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The Latest Popular Topics

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Automating Traceability with Generative AI
Here is an architectural pattern to automate traceability checks by combining batch configuration extraction with Generative AI validation.
January 20, 2026
by Dippu Kumar Singh
· 2,158 Views
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Enterprise LLM Architecture Patterns, From RAG to Agentic Systems
A practical guide to 11 proven LLM architecture patterns, with real-world examples for building scalable, trustworthy, production-ready AI systems.
January 20, 2026
by Ram Ghadiyaram DZone Core CORE
· 6,678 Views · 6 Likes
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The Messaging Challenges No One Talks About in Regulated, Air-Gapped, and Hybrid Environments
For platform engineering, today's solutions fall short, creating a gap between operational security requirements and modernization goals.
January 20, 2026
by Alvin Lee DZone Core CORE
· 1,901 Views
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Why High Performance Storage is Important for AI Cloud Build
Learn the technology and architecture behind building AI Cloud and why high performance storage is important. Explore the latest benchmarks and understand the market.
January 20, 2026
by Anjul Sahu
· 2,069 Views
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“Just Don’t Put PII in the Prompt” Is a Trap: A Two-Plane Architecture for Safe LLM Apps
Separate Data Plane (sensitive data/actions) from Prompt Plane (sanitized context). Use IDs + summaries so secrets never enter prompts.
January 20, 2026
by Mohan Sankaran
· 1,500 Views · 5 Likes
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DeepSeek’s mHC: Manifold-Constrained Hyper-Connections, Explained for Practical Use
An overview of how DeepSeek’s manifold-constrained hyper-connections (mHC) stabilizes multi-stream residual networks while improving performance at scale.
January 19, 2026
by Praveen Kumar Myakala
· 1,898 Views · 2 Likes
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Copilot, Code, and CI/CD: Securing AI-Generated Code in DevOps Pipelines
AI coding tools boost speed but weakens security and developer judgment. Here’s how hidden vulnerabilities escape review and what must change before a breach hits.
January 19, 2026
by Igboanugo David Ugochukwu DZone Core CORE
· 1,841 Views
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RAG at Scale: The Data Engineering Challenges
The data engineering challenges that go beyond the basic concept of RAG when running RAG systems at scale in production.
January 16, 2026
by Guru Hegde
· 2,958 Views · 1 Like
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From RAG to RAG + RAV: A Practical Pipeline for Factual LLM Responses
RAG reduces hallucinations, RAV verifies each claim, and together they yield far more trustworthy LLM answers with optional corrections for accuracy.
January 16, 2026
by Sai Teja Erukude
· 4,615 Views · 3 Likes
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Micro Frontends in Angular and React: A Deep Technical Guide for Scalable Front-End Architecture
Module Federation, Custom Elements, and orchestrators like Single-SPA enable independently evolving, maintainable applications with a seamless user experience.
January 16, 2026
by Renjith Kathalikkattil Ravindran
· 4,069 Views · 1 Like
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From Chatbot to Agent: Implementing the ReAct Pattern in Python
This article provides a raw Python implementation, moving beyond high-level frameworks to show exactly how the agentic loop works under the hood.
January 16, 2026
by Nikita Kothari
· 3,354 Views · 2 Likes
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Integrating CUDA-Q with Amazon Bedrock AgentCore: A Technical Deep Dive
This integration lets AI agents use GPU-accelerated quantum simulations as tools in their workflows. Learn more in this deep dive.
January 16, 2026
by Rakesh Kumar Pal
· 1,760 Views · 1 Like
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RAG on Android Done Right: Local Vector Cache Plus Cloud Retrieval Architecture
Most mobile RAG fails on latency and flaky networks. A local vector cache + cloud retrieval architecture keeps responses fast, fresh, and grounded.
January 16, 2026
by Mohan Sankaran
· 2,577 Views · 5 Likes
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Securing AI-Generated Code: Preventing Phantom APIs and Invisible Vulnerabilities
AI coding tools accelerate delivery but create new security blind spots. Learn how phantom APIs emerge — and what developers can do to catch them early.
January 15, 2026
by Igboanugo David Ugochukwu DZone Core CORE
· 2,415 Views · 1 Like
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DevSecOps for MLOps: Securing the Full Machine Learning Lifecycle
Why ML systems are uniquely vulnerable to security attacks — and how MLSecOps closes the gaps in data, models, and pipelines.
January 15, 2026
by Igboanugo David Ugochukwu DZone Core CORE
· 2,275 Views · 2 Likes
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From Aspects to Advisors: Design Modular Cross-Cutting Features with Spring AI
Understand how Spring AI Advisors work and see how Aspect Oriented Programming concepts can be applied when interacting with LLMs.
January 15, 2026
by Horatiu Dan DZone Core CORE
· 2,552 Views · 5 Likes
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Taming Reinforcement Learning Chaos: An MLOps Architecture for Experiment Management
Reinforcement learning is powerful, but managing thousands of iterations is a nightmare. Here is a practical architecture for building a lightweight experiment system.
January 15, 2026
by Dippu Kumar Singh
· 1,452 Views · 1 Like
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Resilient API Consumption in Unreliable Enterprise Networks (TypeScript/React)
Build robust React clients with explicit timeouts, retries, circuit breakers, cancellation, idempotency, and optimistic UI, plus Axios–RTK Query integration guidance.
January 15, 2026
by Hanna Labushkina
· 3,644 Views · 3 Likes
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Real-Time Recommendation AI Architecture: Streaming Events and On-Device Ranking
This Android recommendation architecture streams events to the backend and uses on-device ranking to deliver fast, resilient, privacy-aware recommendations.
January 15, 2026
by Mohan Sankaran
· 1,377 Views · 6 Likes
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9 Tips for Building Apps to Withstand AI-Driven Bot Attacks
Here are nine tips for app dev teams to strengthen app protections and frustrate AI-driven bot attacks, without harming user experience.
January 15, 2026
by Philip Piletic DZone Core CORE
· 1,741 Views · 1 Like
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