This article examines how integrating AI into the software development lifecycle (SDLC) is enabling teams to move from MVPs to large, resilient systems.
AI Agents perceive, reason, plan, and act autonomously using LLMs. This article breaks down the core components that power every agent and shows you how to build one.
This article provides a practical guide to building a fault-tolerant Google Cloud data pipeline architecture with Firestore, Pub/Sub, Dataflow, and BigQuery.
ML systems introduce security risks most teams aren’t prepared for. The piece explores emerging ML-specific threats and what effective MLSecOps looks like in practice.
How cloud-native microservices transform insurance analytics by enabling scalability, real-time processing, and seamless modernization of legacy platforms.
Feature flags and safe rollouts with Azure App Configuration for large SPA teams, hands-on setup, core principles, TypeScript code for backend and frontend.
AI enhances Workday integrations by improving mapping, testing, and monitoring, but it fails when used without human oversight, domain expertise, and strong governance.
Build long-running workflows by separating orchestration from execution, persisting state, and using events or callbacks to pause and resume without holding compute.
Tools like Ansible enable modernization but introduce a coding skills gap. This article outlines a pattern to democratize automation using intermediate tooling.
How we built a self-healing infrastructure automation platform, enabling faster recovery, lower on-call load, and reliability that scales with the system.