The generative-AI gold rush has bred two things in equal measure: astonishing progress and an ocean of low-grade advice. New capabilities ship weekly; yesterday’s “best practice” can be today’s foot-gun.
Below is a bookmark list that will serve as a stable launchpad.

1. Begin with primary sources

OpenAI’s own material is concise, current, and largely free of hype. Unfortunately it’s scattered, so here’s a (non-conclusive) overview:

• OpenAI Academy – live sessions and recordings. Look for the “Introduction to ChatGPT” on the 10th this month.
• OpenAI for Startups – despite the name, most content applies to others as well
• OpenAI for Business (LinkedIn) – quick, scenario-driven walkthroughs.
• Put AI to Work for Marketing Teams – ignore the title; solid demos.
• Collaborative Writing and Coding with OpenAI Canvas – inventor Karina Nguyen herself explains OpenAI Canvas, a side-by-side workspace where you and ChatGPT can collaboratively edit and refine text or code
• Plus: the gated OpenAI “Platinum” Forum has a wealth of content also

2. Sober macro-perspective

• Ethan Mollick – his book gives a crisp overview of “what AI can do.” It predates the o3 modell but is still a useful primer.
  • Tip, for example: be mindful of ChatGPT’s Memory feature.

3. Pragmatic cheat-sheets

• Model-picker flow chart – intended to help with the overcrowed model selector in paid-for ChatGPT plans.
• … with Prompts included (I am wary, though)

4. Beyond ChatGPT: Developer superpowers

The polished packaging of ChatGPT comes at the expensive of throttled horsepower - relatively. Developers can interact with the models more directly and exercise greater control - e.g. per Ethan Mollicks advice about “memory”, just even more low-level. A ressource handed out at the OpenAI Hackathon in Paris is the “OpenAI Dev Resources” Notion Site.