Altman warns against surrendering judgment to AI
Altman described treating AI models as a religious authority or giving up human judgment as a safety concern. This is his stated view, preserved in a public archive.
Source: TEXXR archive ↗GPT-6 brings diagrams and tools into Chat. Try them on questions you can check—and keep independent safety evidence in view.
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A virtual village where AI characters talk and socialize. An open-source starting point for experimenting with simulated worlds; supports several model providers, including OpenAI-compatible APIs.
An inspectable template collection for summarizing URLs, text, and PDFs. Adapt one input path first, then compare its summaries with the original documents.
A Next.js demo of voice agents that call tools and hand work to specialists. Compare the chat-supervisor and sequential-handoff patterns.
Making an experiment usable by someone else
Understanding realtime events and voice interactions
Discovering and trying community experiments
Market research, business-plan examples, startup costs, and break-even planning in one reference. Use it to define a customer and a deliverable before investing in an AI service.
Details →A practical approach to comparing AI use with delivery time, quality and business outcomes. Includes review and correction time, setup and support costs; its ROI example is illustrative, not a measured earnings result.
Details →A guide to setting a monthly project spending ceiling that pauses resources when reached. Useful for experiments that create cloud infrastructure; compare a real stop with a notification-only budget alert.
Details →Your first conversations with ChatGPT
Improving a prompt you actually use
A structured introduction to AI at work
Choosing a model for a real workload
Keeping the evidence behind your work
Experimenting with local models
Understanding AI beyond a single product
Reading a stack of sources
Moving from chat prompts to working agents
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