With the recent proliferation of generative AI models (from OpenAI, co:here, Anthropic, etc.), practitioners are racing to come up with best practices around prompting, grounding, and control of outputs.Chris and Daniel take a deep dive into the kinds of behavior we are seeing with this latest wave of models (both good and bad) and what leads to that behavior. They also dig into some prompting and integration tips.Sponsors:Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.comFly.io – The home of Changelog.com — Deploy your apps and databases close to your users. In minutes you can run your Ruby, Go, Node, Deno, Python, or Elixir app (and databases!) all over the world. No ops required. Learn more at fly.io/changelog and check out the speedrun in their docs. Changelog++ – You love our content and you want to take it to the next level by showing your support. We’ll take you closer to the metal with extended episodes, make the ads disappear, and increment your audio quality with higher bitrate mp3s. Let’s do this! Featuring:Chris Benson – Website, GitHub, LinkedIn, XDaniel Whitenack – Website, GitHub, XShow Notes:Generative AI model behavior in the news:Microsoft’s AI chatbot is going off the railsA Conversation With Bing’s Chatbot Left Me Deeply UnsettledSydney’s gaslightingChatGPT political biasStable Diffusion amplification of stereotypesUseful guides related to prompt engineering:co:here prompt engineering guidePrompt engineering overview from Elvis Savaria10 Amazing Resources For Prompt Engineering, ChatGPT, and GPT-3Image generation prompt engineering guides: see here and hereUpcoming Events: Register for upcoming webinars here!