Finding these optimization opportunities can itself be a significant undertaking. It requires end-to-end understanding of the spec to identify which behaviors are observable and which can safely be elided. Even then, whether a given optimization is actually spec-compliant is often unclear. Implementers must make judgment calls about which semantics they can relax without breaking compatibility. This puts enormous pressure on runtime teams to become spec experts just to achieve acceptable performance.
We know where it broke, but we can’t see why. Was it a race condition? Did a database read return stale data that has since been overwritten? To find the cause, we have to mentally reconstruct the state of the world as it existed milliseconds before the crash. Welcome to debugging hell.
The main lesson I learnt from working on these projects is that agents work best when you have approximate knowledge of many things with enough domain expertise to know what should and should not work. Opus 4.5 is good enough to let me finally do side projects where I know precisely what I want but not necessarily how to implement it. These specific projects aren’t the Next Big Thing™ that justifies the existence of an industry taking billions of dollars in venture capital, but they make my life better and since they are open-sourced, hopefully they make someone else’s life better. However, I still wanted to push agents to do more impactful things in an area that might be more worth it.。关于这个话题，爱思助手下载最新版本提供了深入分析
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"These new figures show the total cost to taxpayers will be far higher than previously feared.