//Agent Development
Reasoning Models and Test-Time Compute: Letting AI Agents Think Before They Act
Tags : agent architectureAgent DevelopmentAI agentsAI inferenceAI reasoningChain of ThoughtExtended Thinkinginference computelanguage modelsreasoning engineReasoning ModelsReinforcement Learningtest time scalingTest-Time Computethinking models
Reasoning models and test-time compute let AI agents generate a hidden chain of thought — planning, checking assumptions, and self-correcting — before they take action. A practical look at why smarter inference beats bigger models, the latency and cost trade-offs, and how to put reasoning agents into production without overspending.
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How the Model Context Protocol (MCP) Connects AI Agents to Your Data
Tags : Agent DevelopmentAgent FrameworkAgent SecurityAI agentsAI IntegrationAI InteroperabilityAI StandardsContext EngineeringLLMMCPModel Context ProtocolOpen Source AIPrompt InjectionSDKTool Use
Every AI agent eventually hits the same wall: the model is capable, but it cannot reach the data and tools it needs to act. For years, that meant a fresh custom integration for every new database, file store, or API a team wanted its agents to touch. The Model Context Protocol, or MCP, is an..
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