Latest Articles

Working with Cowork: Claude Desktop is three applications pretending to be one. In this article, see the tables of what is shared.

May 14, 2026

by Stefan Wolpers

CORE

· 2,486 Views

Ten Years of Beam: From Google's Dataflow Paper to 4 Trillion Events at LinkedIn

Apache Beam turns ten. From Google's 2015 Dataflow paper to 4 trillion daily events at LinkedIn — what it got right, where it falls short, and what comes next.

May 14, 2026

by Abgar Simonean

· 1,547 Views

Lease Coordination Under Serializable Isolation in CockroachDB

Designing scalable lease coordination in CockroachDB, focusing on key distribution, concurrency, and reducing transaction conflicts in multi-region systems.

May 14, 2026

by Nishant Jain

· 1,505 Views

AI Agents Expose a Design Gap in Microservices Resilience Architecture

Microservices assume predictable callers. AI agents break this with non-deterministic calls, fan-out, and retries. Here are 5 core assumption breaks and fixes.

May 13, 2026

by Vineet Bhatkoti

· 3,877 Views · 1 Like

Readiness Is All You Need

AI work now hinges on reading, not prompting. Those who carefully read and question outputs outperform those who accept polished but flawed results.

May 13, 2026

by Nacho Corcuera

· 1,606 Views · 1 Like

Navigating the Complexities of AI-Driven Integration in Multi-Cloud Environments: A Veteran’s Insights

AI is transforming multi-cloud integration with real-time, decentralized, secure systems — improving compliance, APIs, and scalability across industries.

May 13, 2026

by Abhijit Roy

· 2,397 Views · 1 Like

You Learned AI. So Why Are You Still Not Getting Hired?

Most AI job seekers learn tools. Employers hire people who can specify tasks, evaluate outputs, manage risk, and deliver real business value with AI.

May 13, 2026

by Faisal Feroz

· 5,138 Views · 3 Likes

Stop Using the ATM-Didn’t-Kill-Jobs Story to Reassure Developers About AI

The ATM didn’t kill bank tellers’ jobs — the iPhone did. Getting the history right isn’t reassuring; it clarifies why developers should pay attention.

May 13, 2026

by Thomas Johnson

CORE

· 3,361 Views

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

· 1,766 Views

AWS Kiro: The Agentic IDE That Makes Specs the Unit of Work

You describe a feature, and Kiro generates structured requirements.md, design.md, and tasks.md files first, then implements against them.

May 13, 2026

by Jubin Abhishek Soni

CORE

· 2,924 Views · 2 Likes

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

· 1,428 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

· 3,846 Views

The Cost of Knowing: When Observability Becomes the Outage

Observability costs spiral when teams optimize for visibility, not cost. Fix it by making spend visible, sampling aggressively, and cutting low-value data.

May 13, 2026

by David Iyanu Jonathan

· 1,322 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

· 1,933 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

· 3,694 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

· 2,178 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

· 2,667 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

· 2,703 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

· 1,917 Views

The 7 Pillars of Meeting Design: Transforming Expensive Conversations into Decision Assets

Most meetings waste engineering time, increase latency, and break focus. The 7 Pillars of Meeting Design help teams create efficient, outcome-driven decisions.

May 12, 2026

by Otavio Santana

CORE

· 2,334 Views

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