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cs.AI2026
L3M: A Verifiable Harness and Runtime for Self-Extending and Self-Improving Agents
Carson Eisenach, Robert Joseph George, Vincent Quenneville-Belair +2
The lasting gains in AI have come from methods that absorb more computation, and language models already scale computation within a call. Useful work, though, happens across calls:…
cs.AI2026
Beyond the Harness: End-to-End Optimization of Context Artifacts for Enterprise Text-to-SQL
Kate Gwimm, Carson Eisenach
Deploying LLMs for enterprise Text-to-SQL is bottlenecked less by the model than by what context reaches it: business logic spans thousands of tables, and no model can ingest a ful…