From human intent
to model behavior.
Practical guides to alignment, preference optimization, retrieval, and safety. Connect the objective to an experiment you can inspect.
Start with alignment →Follow the alignment loop.
Model alignment
Define the behavior you want. Design feedback that actually captures it.
RLHF & preference optimization
Follow the training loop, understand its objectives, and inspect what changes.
Retrieval & grounded generation
Find useful evidence. Preserve it through ranking, generation, and citations.
Build a retrieval-augmented generation workflow
Connect an answer to evidence you can inspect.
Read guideImprove reranking and retrieval quality
Improve the evidence set before the model sees it.
Read guideDesign grounded answers and useful citations
Make the relationship between claims and sources visible.
Read guideEvaluation & safety
Measure useful behavior and failure modes before making a release decision.
Evaluation and safety testing
Run a small evaluation that tells you where a system failed.
Read guideTurn safety evaluation into release gates
Turn safety observations into an accountable release decision.
Read guideRed-team prompt injection across trust boundaries
Test what happens when untrusted content asks for authority.
Read guideRead the research.
Keep asking better questions.
Explore the alignment survey, open research resources, and original papers behind these methods.
Research & reports ↗