Learn how to avoid the “Bag of Agents” trap and scale Multi-Agent Systems effectively. Based on DeepMind’s research, discover why coordination structure matters more than agent quantity and how to suppress 17x error amplification using functional planes and a centralized orchestrator for robust, performant agentic AI.
Stop treating LLMs like a magic 8-ball. To achieve a 5x coding performance boost, you must transition from Zero-Shot to Few-Shot Prompting. By providing your AI agent with specific code examples and context, you eliminate ambiguity, prevent hallucinations, and ensure production-ready results that follow your exact architectural standards.
Stop treating AI prompts like static code. Ahmad Wael explores Context Engineering and the Agentic Context Engineering (ACE) framework—a Stanford-led research breakthrough that uses Generator, Reflector, and Curator agents to create self-improving LLM workflows. Learn how to bridge the gap between AI theory and WordPress production.
Stop blaming the LLM for your broken agentic pipelines. Senior WordPress developer Ahmad Wael explains why messy MCP tool descriptions cause model bias and how to fix it using the “hiding arguments” pattern and proxy servers like Master-MCP. Learn to build robust AI integrations without overspending on expensive models.
Stop wasting time on prompt engineering that fails. Ahmad Wael explains why Agentic AI workflows require a graph-based architecture to succeed. Learn how to use IntelliNode and Vibe Agents to turn high-level intent into executable, observable task sequences that prevent hallucinations and scale across enterprise systems. Build smarter, not harder.
Stop building fragile AI demos. I’ll show you how to use Nvidia’s NeMo Agent Toolkit to build reliable, production-ready LLM agents. Learn to solve ‘day 2’ problems like observability and deployment for your AI projects. Get your integrations working without hallucinations or timeouts.
Mastering Effective AI Programming requires moving beyond simple prompts. Learn how to provide strict technical context, use Markdown schema files, and bridge the gap between oral meetings and AI coding agents to eliminate hallucinations and save thousands of tokens on your next WordPress or WooCommerce development project.
Agentic AI systems are great for making decisions, but they often fail traditional medical metrics like AUC. In this post, I break down why binary outputs are a nightmare for risk ranking and share 6 senior-level strategies for deriving continuous scores from your AI agents to ensure fair model comparisons.
Choosing between an AI Engineer vs Machine Learning Engineer is a critical decision for your project. One integrates powerful pre-built models, while the other builds custom algorithms from scratch. Ahmad Wael breaks down the technical differences, the skill sets involved, and how to avoid the “prestige hiring” trap that wastes budget and time.
I had a client last year—big site, tons of custom data. They wanted an AI assistant that didn’t just “answer questions” but could actually check…