The Bitter Lesson: Rethinking How We Build AI Systems:

Recently, I was tending to my small garden when it hit me - a perfect analogy for this principle. My plants don’t need detailed instructions to grow. Given the basics (water, sunlight, and nutrients), they figure out the rest on their own. This is exactly how effective AI systems work.

When we over-engineer AI solutions, we’re essentially trying to micromanage that plant, telling it exactly how to grow each leaf. Not only is this inefficient, but it often leads to brittle systems that can’t adapt to new situations.

This is beautifully articulating something I have been wrestling with for a while. What’s the best optimisation strategy for refining agentic experiences? To what extent can throwing compute at a problem solve for complexity?

Ankit is really onto something here, wonderful framing.