Subscribe • Previous Issues Agents at Work: Navigating Promise, Reality, and Risks Agents are top of mind for people working in AI. Still, when I talk to professionals building AI applications, many express frustration, highlighting the gap between the intense interest in agents and their relatively limited presence in live enterprise environments. Part of this skepticism isContinue reading “Real-World Lessons from Agentic AI Deployments”
Category Archives: Uncategorized
Beyond the Hype: The Reality Gap in Multi-Agent Systems
The allure of multi-agent systems (MAS), where teams of LLM-based agents collaborate, is undeniable for tackling complex tasks. The theoretical benefits seem clear: breaking down problems, parallelizing work, and leveraging specialized skills promise more sophisticated AI solutions than single agents can deliver. Yet as teams building these systems are discovering, translating this promise into reliableContinue reading “Beyond the Hype: The Reality Gap in Multi-Agent Systems”
Google’s AI Revival
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Why Your Multi-Agent AI Keeps Failing
Subscribe • Previous Issues Beyond the Hype: The Reality Gap in Multi-Agent Systems The allure of multi-agent systems (MAS), where teams of LLM-based agents collaborate, is undeniable for tackling complex tasks. The theoretical benefits seem clear: breaking down problems, parallelizing work, and leveraging specialized skills promise more sophisticated AI solutions than single agents can deliver. Yet asContinue reading “Why Your Multi-Agent AI Keeps Failing”
Model Context Protocol: What You Need To Know
Table of Contents Understanding MCP Basics What is the Model Context Protocol (MCP)? What fundamental problems does MCP aim to solve? Why are these context management problems significant for AI applications? Can you provide a concrete example of how context fragmentation affects AI applications? Current Approaches and Their Limitations What methods do developers currently useContinue reading “Model Context Protocol: What You Need To Know”
Choosing the Right AI Model: Performance, Cost, and Task Specificity
In building AI applications and solutions, three best practices have clearly emerged. First, design your system to remain agnostic about the model provider. Given the steady stream of highly capable models from proprietary vendors like OpenAI, Anthropic, and DeepMind, as well as open-weight providers such as Meta, DeepSeek, and Alibaba. Second, prepare to further customizeContinue reading “Choosing the Right AI Model: Performance, Cost, and Task Specificity”
The AI Model Selection Mistakes You Can’t Afford to Make
Subscribe • Previous Issues Choosing the Right AI Model: Performance, Cost, and Task Specificity In building AI applications and solutions, three best practices have clearly emerged. First, design your system to remain agnostic about the model provider. Given the steady stream of highly capable models from proprietary vendors like OpenAI, Anthropic, and DeepMind, as well as open-weightContinue reading “The AI Model Selection Mistakes You Can’t Afford to Make”
An In-Depth Look at the Stanford AI Index Report
The Stanford AI Index Report 2025 provides the most comprehensive, data-driven overview of artificial intelligence trends globally. I consider it essential annual reading to stay grounded in the actual progress and impact of AI, tracking everything from technical benchmarks to policy shifts. I recently had the chance to discuss the latest findings with Nestor Maslej,Continue reading “An In-Depth Look at the Stanford AI Index Report”
The State of AI in 2025
Subscribe • Previous Issues An In-Depth Look at the Stanford AI Index Report The Stanford AI Index Report 2025 provides the most comprehensive, data-driven overview of artificial intelligence trends globally. I consider it essential annual reading to stay grounded in the actual progress and impact of AI, tracking everything from technical benchmarks to policy shifts. I recentlyContinue reading “The State of AI in 2025”
Llama 4: What You Need to Know
Table of Contents Model Overview and Specifications What is the Llama 4 model family and what models are included? What is the Mixture-of-Experts (MoE) architecture used in Llama 4? How are the Llama 4 models multimodal? Performance and Benchmarks How do Llama 4 models perform compared to other leading models? Are current benchmarks adequate forContinue reading “Llama 4: What You Need to Know”