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And it needs deep extensibility. Users and AI must be able to write extensions that access the system’s internals, building custom tools, automation, and domain-specific reasoning engines. This is already happening: AI agents build their own proof strategies on top of the platform. The platform adapts to its users, not the other way around.

That includes cuts to a significant number of science programmes such as the Mars Sample Return that aims to return samples from the planet's surface to Earth.

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Entrepreneurs succeed when they are able to add value to the lives of others. People and organizations are willing to pay them for their products or services because those products and services improve their lives in some way.

My obligation as a professional coder is to do what works best, especially for open source code that other people will use. Agents are another tool in that toolbox with their own pros and cons. If you’ve had poor experiences with agents before last November, I strongly urge you to give modern agents another shot, especially with an AGENTS.md tailored to your specific coding domain and nuances (again here are my Python and Rust files, in conveient copy/paste format).

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