InfoQ Homepage Programming Content on InfoQ
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/articles/ai-agent-transport-layer/en/smallimage/ai-agent-transport-layer-thumbnail-1775031603285.jpg)
Stateful Continuation for AI Agents: Why Transport Layers Now Matter
Agent workflows make transport a first-order concern. Multi-turn, tool-heavy loops amplify overhead that is negligible in single-turn LLM use. Stateful continuation cuts overhead dramatically. Caching context server-side can reduce client-sent data by 80%+ and improve execution time by 15–29% .
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/articles/beyond-rag-context-aware/en/smallimage/beyond-rag-context-aware-thumbnail-1774531119239.jpg)
Beyond RAG: Architecting Context-Aware AI Systems with Spring Boot
This article introduces Context-Augmented Generation (CAG) as an architectural refinement of RAG for enterprise systems. It shows how a Spring Boot-based context manager can incorporate user identity, session state, and policy constraints into AI workflows, improving traceability, consistency, and governance without altering existing retrievers or LLM infrastructure.
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/articles/event-driven-banking-architecture/en/smallimage/event-driven-banking-architecture-thumbnail-1774430827143.jpg)
Event-Driven Patterns for Cloud-Native Banking: Lessons from What Works and What Hurts
Event-driven architecture helps banks decouple systems, scale services, and create clear activity trails. But it also introduces complexity, new failure modes, and operational challenges. Chris Tacey-Green explains where it adds value in banking systems and the practical patterns, such as inbox/outbox and stable event contracts, needed to make it reliable.
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/articles/adopting-swiftui-at-scale/en/smallimage/swiftui-at-consumer-scale-lessons-from-adopting-it-with-50-million-users-thumb-1773911055159.jpg)
Lessons from Adopting SwiftUI in an App with 50 Million Users
Most SwiftUI educational content focuses on small projects and sample apps that do not explain what it means to adopt it in a 50 million user app developed by a team of 20+ iOS engineers. This article will attempt to fill this gap. and show how to succeed without breaking your team, your app, or your users' trust along the way.
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/articles/configuration-control-plane/en/smallimage/configuration-as-a-control-plane-designing-for-safety-and-reliability-at-scale-thumb-1773657574566.jpg)
Configuration as a Control Plane: Designing for Safety and Reliability at Scale
Configuration has evolved from static deployment files into a live control plane that directly shapes system behavior. The evolution of configuration management highlights why misconfigurations can trigger large outages and how hyperscalers deploy changes safely using staged rollouts, validation, blast radius limits, and automated rollback at scale.
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/articles/practical-robustness-going-beyond-memory-safety-rust/en/smallimage/beyond-memory-safety-what-makes-rust-different-lessons-from-autonomous-robotics-thumb-1773646654979.jpg)
Beyond Memory Safety: What Makes Rust Different – Lessons from Autonomous Robotics
This article explores that question through the lens of a real-world Rust project: a system responsible for controlling fleets of autonomous mobile robots. While Rust's memory safety is a strong foundation, its true power lies in the type system and ownership rules. The session will go beyond memory safety and explore ways to encode behavior and protocols directly into types.
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/articles/read-copy-update/en/smallimage/read-copy-update-thumbnail-1772618412119.jpg)
Read-Copy-Update (RCU): the Secret to Lock-Free Performance
Innovative software engineer with expertise in optimizing concurrency through advanced techniques like Read-Copy-Update (RCU). Proven track record of boosting read performance by over 110% in read-heavy workloads. Skilled in leveraging RCU principles across production systems, enhancing architecture efficiency, and streamlining data handling to maximize scalability and minimize overhead.
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/articles/kotlin-scalable-swiftui-patterns/en/smallimage/thumbnail-kotlin-scalable-swiftui-patterns-1771922819056.jpg)
Borrowing from Kotlin/Android to Architect Scalable iOS Apps in SwiftUI
Building iOS apps can feel like stitching together guidance from blog posts and Apple samples, which are rarely representative of how production architectures grow and survive. In contrast, the Kotlin/Android ecosystem has converged on well-documented, real-world patterns. This article explores how those approaches can be translated into Swift/SwiftUI to create maintainable, scalable iOS apps.
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/articles/panel-high-performing-teams/en/smallimage/panel-high-performing-teams-thumbnail-1771509840628.jpg)
Virtual Panel - Culture, Code, and Platform: Building High-Performing Teams
In this virtual panel, we'll focus on performance improvement through platform engineering and fostering developer experience, to increase productivity, quality, developer well-being, and more. We'll also explore the role that tech leadership can play in culture change and performance improvement for software development organizations.
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/articles/building-ai-agent-gateway-mcp/en/smallimage/building-ai-agent-gateway-mcp-thumbnail-1771417896950.jpg)
Building a Least-Privilege AI Agent Gateway for Infrastructure Automation with MCP, OPA, and Ephemeral Runners
This article presents a least-privilege AI Agent Gateway that places clear controls between AI agents and infrastructure. Agents do not access infrastructure APIs directly. Instead, every request is validated, authorized using policy as code with Open Policy Agent (OPA), and executed in short-lived, isolated environments, with built-in observability using OpenTelemetry.
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/articles/architecting-agentic-mlops-a2a-mcp/en/smallimage/architecting-agentic-mlops-a2a-mcp-1770303550343.jpg)
Architecting Agentic MLOps: a Layered Protocol Strategy with A2A and MCP
In this article, the authors outline protocols for building extensible multi-agent MLOps systems. The core architecture deliberately decouples orchestration from execution, allowing teams to incrementally add capabilities via discovery and evolve operations from static pipelines toward intelligent, adaptive coordination.
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/articles/ai-generated-mvp/en/smallimage/thumbnail-ai-generated-mvp-1770282822570.jpg)
You’ve Generated Your MVP Using AI. What Does That Mean for Your Software Architecture?
AI‑generated code creates implicit architectural decisions, forcing teams to rely on experimentation to validate quality attributes. To get useful results from AI, teams must clearly express trade‑offs and reasoning so the model can generate solutions aligned with desired QARs.