Experiments and results
Read the question, comparison, findings, and limits before applying a result.
These six reports describe the author's own experiments. Each one answers one question. Read a result with the workload and comparison in its original report.
Retrieval and context
When one representation loses detail
What happened on real prose
Conditioning on an objective
Selection and economics
Diversity and the consuming model
Memory measurements
Use a result carefully
Look for the dataset, questions, baseline, evaluation measure, model configuration, and uncertainty. Do not infer an industrial deployment result from a text-retrieval benchmark. New modality and agent-loop experiments need their own evidence.
See how to test a context design, what changed, and proposed investigations.
Cite this page
Written by Murali Sid, Founder and AI Systems Architect, last updated 15 October 2026. Licensed CC BY-SA 4.0, so quote it freely with attribution.
Murali Sid (2026). Experiments and results. Agentic Architecture Skills. https://www.agenticarchitectureskills.com/research/experimentsMachine-readable version of this page: /research/experiments.md