Everything we have talked about and built together, in order.

Past meetings, most recent first.

Talks, demos, and collaborative projects from every Nerds Like Me gathering. More meetings will appear here after they happen.

• Talk: What large language models actually are — and what they are not A grounded walk through how these models work, what the token-prediction framing misses, and why your intuitions about memory and reasoning may need updating.
• Demo: Building a local image classifier in an afternoon A member walked through training a small classifier on personal photos using open tools, no cloud account required. Included the parts that did not work on the first attempt.
• Discussion: Agents — what the word actually means right now Open floor on what people are calling agents, what is real versus marketing, and where the useful patterns are emerging in 2025.
• Project: Group prompt-engineering exercise We took the same task, wrote ten different prompts, and compared outputs. The conversation about why some worked was better than the results themselves.
• Talk: Fine-tuning a small model on domain-specific text A walkthrough of the practical questions — dataset size, compute cost, when fine-tuning beats prompting — with a live example from a member's side project.
• Demo: Using embeddings to search a personal notes archive How one member indexed two years of plaintext notes and built a semantic search interface that actually gets used every day.
• Discussion: AI tools in everyday work — what is actually sticking Members shared what they have adopted, what they tried and dropped, and what they are still skeptical about. Less hype, more honest accounting.
• Project: Mini hackathon — build something useful in two hours Teams of two or three, one constraint (no existing API wrappers), two hours. Three projects presented; one is still running in production for a member's day job.