https://open.substack.com/pub/sluongng/p/stages-of-coding-ag...
I think we need much different toolings to go beyond 1 human - 10 agents ratio. And much much different tooling to achieve a higher ratio than that
Imagine a superhuman agent who does not need to run in endless loops. It could generate 100k line code-base in a few minutes or solve smaller features in seconds.
In a way, the inefficiency is what leads people to parallelism. There is only room for it because the agents are slow, perhaps the more inefficient and slower the individual agents are, the more parallel we can be.
All of this is not a direct signal to a productivity boost. I think at higher volumes, you will need to start to account for the "yield" rate of the token volumes above: what are the volumes of tokens that get to the final production deployment? At which stage is it a constraint on the yield? Is it the models, or is it the harness, or something else (i.e. Code Review, CI/CD, Security Scans etc...)? And then it becomes an optimization problem to reduce the Cost of Goods Sold while improving/maintaining Revenues. The "productivity" will then be dissolved into multiple separate but more tangible metrics.
So we are just now getting agents which can reliably loop themselves for medium size tasks. This generation opens a new door towards agent-managing-agents chain of thoughts data. I think we would only get multi-agents with high reliability sometimes by the mid to end of 2026, assuming no major geopolitical disruption.