Subscribe • Previous Issues Your AI Cheat Sheet: Manus, Gemma 3, OpenAI, and Global Regulations Feeling overwhelmed by the pace of AI developments? Our latest collection of guides and cheat sheets covers everything from China’s groundbreaking Manus agent to Google’s Gemma 3 and the evolving regulatory landscape across major economies. Catch up on a transformative week inContinue reading “AI This Week: New Agents, Open Models, and the Race for Productivity”
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From Prototype Purgatory to Production-Grade AI Agents
Subscribe • Previous Issues Taming the Wild West of AI Agents: Addressing the Challenges of Real-World Deployment AI agents are autonomous systems that combine language (and multimodal) understanding with the decision-making prowess of foundation models to interpret complex inputs, reason through multifaceted scenarios, and execute tasks autonomously. The business landscape is abuzz with excitement, as industry analystsContinue reading “From Prototype Purgatory to Production-Grade AI Agents”
Boost AI Performance: Understanding Inference Scaling
Subscribe • Previous Issues Decoding Inference Scaling: The Dawn of Reasoning-Driven AI Inference scaling, also known as inference-time compute, is the strategic allocation of computational resources during the operational phase of AI models. With the rise of reasoning-enhanced Large Language Models (LLMs) and foundation models, inference scaling has become even more crucial. These models leverage additional computeContinue reading “Boost AI Performance: Understanding Inference Scaling”
10 Things to Know About the State of AI Agents
Subscribe • Previous Issues AI Agents: 10 Key Areas You Need to Understand 1. GUI-Based Interaction AI agents (that rely on foundation models) increasingly interact with software through graphical user interfaces (GUIs), much like a human using mouse and keyboard inputs. This is in contrast to older approaches limited to bespoke or specialized APIs. Frameworks like OpenAIContinue reading “10 Things to Know About the State of AI Agents”
Is Your AI Missing Out? The Hidden Logic in Your Spreadsheets
Subscribe • Previous Issues AI’s Spreadsheet Blind Spot: Bridging the Logic Gap In a previous article, I highlighted the need for AI applications to bridge the gap between their advanced capabilities and the real-time data that businesses depend on. However, for AI to truly transform business workflows, it must also tap into one of the most enduringContinue reading “Is Your AI Missing Out? The Hidden Logic in Your Spreadsheets”
AI in 2025: Don’t Miss These Key Trends
Subscribe • Previous Issues What AI Teams Need to Know for 2025 I’ve been watching the AI landscape closely, and I’m convinced that 2025 will be a pivotal year. We’re moving beyond the hype and into a phase of real, tangible impact. This list isn’t just about what’s happening; it’s about what’s next. Generative AI for EnterpriseContinue reading “AI in 2025: Don’t Miss These Key Trends”
The Real Story of AI in Code
Subscribe • Previous Issues The Rise of the AI-Powered Developer Even at this stage in AI’s evolution, it’s not uncommon to encounter skepticism, with some viewing it as little more than “spicy autocomplete” – an overhyped technology with limited lasting impact. Let’s be honest: the ‘spicy autocomplete’ label for AI in software development is not just lazy,Continue reading “The Real Story of AI in Code”
Empowering AI Agents with Real-Time Data
Subscribe • Previous Issues Building Better AI Agents Through Real-Time Data Access In my previous post, I explored how the Generative AI era is upending traditional data processing paradigms—shifting us from the familiar terrain of SQL-centric systems into AI-centric tools, where unstructured, multimodal data reigns supreme. While the buzz surrounds unstructured data formats like sales calls, PDFs,Continue reading “Empowering AI Agents with Real-Time Data”
Paradigm Shifts in Data Processing for the Generative AI Era
Subscribe • Previous Issues Bridging the Gap: Multimodal Data Processing for Generative AI By Ben Lorica and Dean Wampler. In the rapidly evolving landscape of Generative AI, one of the most critical, yet often underestimated challenges is data processing and preparation. While models have become more sophisticated, the data pipelines feeding them have not kept pace, especiallyContinue reading “Paradigm Shifts in Data Processing for the Generative AI Era”
Structured Prompt Engineering Made Easy
Subscribe • Previous Issues Seven Features That Make BAML Ideal for AI Developers Technical teams building AI applications with large language models (LLMs) face significant challenges in managing and scaling their projects. One major issue is the lack of rigor and structure in prompt engineering. Developers often embed prompts directly into code as simple strings or JSONContinue reading “Structured Prompt Engineering Made Easy”