I’ve long felt that while the Gemini 3 Pro model is fairly good, the Gemini CLI harness isn’t. I saw an example of this today. Me: Tell me the GitHub IDs of all students in this directory. Gemini CLI: SearchText 'github' within ./ Found 100 matches (limited) Sending this message (14606686 tokens) might exceed the remaining context window limit (1037604 tokens). Me: Only send the (small) required snippets of data. Write code as required. ...
Instead of learning and applying new Codex features, I asked it to analyze my sessions and tell me what I’m under-using. I'd like you to analyze my Codex sessions and help me use Codex better. sessions/ has all my past Codex sessions. Search online for the OpenAI Codex release notes for the latest features Codex has introduced and read them - from whatever source you find them. Then, create a comprehensive catalog of Codex features. Then, analyze my sessions and see which feature I could have used but didn't and make a comprehensive list. Then summarize which features I should be using more, how, what the benefits are, and with examples from my sessions. Document these in one or more Markdown files in this directory. Write scripts as required. Commit as you go. It did a thorough job of listing all the new features and analyzing my gaps. ...
Arun Tangirala and I webinared on “AI in Education” yesterday." “(“Webinared” is not a word. But “verbing weirds language”.)” Mid-way, Jose Swan from the audience asked, “Can you summarise this session using an AI? There are SEVERAL tools you can use to summarize talks. Whisper for transcription, FFMpeg for keyframe extraction, #NotebookLM for podcast generation, text-embedding-3-small for topic modelling, and of course, any regular LLM include #ChatGPT for summarization or translation. ...