AI Research

A modular skill distilled from Neel Nanda’s research process sequence (Posts 1–3).
The goal is to help you make progress under uncertainty by identifying the right stage, the right north star, and the right next actions.

This skill is designed for empirical research with short feedback loops, but generalizes broadly.

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North star

Research progress looks different at different stages:

• Explore: maximize information gained per unit time
• Understand: gather evidence that convinces you a hypothesis is true or false
• Distill: compress findings into concise, defensible, communicable truth

A common failure mode is using the wrong standard for the current stage.

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How to use

Common inputs

• A short description of the project
• Current artifacts (results, plots, notes, draft text)
• What feels confusing or stuck
• Any constraints (deadline, compute, scope)

(Use: Intake template)

Common outputs

• Current stage + north star
• Top uncertainties
• 1–3 prioritized next actions
• A fast-fail test (if the direction is wrong)
• Baselines / alternative explanations to check
• If applicable: hypothesis or claim distillation

(Default output format: Triage output template)

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Workflows

A) “I’m stuck / what should I do next?”

1. Stage classifier
2. Run the relevant stage module:
   • Explore → Exploration: information gain
   • Understand → Understanding: hypotheses & evidence
   • Distill → Distillation: communicable truth
3. Prioritisation
4. Produce triage output

B) “I don’t trust my results”

1. Truth-seeking
2. Understanding: hypotheses & evidence
3. Red-team checklist

C) “I need to move faster”

1. Moving fast
2. Tight feedback loops
3. Fail fast

D) “I need to write this up / distill”

1. Distillation: communicable truth
2. Distillation claims template
3. Hypothesis ↔ evidence map

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Modules index

• 00 Overview
• 01 Stage classifier
• 02 Ideation & problem choice
• 03 Exploration: information gain
• 04 Understanding: hypotheses & evidence
• 05 Distillation: communicable truth
• 06 Truth-seeking
• 07 Prioritisation
• 08 Moving fast
• 09 Tight feedback loops
• 10 Fail fast
• 11 Action under uncertainty
• 12 Research taste: overview
• 13 Research taste: ingredients
• 14 Cultivating research taste
• 15 Common failure modes

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Templates

• Intake template
• Triage output template
• Experiment plan template
• Red-team template
• Distillation claims template
• Weekly review template

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Acknowledgements

Compiled from Neel Nanda’s research process sequence (Posts 1–3, Apr–May 2025).