基于此，一场硬刚跨国巨头、争夺百亿市场的升维战，已悄然打响。
Дарья Устьянцева (редактор отдела «Мир»)
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The agent was able to create a very detailed documentation about the ZX Spectrum internals. I provided a few .z80 images of games, so that it could test the emulator in a real setup with real software. Again, I removed the session and started fresh. The agent started working and ended 10 minutes later, following a process that really fascinates me, and that probably you know very well: the fact is, you see the agent working using a number of diverse skills. It is expert in everything programming related, so as it was implementing the emulator, it could immediately write a detailed instrumentation code to “look” at what the Z80 was doing step by step, and how this changed the Spectrum emulation state. In this respect, I believe automatic programming to be already super-human, not in the sense it is currently capable of producing code that humans can’t produce, but in the concurrent usage of different programming languages, system programming techniques, DSP stuff, operating system tricks, math, and everything needed to reach the result in the most immediate way.
JetStream’s answer is built around a feature called AI Blueprints—real-time graphs that map everything an AI system is doing inside an organization at any given moment. Each Blueprint traces the full chain of activity: which agents are running, which models they’re using, what data and tools they are interacting with, and who or what is behind each action. Rather than a static snapshot, Blueprints track live behavior, so if an AI system starts acting outside its intended purpose, the platform flags it. They also track cost, showing what each AI workflow is spending and who is responsible for it.