How AI tools can go wrong and how to work around it. Covers hallucinations, sycophancy, context limits, and other common model weaknesses.
Articles (3)
How to give AI tools the right information at the right time to produce accurate, useful responses.
The architectural tradeoffs of modern large language models and the core weaknesses that emerge from alignment training.
Why AI models tend to validate users instead of challenging flawed assumptions, and how to push back for more honest answers.