Meta-Code, Scaling Strategies, and the Next Wave of Agent Infrastructure
Research
Self-Evolving Agents via Meta-Code Architecture
This paper gives us the blueprint for turning agents into engineers. For builders, this means moving from prompt chains to self-evolving systems that push their own performance curves.
Optimizing Agent Memory for Long-Horizon Tasks
Context windows are the new bottleneck. This paper offers a concrete architectural fix to keep agents fast and cheap without fatal data loss, solving a massive scaling problem.
Why Agents Get Stuck: Parsing Tool-Calling Failures
Another lesson in reliability: why basic tool-calling can kill autonomous chains. Critical for anyone building production pipelines who needs the failure modes mapped before deployment.
Tools
Firecrawl just made the web less messy for AI. If your agents do heavy research, this lets them browse at full speed without constantly getting stuck on layout changes.
News
Salesforce is making its agents the system of record, not just assistants. This mirrors the MLOps lift-and-shift and means enterprise automation budgets are finally migrating to agent-native workflows.
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