Your 1 million token context window is lying to you. The bigger you make the prompt, the worse the model gets at using it. It reads the start, reads the end, and skims the middle. A longer prompt is not a better prompt. You pay more, wait longer, and usually get a worse answer. This is why every serious AI agent in 2026 runs context compaction. I broke down 11 of these techniques and the exact order I run them in. #short

As you know, Anthropic became the first AI company blacklisted by the US government. The story everyone shared was simple. They said no to surveillance and weapons, got cut off, and OpenAI swooped in for the deal. Here's the part that got skipped. Anthropic wasn't refusing to work with the government. They'd been inside classified systems since 2024. So had OpenAI. The actual fight was narrow. The Pentagon wanted two safeguards pulled from Claude: mass domestic surveillance and fully autonomous weapons. Anthropic drew the line right there, loudly and in public. And OpenAI never signed the exact deal Anthropic walked away from. A few days later they quietly tightened their own wording, much closer to where Anthropic had been pushing the whole time. So it was never one clean company saying no and another saying yes. Both were already in. They just handled the line very differently once it got explicit. There's a lot more to it. The lawsuits, the supply chain risk label, the sympathy wave that shot Claude to number one. I covered the full timeline in the video 👇 #short