Super Prompt: Building in the Era of AI Agents

We review four clips from the Dwarkesh Patel Podcast with Satya Nadella, Microsoft's CEO. I highly recommend Dwarkesh’s show—technical & nerdy, but excellent.
Satya talks about scaffolding—the software wrapped around AI models to make them actually work.
So we speak with someone building that scaffolding: Neil McKechnie runs two AI-first startups as a CTO. 
He discusses how he orchestrates up to twelve different language models—GPT-5, Claude, Gemini, Llama, Mistral, Cohere, Perplexity. 
We discuss what it actually takes to build production systems with LLMs today—and what that reveals about the agent future we’re being pitched.
Dwarkesh's Podcast: https://www.youtube.com/@DwarkeshPatel
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Description:
AI agents from OpenAI, Google, and Anthropic promise to act on your behalf—booking flights, handling tasks, making decisions. What kind of agency do these systems actually have? And whose interests are they serving?
Enterprise AI agents are already deployed in customer support, code generation, and task automation. Consumer agents—ChatGPT Agent Mode, personal task assistants—face a wider gap between marketing promises and actual capabilities.
The alignment problem: agents need access to your calendar, email, and personal preferences to help you effectively. But the agent that knows you well enough to serve you is also positioned to steer you. When you delegate decisions to an agent, who decides what success looks like?
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With great power comes great responsibility. How do leading AI companies implement safety and ethics as language models scale? OpenAI uses Model Spec combined with RLHF (Reinforcement Learning from Human Feedback). Anthropic uses Constitutional AI. The technical approaches to maximizing usefulness while minimizing harm. Solo episode on AI alignment.

REFERENCE
OpenAI Model Spec
https://cdn.openai.com/spec/model-spec-2024-05-08.html#overview
Anthropic Constitutional AI
https://www.anthropic.com/news/claudes-constitution

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Notable open source large language models from Meta, French AI company Mistral (valued at $2B), Microsoft, and Apple. Not all open source models are equally open—the restrictions and licensing constraints you need to know before deploying one. Solo episode.
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Why enterprises and entrepreneurs choose open source LLMs like Meta's Llama—cost-effectiveness, control, privacy, and security. The safety and ethics debate: which poses greater risk to humanity, open source or proprietary AI models? Both? Neither? Solo episode on open source LLMs.
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