Perspectives on software engineering, AI, cloud infrastructure, and the tech events shaping our industry.
IoT2026-04-285 min readFeatured
LoRa's Silent Revolution: Why Engineers Are Ditching Cellular for Long-Range IoT
LoRa networks are solving real infrastructure problems where cellular fails. Here's why enterprises are quietly building the next layer of IoT connectivity.
Public Safety Answering Points are drowning in call volume and misrouted emergencies. AI call classification can cut response times by 30% while reducing dispatcher burnout.
Moving from 2D to 3D UI design requires more than scaled-up buttons. Learn the critical mistakes designers make and how spatial thinking changes everything.
Why Your ML Pipeline Fails in Production (And How to Fix It)
Model accuracy means nothing if your pipeline crashes at scale. We'll show you the exact monitoring gaps most teams miss and how to catch them before users do.
Why Your ML Pipeline Fails in Production (And How to Fix It)
Data drift, dependency hell, and silent model degradation sink more ML projects than bad algorithms ever will. Here's what actually matters in production.
Enterprise AR That Pays: Real ROI Cases From Today
AR isn't theoretical anymore. Manufacturing, logistics, and field service teams are seeing measurable returns right now. Here's what's actually working.
WebXR has moved past proof-of-concept. Native browser support for AR is solid, APIs are stable, and companies are shipping real experiences. Here's what changed.
Performance Budgets for VR: Hitting 90fps or Paying the Sickness Tax
Miss your framerate target in VR and users won't just experience lag—they'll experience nausea. Here's how to build and enforce performance budgets that keep your VR app smooth.
Photogrammetry for AR: Capturing Real Objects for Mixed Reality
Learn how photogrammetry transforms physical objects into digital 3D models for AR applications. We cover capture techniques, processing workflows, and integration strategies.
Running ML Models on Microcontrollers: TinyML Essentials
Deploy trained ML models directly to resource-constrained devices. Learn the practical workflow for TinyML, from model quantization to firmware integration.