AI engineering article archive

Explore guides and articles on AI development, retrieval systems, and production engineering. Page 7 of 11.

• Holistic Engineering Organic Problem Solving Complex Systems

  Holistic engineering is the practice of deliberately factoring these non-technical forces into our technical decisions, designs, and strategies.

• Multi Cloud Event Driven Architectures

  Building resilient multi-cloud event-driven systems demands latency optimization, strong recovery, and duplicate control to ensure reliability, agility, and cross-cloud consistency.

• Adopt Micro Frontends

  Micro-frontends prioritise autonomy over reuse, aligning with Conway's law. Migration should start gradually, focusing on establishing a first end-to-end flow where autonomy is most beneficial.

• Scaling Cloud Distributed Applications

  This article shares goals and strategies for scaling cloud and distributed applications, focusing on lessons learned from our cloud migration at Chase.com at JP Morgan Chase.

• Overload Protection Platform Engineering

  Shared, consistent overload protection is often missing in platform engineering, leading to fragile, inconsistent services. Central limits, visibility, and adaptive controls improve reliability.

• Java Trends 2025: JVM AI & Modernization Planning

  Review InfoQ’s 2025 Java trends: Java 25, AI frameworks on the JVM, application modernization, Jakarta EE and deployment choices.

• Secure Ai Development

  AI agents can boost productivity but pose risks. Secure the ReAct loop with provenance, critics, scoped tools, threat modeling, and bounded autonomy to prevent catastrophic failures.

• Nextgen Search Ai Opensearch Mcp

  In this article, authors discuss next-generation conversational search using OpenSearch and AI agents powered by Large Language Models (LLMs) and Model Context Protocol (MCP).

• Architecture Ai Augmented Change

  Most AI initiatives fail to scale. Architects must enable "fast flow" through clear domains and context engineering to drive continuous AI-augmented change.

• Architects Ai Era

  AI transforms architects from makers to meta-designers. The "Three Loops" model (In, On, Out) balances automation with human judgment, enabling "bionic" professionals to design responsibly.

• Evolution Backend Streaming Application

  In streaming, the challenge is immediate: customers are watching TV right now, not planning to watch it tomorrow.

• DORA Metrics PBCs

  Use DORA metrics with Process Behavior Charts to separate signal from noise, detect real delivery changes early, and turn DevOps metrics into reliable tools for improvement decisions.

• Architects Dilemma

  Software teams must decide between proven platforms and custom paths. Experiments reveal if frameworks meet MVP/MVA goals, balancing speed, scalability, and long-term support.

• Agentic Terminal Cli Agents

  In this article author Sachin Joglekar discusses the transformation of CLI terminals becoming agentic where developers can state goals while the AI agents plan, iterate, and execute the requests.

• Spec Driven Development

  Spec-Driven Development elevates specifications to executable system truth. Architecture becomes enforceable through continuous validation, while AI-powered generation materializes intent into code.

• Platform Golden Path Approach

  Declarative config abstracts infrastructure complexity, letting developers focus on code, while unified YAML enables cost validation and consistent deployments through a centralized "golden path".

• Preventing Data Exfiltration Google Cloud

  Implementing VPC Service Controls requires balancing technical controls with organizational needs. Success depends on thorough planning, phased rollouts, and making secure practices easy to adopt.

• Ai Assisted Development Series

  In this series, we examine what happens after the proof of concept and how AI becomes part of the software delivery pipeline.

• Ai Developers Rewriting Software Process

  This virtual panel brings together engineers and technical leaders to examine how AI is reshaping software development, and the importance of context, validation, and culture in daily workflows.

• Friction Fix

  Friction is the invisible current that sinks every transformation. Friction isn’t one thing– it’s systemic. The fix is changing our patterns of thinking, communicating, and organizing.

• Durable Objects Handle Inflight Requests

  Durable Objects end "thundering herds" by unifying in-flight work and cached results. Per-key singletons eliminate redundant tasks and complex locks, making distributed caching simple and efficient.

• Engineering Speed Scale

  Low‑latency systems require intentional design, strict latency budgets, caching, async patterns, and strong observability. Architecture creates speed; culture sustains it as systems evolve.

• Agent Reinforcement Learning Apache Spark

  This article introduces a reinforcement learning (RL) approach grounded in Apache Spark that enables distributed computing systems to learn optimal configurations autonomously.

• Why Ml Projects Fail Production

  In this article, the author diagnoses common failures such as weak problem framing and the prototype-to-production gap, and offers practical guidance for successful ML project delivery.

• Skeleton Architecture

  Skeleton Architecture tames AI tech debt. By separating human-owned base classes from AI logic, it enforces security and structure, enabling high velocity without architectural drift.

• Agent Assisted Intelligent Observability

  As systems grow, alert noise rises. Agentic observability layers AI on existing tools, starting read-only to spot anomalies, add context, correlate signals, and automate low-risk tasks.

• Building Llms Resource Constrained Environments

  In this article, the author argues that limitations can drive innovation, demonstrating how smaller models and disciplined engineering allows for impactful AI systems despite resource constraints.

• Jakartaee 12 Milestone 2

  Jakarta EE 12 Milestone 2 unifies querying across Persistence, Data, and NoSQL via Jakarta Query and embraces Java 21 to deliver a more modern, integrated enterprise Java platform.

• Prompts To Production Playbook For Agentic Development

  In this article, author Abhishek Goswami shares a practitioner's playbook with development practices, that describes building agentic AI applications and scaling them in production.

• Ai Generated Mvp

  AI‑generated code creates implicit architectural decisions, forcing teams to rely on experimentation to validate quality attributes.

• Architecting Agentic Mlops A2a Mcp

  In this article, the authors outline protocols for creating extensible multi-agent MLOps. The architecture decouples orchestration from execution, enabling discovery and intelligent coordination.

• Proactive Autoscaling Edge Kubernetes

  Default Kubernetes scaling often reacts too late for edge systems. Using response time, spare capacity, and startup delays helps scale earlier, reduce spikes, and keep performance steady at the edge.

• Enterprise Spec Driven Development

  Spec‑Driven Development helps align intent between humans and AI, but enterprise adoption requires cultural change, workflow integration, and scalable collaboration patterns.

• Building Ai Agent Gateway Mcp

  This article presents a least-privilege AI Agent Gateway that controls how agents access infrastructure. Every request is validated, authorized, and executed in isolated, short-lived environments.

• Panel 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.

• Kotlin Scalable Swiftui Patterns

  iOS developers often rely on samples that don’t mirror real-world scale, while Kotlin provides proven architectural guidance. Here’s how to translate those ideas into SwiftUI for apps that scale.

• Read Copy Update

  Unlock unprecedented read scalability with RCU: a revolutionary lock-free approach that outperforms traditional reader-writer locks by maximizing efficiency in read-heavy workloads.

• Change Metrics System Reliability

  Change-related metrics are first-class reliability signals. A minimal set of business and technical indicators, backed by event-centric observability, connects delivery performance to reliability.

• Oil Water Moment Ai Architecture

  What happens when deterministic software meets non deterministic AI? Like oil and water, the mix creates new architectural challenges. Intent driven design is becoming the stabilising force.

• Evaluating Ai Agents Lessons Learned

  This article presents practical approaches to evaluating AI agents in production systems, covering benchmarks, hybrid evaluation pipelines, reliability assessment, and real-world system behavior.