Agentic AI in 2026: The Year Agents Stopped Being a Demo
Agentic AI went from cool demos to real production workflows in 2026. Multi-agent orchestration, terminal-based agents, and what is still broken.
My AI Agents Struggle with Reliability (March 2026)
Hey everyone, Alex here from agntai.net. It’s March 2026, and I’ve been wrestling with something that I think a lot of you working with AI agents are probably feeling too: the sheer complexity of making these things actually work reliably in the wild. We’re past the “cool demo” phase for a lot of agentic systems.
My AI Agent Debugging: Misplaced Commas & Existential Crises
Hey there, AgntAI.net crew! Alex Petrov here, fresh off a truly baffling debugging session that reminded me just how much we’re still figuring out in the world of AI agents. You know, the kind of session where you’re staring at logs, convinced your agent is having an existential crisis, only to find a misplaced comma
Agent Evaluation Done Right: Practical Tips and Rants
The Tale of Frustration: Evaluating Agents Blindly
Oh, the stories I could tell you about agent evaluation gone wrong! I once spent close to three weeks trying to assess an agent’s performance using metrics that ended up being as useful as a wooden spoon in a bar fight. Imagine having your agent score 95% in
Advanced AI Architecture: Neural Network Optimization 2026
Explore cutting-edge neural network optimization techniques shaping AI architecture in 2026. Discover advanced optimizers, hardware-aware methods, AutoML, and federated learning strategies.
Optimizing AI Architecture: Neural Net Techniques for 2026
Explore cutting-edge neural network optimization techniques shaping AI architecture in 2026. Dive into advanced quantization, federated learning, and hardware-aware NAS.
ML Engineering Best Practices: Building Robust AI Systems
Learn essential ML engineering best practices for building, deploying, and maintaining production AI systems. Optimize pipelines, data, and models for reliability and scale.
Transformer Architecture Deep Dive: ML Engineering Insights
Explore the Transformer architecture’s core mechanics, from self-attention to practical engineering challenges. A deep dive for ML engineers building advanced AI systems.
RAG Systems in ML: The Good, The Bad, and The Ugly
The Time I Wanted to Throw My Laptop
You ever had one of those days where everything goes south, and you think you’re living in some twisted universe where tech creators laugh at your misery? That’s how I felt when I first deployed a RAG system. Let me tell you, RAG, or Retrieval-Augmented Generation, has