this is where REA × Kimi K3 starts to get dangerous.
reverse engineering usually forces one model to keep too much of the app in context at once.
REA changes the shape of the problem first.
so the workflow becomes less like “read this codebase” and more like distributed forensics:
map the surface → assign narrow investigations → trace relationships → compare findings → reconstruct the architecture
the important part is that no single agent needs to understand the whole app.
the swarm builds that understanding collectively.
that’s what makes REA × K3 interesting to me: reverse engineering stops being limited by how much code one model can hold in its head.
full course in the article below ↓
this is pure f*cking treasure
REA creator just dropped 20 GitHub repos to build a f*cking reverse engineering studio:
01 / analysis core
02 / mobile & apps
03 / binary & low-level
04 / network & runtime
05 / rebuild & verify
the loop: binary -> REA -> SPEC.md -> rebuild -> oracle -> retry
study the original. ship your own.
this is f*cking insane...
Jensen Huang: Nvidia's Future, Physical AI, Rise of the Agent, Inference Explosion, AI PR Crisis.
Token/employee allocation discussion starts around the 20:48 mark.
He argues that a $500K engineer should consume at least $250K in tokens annually (otherwise he’d be “deeply alarmed” or “go ape”), compares it to a chip designer refusing CAD tools, and notes NVIDIA is trying to spend heavily on tokens for its engineering team.
https://t.co/nifUqVcOQj