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Issue #4 ยท WeeklySep 30, 2026

Paper of the Week #4 โ€” A Memory of Procedures, or a Memory of Examples?

Designer-RSI grows a natural-language skill bank from user traffic and lifts execution success from 72.7% to 99.3% with no weight updates. I built the narrow version on a task with human labels: 40 rules distilled from the model's own mistakes fixed 4 items and broke 5. Retrieving five raw examples fixed 19 and broke none.

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How Far Does a Simple Classifier Get? Chapter 2 of a Book on Building Decision Systems

How Far Does a Simple Classifier Get? Chapter 2 of a Book on Building Decision Systems

Free sample chapter: split BANKING77 before training, then two CPU classifiers reach 91.2% and 92.9% on the test set, with code that runs in about a minute.

- Models & Algorithms
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Which Messages Should Go to a Person? A Classifier, a Decision Model and a Hand-Off, Measured

Which Messages Should Go to a Person? A Classifier, a Decision Model and a Hand-Off, Measured

On BANKING77 a decision model after a classifier saved no hand-offs. On CLINC150 unknown questions broke the thresholds; adding 250 to validation halved the leaks.

- Models & Algorithms
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Classifier, LLM or Decision Model? A Measured Guide to Text Classification

Classifier, LLM or Decision Model? A Measured Guide to Text Classification

One path through every text-classification measurement on this blog: on the same 154 banking messages, a CPU classifier scored 90.3%, an LLM with five retrieved examples 94.8%, and Jev 76.0%. Which to use, and when.

- Models & Algorithms
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Ollama's Decision Models on the Same Questions as Jev: Nimble and Tev1, Measured

Ollama's Decision Models on the Same Questions as Jev: Nimble and Tev1, Measured

On the same questions as Jev, Ollama's Nimble 9B scored 95.6% on TREC (Jev 89.0%) but 76.0 against 85.7 on a 4,599-question reasoning-heavy panel.

- Models & Algorithms
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Paper of the Week #4 โ€” A Memory of Procedures, or a Memory of Examples?

Paper of the Week #4 โ€” A Memory of Procedures, or a Memory of Examples?

Designer-RSI grows a natural-language skill bank from user traffic and lifts execution success from 72.7% to 99.3% with no weight updates. I built the narrow version on a task with human labels: 40 rules distilled from the model's own mistakes fixed 4 items and broke 5. Retrieving five raw examples fixed 19 and broke none.

- AI Research
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Jeff vs Jev on the Same Questions: Overall Scores and a 26-Option Limit (Fixed in v1.1)

Jeff vs Jev on the Same Questions: Overall Scores and a 26-Option Limit (Fixed in v1.1)

On Jeff's own 4,599 questions, Jev scored 85.7 and Jeff-2B 83.0. Jeff v1.0 never picked an option past the 26th in my tests; v1.1 fixes that, remeasured.

- Models & Algorithms
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