Edition 2026.36 /
The frontier should remember
Historical research on persistent context, provenance, tools, evaluation and correction in AI systems.
The research
The idea worth keeping.
The edition explored persistent context, provenance, tool use and evaluation as complementary layers around language models. It asked whether a system can carry evidence through action and use later correction to improve subsequent work.
The public methodological point is that a generated answer and a verified outcome are different stages. Permissions, observability and human review matter when a system acts across multiple steps.
The edition’s evidence-to-outcome framework
- 01Evidence
- 02Action
- 03Verification
- 04Consequence
- 05Correction
Evidence and boundaries
Read with the original limits.
This is a research synthesis, not proof that additional system layers outperform stronger standalone models. Comparative effectiveness requires measured outcomes.