✨ What you'll learn (tl;dr) In ~12 minutes you'll see how to deploy Microsoft's BitNet 1.58-bit quantized LLM on AWS Lambda, the container-based architecture, and performance benchmarks across different memory configurations using the microsoft/bitnet-b1.58-2B-4T model.

Big idea: 1.58-bit quantization enables LLM deployment on Lambda's CPU infrastructure. At ~1.1GB, the model fits within Lambda's constraints for serverless AI inference.

As large language models (LLMs) evolve from passive responders into autonomous agents that can reason, plan, and act—welcome to the age of Agentic AI. These systems don't just generate answers; they browse the web, execute scripts, send emails, and even orchestrate other agents. And with that autonomy comes an entirely new class of cybersecurity threats.

The OWASP Agentic AI: Threats and Mitigations report is the first of its kind to lay out a structured threat model tailored to the unique risks introduced by LLM-powered agents. From memory poisoning and cascading hallucinations to identity spoofing and rogue agents—this is the new frontline of AI security.

✨ What you'll learn (tl;dr) In ~8 minutes you'll see why most data‑governance efforts stall, how to turn governance into load‑bearing scaffolding, and the exact roadmap, roles, and rituals that move you from ad‑hoc chaos to self‑sustaining confidence—without freezing delivery.

Big idea: Data governance isn't red tape; it's the scaffolding that lets strategic initiatives—from AI to customer experience—scale safely and evolve fast. Bake lightweight governance into culture, rituals, and engineering workflows so raw data turns into durable business value without slowing delivery.

Introduction​

In an age where digital transformation is more than just a buzzword, achieving optimum operational efficiency has become a vital focus for businesses. Companies striving to evolve and stay ahead often encounter the phenomenon of a 'Digital Standstill'—a term referring to the stagnation in innovation and development caused by accumulating technical debt.

In this article, I intend to shed light on how the Theory of Constraints can provide a systematic approach to overcoming the challenge posed by technical debt.

Technological realm is always changing, and organizations must constantly navigate through turbulent waves and shifting currents. The compass guiding many on this voyage has been the Centers of Excellence (COE). But is the COE an eternal beacon, or does it have its sunset?

Achieving sustained growth is the ultimate dream for many businesses, but how to realize that dream is often elusive. One proven way is to leverage the "flywheel effect," a concept that advocates for creating a self-perpetuating growth cycle through customer satisfaction and word-of-mouth referrals. And as we move further into the age of AI, the potential for supercharging your flywheel becomes even more palpable. Here's a look at how incorporating Generative AI into your flywheel model can boost your business.