In a talk at PlatformCon, author Camille Fournier shared common platform engineering mistakes she sees and how to avoid them.

The authors also flag a recurring issue: while AI models can often generate syntactically correct code snippets, they frequently lack a semantic understanding of the overall software architecture.

CoLab, a company helping engineering teams run more consistent design reviews, has released a new AI tool - AutoReview.

Building modularity early via microservices or well-defined domains within a monolith supports scalability. For fintechs ...

What’s needed is a “paved road” for agent connectivity: infrastructure that handles tool authentication, rate-limiting and monitoring consistently across all agent tools. This lets developers focus on ...

Key Takeaways Tech firms now hire based on skills, not degrees.Portfolios, coding challenges, and GitHub matter most to ...

Vijay Kumar Soni, a digital payments expert, integrates engineering and AI to build secure, scalable financial platforms. His ...

Google Cloud's innovative Cloud Storage bucket relocation feature enables seamless, non-disruptive data migration across ...

Experts from Universal Robots and OnRobot offer insights into how to select versatile end-of-arm robot tools that work ...

Moving to the cloud isn’t just about new technology—it’s about redefining the engineering workflows that drive modern product ...

Sigmetrix champions early-stage tolerance analysis to help engineers create manufacturable, high performance products without ...

Traditional vibration analysis falls short for slow-speed machinery. Augury’s AI-powered platform uses high-frequency ...