and loops without a self-improving eval agent. We did this at Anthropic. Cost us 2 years."
This is the kind of alpha that separates real builders from script kiddies. If you're shipping AI products without proper eval loops, you're basically flying blind.
The meta lesson: even top-tier teams at $ANTH make architectural mistakes that set them back years. Your competitive edge isn't just speed—it's building the right feedback systems from day one.
For AI crypto projects, this hits different. Most teams are rushing to launch without proper evaluation frameworks. That's how you get rugged by your own tech stack.