AI agents are moving beyond individual interactions towards systems that can maintain context, manage ongoing tasks and act while users are away. This article examines the architecture behind persistent intelligence, from memory and task orchestration to cloud execution, proactive coordination, multi-agent systems and governance.
Always-On AI Agents: Persistent Intelligence Architecture Read More »
Google’s intelligence ecosystem is extending beyond individual models into a broader architecture of reasoning, multimodal generation, interactive simulation and connected applications. This article examines how Gemini, Genie and Connected Apps fit into that emerging stack, exploring MCP integration, Android AppFunctions, delegated authorisation, execution boundaries and the governance required to connect intelligence with external systems.
Google’s Emerging Intelligence Stack: Gemini, Genie and Connected Apps Read More »
AI work agents are changing how people interact with software. This article examines the architecture behind agent workspaces, exploring orchestration, execution environments, application connectivity, permissions, security and the systems required to complete meaningful work.
The Architecture of AI Work Agents: Execution, Permissions and Deliverables Read More »
System One Models may fit best where software needs repeated, bounded decisions over rich context, meaningful uncertainty, and programmatic control.
TypeSafe evaluates System One Models inside structured software workflows rather than relying only on conventional model benchmarks. Here is what that methodology measures and leaves open.
System One Models change the computational problem by focusing on bounded decisions rather than open-ended language generation. Explore what this could mean for latency, throughput, and inference economics.
