Video editing is now a collaboration between humans and AI. This collaboration lets creators scale production faster and cheaper without losing the soul of their work.
Egress — not compute — drives surprise cloud costs. Fix it by designing for data locality, using compression/caching wisely, and actively monitoring data flows.
Building with LLMs in 2026 means more than picking a model and calling an API. This article covers the full open-source stack by defining tools and their usage.
April 28, 2026
by Vidyasagar (Sarath Chandra) Machupalli FBCS
CORE
A startup builds API security from day one using identity, mTLS, validation, and automation — embedding defenses into architecture instead of reacting after failures.
This guide shows how to build a secure CI/CD pipeline with early scanning, policy-as-code, SBOMs, zero trust, and safe AI-driven remediation in DevSecOps.
AI is erasing tech’s age bias by boosting older workers’ speed and amplifying their experience—making them more productive, reliable, and valuable than ever.
This article explores a practical and resilient design pattern that addresses this problem by embracing asynchronous processing and eventual consistency.
Benchmarks test success. Production tests failure. Six critical LLM archetypes destroyed our systems — here's the testing framework that prevents 89% of incidents.
AI-driven development expands attack surfaces; this article shows how continuous security, zero trust, and runtime enforcement scale DevSecOps in AI pipelines
Detect APTs with behavioral analytics and log correlation, building baselines and linking events to turn weak signals into actionable security detections.