danikkk_wqs (@danikkk_wqs)

You're the bottleneck in your own system. People actually making money with AI in 2026 don't prompt manually anymore. They build loops - systems that plan, execute, and verify themselves. Example: One voice note in five finished posts out, for Instagram, Telegram, YouTube, and LinkedIn. No human involved between the start and the result. You write the goal once. The AI decides the next step, scores it, and fixes what's weak. Skip the verify step and the loopт "finishes" - but the output is mediocre, because nothing ever checked it. Skip the stop condition and it either runs forever, or you kill it by hand. Your first version will be rough. The point is to ship one that actually works. Fixing prompts, or building a system?

The best AI safety grade - a C+. Not from an underdog. From the leader. The Future of Life Institute rated major AI labs on risk management, transparency, and whether they keep their own promises. Anthropic - C+. OpenAI and Google DeepMind - C. Meta - D+. xAI, DeepSeek, and Mistral failed the assessment. Even the leader barely scraped a C+. Meanwhile, several labs have quietly walked back their own earlier safety commitments. And all of this is happening while AI gets trusted with cybersecurity, medical reviews, and autonomous agents. If you’re trusting AI with decisions, don’t ask: “Which model is smarter ?” “Who checked its safety ?”

Your prompt engineering course is trash now. Karpathy said it straight at Sequoia Ascent: stop treating LLMs as oracles. They're statistical "ghosts" they need to be guided, controlled, and constrained by rigid boundaries. Before: send text, get text back. The model forgot context on step five - and nobody knew why. Now the agent writes the code, runs its own tests, reads the error and rewrites the fix - on its own, until the tests pass at 100%. Behind this are three technologies almost nobody talks about. Transactions that roll back when the agent makes a mistake. Memory that deletes outdated facts on its own. Routing that decides which agent a given step actually needs. The human reviews it and hits "Deploy." No prompt engineering course will explain any of that.