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The article argues that the real bottleneck in AI is not capability but the lack of transparency and control in the context layer, warning that opaque AI systems could reduce human agency and decision-making.
This article argues that building AI agents is easy, but providing them with sufficient business context remains the hard and unsolved infrastructure problem, proposing the need for a dedicated 'context layer' akin to GitHub for code.
The author argues that owning the context layer (unified memory, business logic) separate from AI harnesses enables true portability, using MCP servers to swap between tools like Claude Code and Codex with a one-line config change.
A discussion on building companies run by AI agents, where humans focus on strategy and agents handle execution, with the company acting as a shared context layer.
This article introduces the open-source AI assistant OpenHuman, which serves as a context layer for personal AI, connecting tools like Gmail, Notion, and GitHub to continuously understand the user's digital life. It turns fragmented information into task cues and project memories, applied across seven scenarios: email, meetings, creation, development, learning, team collaboration, and personal life management.
The article discusses the emergence of 'agent context engines' like Redis Iris as a runtime layer that combines retrieval, memory, data sync, and caching, enabling agents to work with live business data without custom integration per workflow.
The author critiques the lack of transparent benchmarking in emerging context layer and MCP optimizer tools that promise drastic token savings, noting that real-world tests fail to replicate claimed efficiencies. They urge developers to demand open, reproducible benchmarks and ask for recommendations of tools that actually deliver measurable results.
Unabyss is a MCP-native, self-updating context layer for AI applications, designed to maintain persistent context across interactions.
WrenAI is an open-source GenBI engine that enables AI agents to generate, deploy, and govern business intelligence dashboards from any database, grounded in an open context layer for trustworthy semantics and governance.