The Latest and Popular SDLC Topics

AI Assist vs AI Complete: The Real Gap in Most AI Workflows Today

The real difference between AI features and AI that finishes the job — most enterprise AI helps with a workflow but doesn't own the outcome.

August 13, 2026

by Muralidharan Lakshmanan

· 2,100 Views · 1 Like

Orchestrating Small Language Models Without Losing Events or Context

Temporal and Kafka orchestrate small language models reliably through durable workflows, ordered events, idempotency, retries, replay, and context preservation.

August 13, 2026

by Akhil Madineni

CORE

· 2,074 Views · 3 Likes

From Microservices to Agent Services: The Next Architectural Shift

AI agents redefine service boundaries by introducing intent-driven orchestration, semantic capabilities, and autonomous decision services.

August 12, 2026

by Uthej Mopathi

CORE

· 2,937 Views · 2 Likes

The AI Memory Security Blueprint

Protect enterprise RAG systems with provenance, context isolation, and vector database governance to reduce retrieval poisoning and prompt injection risks.

August 12, 2026

by Igboanugo David Ugochukwu

CORE

· 3,662 Views · 2 Likes

Building AI-Driven Service Operations: Integrating CRM, Inventory, and Field Service

Effective AI-driven CRM implementations depend on integration with field service, inventory, ERP, and logistics so predictive insights can be executed successfully.

August 12, 2026

by Abhishek Sharma

· 1,943 Views · 2 Likes

Machine Identity Debt

Learn why traditional cloud infrastructure struggles with AI workloads and how modern identity, trust, and governance improve security in production.

August 12, 2026

by Igboanugo David Ugochukwu

CORE

· 2,078 Views · 2 Likes

The AI Software Supply Chain Blueprint

Learn how to secure AI pipelines with trusted models, verified dependencies, ML-BOMs, and supply chain controls from development to deployment.

August 11, 2026

by Igboanugo David Ugochukwu

CORE

· 3,325 Views · 1 Like

Why Traditional Cloud Infrastructure Breaks AI Workloads in Production

Legacy cloud infrastructure can't keep pace with AI workloads. Let's deep dive into the key failure points and how to fix them in production.

August 11, 2026

by Mohit Shah

· 2,628 Views · 1 Like

The Agent in Your Pipeline Doesn't Have a Manager. That's the Problem.

AI agents are flooding development environments faster than governance can keep up. Learn why visibility, identity, and access controls matter now.

August 11, 2026

by Igboanugo David Ugochukwu

CORE

· 1,619 Views

Incident Management and the Rise of AI SRE Agents

A newer category, dedicated AI SRE agents, goes further: they actively query logs, metrics, and deploy history live during an incident.

August 11, 2026

by Vidyasagar (Sarath Chandra) Machupalli FBCS

CORE

· 2,600 Views · 2 Likes

A Framework-Agnostic Approach to SSR for Microfrontends

Framework-agnostic SSR for independently deployed microfrontends — without a shared build, central orchestrator, or framework lock-in.

August 11, 2026

by Vitaly Zheltko

· 2,355 Views · 1 Like

We Empowered AI Agents With 'Hands,' Now We Require Kernel-Level Vision to Monitor Them

MCP tool use creates massive application-layer blind spots. Close the gap by monitoring agent behavior directly in the kernel space.

August 11, 2026

by Ammar Ekbote

· 2,068 Views · 1 Like

How We Built an LLM Pipeline That Survives Traffic Spikes

A traffic spike took down our LLM summarizer. Here is the severity-routing + token-governor design that keeps it alive. Plan in tokens, not requests.

August 10, 2026

by Dileep Mundakkapatta

· 1,848 Views · 1 Like

Building an AI-Powered Incident Triage Agent with .NET Aspire

A practical, code-driven tutorial on building an AI-powered incident triage agent using .NET 10 and .NET Aspire 9, and other modern tools.

August 10, 2026

by Muhammad Asif Nawaz

· 2,602 Views · 1 Like

Agentic AI in 2026: How Autonomous AI Agents Are Replacing Manual Dev Work

Autonomous AI agents are moving from demos to production in 2026. See how agentic AI, MCP, and multi-agent systems are changing dev workflows.

August 10, 2026

by Ghulam Ghous

· 1,634 Views · 1 Like

GraphQL Isn’t Dead Yet, AI Agents Revived It

GraphQL was good at a time, then it simmered off. Is GraphQL about to make a comeback because of AI? Will GraphQL be able to serve better for AI Agents?

August 10, 2026

by Akash Lomas

· 1,378 Views · 2 Likes

A Practical Pipeline for Identifying Sensitive Columns Before Test Data Masking

In this article, I will be introducing a pipeline designed to identify sensitive data columns before masking steps and improve the efficiency of the data masking process.

August 10, 2026

by Siyuan Feng

· 1,596 Views

How We Cut PyFlink Pipeline p99 Latency from 3-5 Seconds to ~500ms

We eliminated per-record Python-side Protobuf parsing and JVM-to-Python crossings by letting Flink's native Protobuf format decode records directly into typed columns.

August 7, 2026

by Arjun Shah

· 3,068 Views · 1 Like

Orchestration Meets MCP: Building Governed Agentic Workflows With Quarkus Flow and AGENTS.md

By combining Quarkus Flow, LangChain4j, MCP tools, and AGENTS.md, developers can construct deterministic, tool-augmented, and enterprise-governed AI agent loops.

August 7, 2026

by Daniel Oh

CORE

· 2,878 Views

How RAG Cuts Hallucinations in Generative AI Chatbots

RAG cuts chatbot hallucinations by grounding answers in retrieved source data, not model memory. Retrieval quality and evaluation matter more than model size.

August 6, 2026

by Paul Schloss

· 1,904 Views

The Latest Popular Topics