AI Engineer Notebooks – free, framework-free RAG/agents/evals on Colab
calmrocks
79 points
9 comments
August 27, 2026
Related Discussions
Found 5 related stories in 68.7ms across 4,692 title embeddings via pgvector HNSW
- Six months of writing code exclusively with agents bryanmikaelian · 66 pts · August 27, 2026 · 60% similar
- Terminal-Bench-Science: Evaluating AI agents on scientific research workflows matt_d · 61 pts · August 28, 2026 · 58% similar
- Show HN: Open-source playground to red-team AI agents against public prompts zachdotai · 13 pts · August 09, 2026 · 57% similar
- Show HN: Ratel, give agents unlimited tools and skills without context bloat jack1689 · 19 pts · July 16, 2026 · 56% similar
- Scientific computing in the age of agentic AI mfiguiere · 27 pts · July 28, 2026 · 56% similar
Discussion Highlights (4 comments)
consumer451
Man, I could have used something like this last year. Upon review, it appears that fumbling my way through the dark with Claude and Google led to the same place, in nearly all cases. However, this is all written by Claude — it has too many em-dashes to not be, does it not? So, maybe that's why we ended up in the same places. Does anyone know of any other resources in this vein?
nycdatasci
Why does applied AI intentionally exclude a framework/harness around AI? The job is to harness the power of AI, and a harness is a critical part of that.
KolibriFly
Glad to hear they are prioritizing evaluation right from the start. Usually people just throw together a rag pipeline on the knee and then judge the metrics by eye, skimming three responses in the terminal
ghm2199
One thing that evals are super important from the get go are where the harness+model inference is part of the product, e.g. if you are doing voice ai, building out a test harness to test the system is a non trivial first step.