Real solutions to real problems. No fluff, no SEO spam—just useful stuff I've learned the hard way so you don't have to.
After enough Data Center to Cloud migrations, you develop an instinct for when things are about to go sideways. It's never the core data — Jira issues, Confluence pages, user accounts — that breaks the project. It's the apps. Specifically, it's the moment you realize the vendor doesn't have an answer either, and your client's deadline doesn't care.
JSM's native portal is functional enough for agents — but for the people filing requests, it's a friction-first experience that drives tickets up, not down. Refined Sites fixes the part your requesters actually see. Here's what you gain, what stays broken, and when the investment earns its keep.
Every workflow validator on the Atlassian Marketplace requires scripting. Every AI app for Jira is an assistant that can’t block a transition. CogniRunner sits in the gap between those two worlds — plain-English prompts that evaluate Jira field content, including attachments, as a real-time workflow gate.
After 10+ Data Center to Cloud migrations, here's what nobody tells you: they're imperfect by necessity, not by design. Waiting for perfection is the single most expensive mistake an organization can make — and I've watched it happen in real time.
Atlassian Cloud replaces Cloudflare with a fully managed AWS-native security stack — Amazon CloudFront for CDN, AWS WAF for application-layer firewalling, and AWS Shield Advanced for DDoS protection. The stack is enterprise-grade and battle-tested, but you can't touch it. This post maps every Cloudflare capability to its Atlassian Cloud equivalent, details the gaps your security team needs to plan for, and gives you the honest technical assessment for your Data Center migration.
A deep dive into Qwen3-Coder-Next, the 80B MoE model that brings powerful local development within reach. Learn why this 2026 release matters for developers who value control, predictability, and consistent results.
A systematic approach to controlling how AI agents behave when working on software projects. Addresses the fundamental problem that AI models are unpredictable by default.
Autonomous AI agents are impressive, but their "helpfulness" often leads to unauthorized changes. After Claude Code silently removed rate limiters and rewrote my email templates, I found a more reliable alternative in the Zed Editor paired with GLM-4.7. Description: A technical deep-dive into the risks of "Vibe Coding" and AI overreach. This post analyzes a real-world incident where an autonomous agent broke production features while fixing bugs, and explores why the strict instruction-following capabilities of Zhipu's GLM-4.7 model inside the Zed editor offer a safer, more deterministic workflow for serious engineering.
Discover how the MCP Document Processor helps AI agents work with document formats more effectively. This Model Context Protocol server provides tools for reading PDFs with OCR and creating DOCX and Excel files. Tested with Qwen3-8b-VL for vision processing and GLM-4.7-REAP for cloud models, it handles document structure, table extraction, and professional document generation with practical styling options.