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All digests tagged Microservices Architecture
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Securing AI agents requires moving beyond standing credentials. By implementing OAuth token exchange and using a Security Token Service (STS), organizations can enforce task-scoped, ephemeral access, mitigating the risk of the 'lethal trifecta.'
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Learn how Postman mapped 115 microservices into an API context graph to enable coding agents to function across complex, distributed systems. Discover how to improve API discovery and impact assessment.
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To ensure AI safety, agents must run in sandboxes that are modeled after the task's intent. Safety comes from limiting tools and context, not from the harness itself.
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Aspire AppHost simplifies polyglot development by providing a unified orchestration layer for mixed-stack projects. It automates service wiring, manages configuration via environment variables, and offers centralized observability across languages.
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Ungoverned skills are a form of technical debt. To scale AI-native organizations, know-how must be managed via a centralized skills catalog that enforces versioning, ownership, and composability.
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To unlock agent autonomy, we need a new runtime layer enforcing safety. This system uses Containment, Scoped Capabilities, and Intent-Based Access to prevent agents from expanding their blast radius.
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AI models are no longer the bottleneck in code review; context is. The future requires moving from line-by-line diff checking to reviewing an entire software development graph that tracks service contracts and dependencies.
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Managed Deep Agents simplifies agent deployment by bundling the Deep Agents harness with infrastructure like Context Hub and durable execution, enabling seamless transition from local code to production scale.
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Learn how to integrate AI agents into event-sourced systems for fraud detection. By building a semantic layer over multiple bounded contexts, you can resolve ambiguous transactions that traditional ML models miss.
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Discover SQL MCP Server: The open-source solution for secure data access. It provides a standardized API layer to connect AI agents and modern apps to your enterprise database, simplifying development and enforcing security.
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Learn the definitive five-layer stack for AI automation: Backend (Python/FastAPI), Database (Postgres/Supabase), Frontend (React/Vite), AI Models, and Infrastructure (Docker). Build production-ready systems.
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