The Latest and Popular SDLC Topics

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

· 2,464 Views · 1 Like

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

· 2,783 Views · 3 Likes

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

· 3,197 Views · 1 Like

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

· 2,608 Views · 2 Likes

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

· 1,529 Views · 1 Like

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

· 1,458 Views · 5 Likes

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

CORE

· 2,060 Views · 1 Like

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

CORE

· 2,017 Views · 2 Likes

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

CORE

· 2,061 Views · 5 Likes

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

· 1,282 Views · 1 Like

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

· 3,374 Views · 3 Likes

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

· 1,129 Views · 6 Likes

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

CORE

· 1,545 Views · 1 Like

Assist, Automate, Avoid: How Agile Practitioners Stay Irreplaceable

Without a decision system, every task you delegate to AI is a gamble on your credibility and your place in your organization’s product model.

January 15, 2026

by Stefan Wolpers

CORE

· 1,603 Views · 1 Like

Your Product Doesn’t Need Another AI Feature; It Needs an AI Guardrail

Learn why adding AI isn’t always better and how guardrails ensure safe, trustworthy, and user-focused AI features in your products.

January 15, 2026

by Erioluwa Asiru

· 1,073 Views

What Actually Breaks When LLM Agents Hit Production — And How Amazon's Agent Core Fixes It

The future of LLM agents is not better reasoning — it's better engineering. This article explains why and how structured engineering turns agents into reliable systems.

January 14, 2026

by Haymang Ahuja

· 1,263 Views · 1 Like