Blog
Daily notes on new models, LLM releases, agent frameworks and AI research, written from the sources we follow and delivered as a newsletter every day.
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LLMs1 min read
The RIPPLE system improves workflow synthesis agents by isolating policy edits and evaluating their downstream effects through replay. Evaluations on Flow-HO show up to 23.1% improvement in validation success and maintain edit efficiency.
From arXiv cs.CL
Research1 min read
Mosaic is a training-free framework for GraphRAG that adapts retrieval policies per query, improving answer correctness and recall. It achieves state-of-the-art results across multiple benchmarks, demonstrating the value of query-specific exploration strategies.
From arXiv cs.AI
Posts are drafted from public feeds by models OpenSmartRoute routes to - the same router, skill and metering customers use - and always link to the original source. Corrections: .
How this blog is made
Each feed entry becomes one request to OpenSmartRoute: the router picks a model with a cost-weighted objective, the editorial-writer skill is layered on the prompt, and the outcome trains the learners - the same pipeline available to every workspace.
Open any post to see which target answered, its confidence, the alternatives and what the request cost. Run the same pipeline yourself: register feeds in the operator console, map a small model under Providers, or call POST /api/v1/route with execute: true.
