The Latest and Popular SDLC Topics

Spec-Driven Integration: Turning API Sprawl Into a Governed Capability Fleet for AI

Alpha release of a new integration approach that translates your existing data and APIs into standardized APIs, MCP, and agent skills for AI.

May 13, 2026

by Kin Lane

· 1,970 Views

How to Build and Optimize AI Models for Real-World Applications

Building effective AI models for real-world applications requires clear problem definition, quality data, the right algorithms, continuous testing, and optimization.

May 13, 2026

by Mitchell Jhonson

· 1,594 Views

How to Test a PATCH API Request With REST-Assured Java

This tutorial demonstrates how to test PATCH requests using REST Assured in Java for API testing, including examples of partial data updates.

May 13, 2026

by Faisal Khatri

CORE

· 5,008 Views

LLM Integration in Enterprise Applications: A Practical Guide

LLM integration boosts efficiency, automates workflows, and sharpens decisions — but success hinges on strategy, execution, and business alignment.

May 13, 2026

by Lilly Gracia

· 2,339 Views

Solving the Mystery: Why Java RSS Grows in Docker on M1 Macs

Java apps running in x86-64 Docker containers on ARM64 M1 Macs experience mysterious RSS memory growth due to Rosetta 2 translation cache. The culprit? JIT compilation.

May 12, 2026

by Sumeet Sharma

· 4,212 Views · 1 Like

The Art of Token Frugality in Generative AI Applications

Trim your prompts, cache aggressively, route simple queries to smaller models, constrain your outputs, and swap JSON for TOON to lower token bills.

May 12, 2026

by Sibanjan Das

· 3,020 Views

Has AI-Generated SQL Impacted Data Quality? We Reviewed 1,000 Incidents

We analyzed 1,000 data pipeline incidents across 500+ environments and found that code-related failures still account for ~10% of all data quality issues.

May 12, 2026

by Lior Gavish

· 3,053 Views

Code Quality Had 5 Pillars. AI Broke 3 and Created 2 We Can’t Measure

AI-generated code broke three of the five classical non-functional quality pillars — readability, maintainability, and security — while creating two new dimensions

May 12, 2026

by Abgar Simonean

· 3,571 Views · 3 Likes

You Secured the Code. Did You Secure the Model?

AppSec focuses only on code, leaving AI supply chains exposed. Effective security embeds AI checks into workflows, scanning PRs and AI components continuously.

May 12, 2026

by Eran Kinsbruner

· 2,142 Views

Scalable Support Request Analysis Using Embeddings, HDBSCAN, and Tiny LLMs

Effective use of historical data to classify support requests into buckets and identify emerging or slightly different patterns.

May 12, 2026

by Jijo Puthalath

· 1,558 Views

AI in Software Development: A Mirror, Not a Magic Wand

AI doesn’t replace engineering discipline; it amplifies it. Used carefully, AI speeds up good design and clean code; used carelessly, it accelerates technical debt.

May 11, 2026

by Jonathan Dodd

· 2,967 Views · 5 Likes

AI-Driven Integration in Large-Scale Agile Environments

Learn how AI integrates with Agile at scale, improving velocity and insights while requiring human oversight, bias control, and continuous feedback.

May 11, 2026

by Abhijit Roy

· 3,386 Views · 2 Likes

Stop Using Python for Your GenAI Apps, Use Go and Genkit Instead

Python has dominated the GenAI conversation, but it is neither the only nor the best option for production. Here is why Go is a stronger bet.

May 11, 2026

by Xavier Portilla Edo

CORE

· 2,266 Views · 1 Like

How to Effectively Evaluate a Ranking ML System

Evaluating ranking systems requires more than offline metrics. Learn how to use offline, online, and business metrics to measure real impact.

May 11, 2026

by Muthukumaran Vaithianathan

· 2,671 Views

Hallucination Has Real Consequences — Lessons From Building AI Systems

This article explains why hallucinations happen, the types, and practical ways to reduce them using RAG, low temperature, guardrails, and validation layers.

May 11, 2026

by Ram Ghadiyaram

CORE

· 3,054 Views · 2 Likes

Improving Java Application Reliability with Dynatrace AI Engine

Leverage Dynatrace’s AI-powered observability to automatically detect anomalies, pinpoint root causes, and prevent performance issues in Java applications.

May 11, 2026

by Ramya vani Rayala

· 2,377 Views · 1 Like

Building a Production-Ready AI Agent in 2026: Beyond the Hello World Demo

Stop treating AI agents like prompts — treat them like software. To ship in 2026: validated tool contracts, tiered memory, RAG grounding, and deep observability.

May 8, 2026

by Nikita Kothari

· 4,111 Views · 2 Likes