Author name: Marcelo Acosta

AWS June Mid-Month Update: FinOps, AI, and Infrastructure Enhancements The first half of June 2025 has delivered a substantial wave of AWS updates across multiple service categories. From enhanced FinOps capabilities to expanded AI tooling and global infrastructure growth, these announcements demonstrate AWS’s commitment to addressing real-world enterprise challenges while preparing for the upcoming re:Inforce […]

Meta has unveiled V-JEPA 2, a significant advancement in world modeling that brings us closer to artificial intelligence systems capable of understanding and reasoning about the physical world. This 1.2 billion-parameter model represents a crucial step toward achieving advanced machine intelligence (AMI) and building AI agents that can operate effectively in real-world environments. The release

Software development has fundamentally shifted with sophisticated AI coding assistants like Claude. What started as a meme has evolved into a legitimate development methodology that can deliver genuine 10x productivity improvements when applied correctly. But like any powerful tool, the difference between success and disaster lies in how you wield it. This post is heavily

AWS has rolled out significant updates across multiple service categories since early May 2025. These developments focus on enhanced AI capabilities, expanded regional availability, and improved developer productivity tools. AI and Machine Learning Enhancements Amazon Bedrock continues expanding its AI capabilities with Model Distillation now generally available, supporting Amazon Nova Premier as teacher models and

Why do some RAG (Retrieval-Augmented Generation) systems deliver precise, contextualized answers while others return irrelevant or even fabricated information? The difference isn’t just in data quality or the language model used. After analyzing numerous RAG implementations in enterprise environments, I’ve identified a clearly defined maturity scale. Systems that truly generate value don’t simply connect an

That’s a wrap on Interrupt 2025! This year, 800 folks from across the globe gathered in San Francisco for LangChain’s first industry conference to hear stories of teams building agents – and the energy was incredible. Major companies including Cisco, Uber, Replit, LinkedIn, Blackrock, JPMorgan, and Harvey shared lessons on architectures, evaluations, observability, and prompting

Staff engineers are increasingly encouraged to adopt AI tools, but much of the discussion focuses on basic code generation. This post explores how staff engineers can use Cursor to tackle real engineering challenges and automate tedious tasks that consume valuable time. A Three-Step Framework for Using Cursor Explore: Share context about the problem and gather

Google Cloud’s latest report shows that businesses are moving beyond just experimenting with AI – they’re now using it to solve real problems. This shift creates new opportunities for startups that can build practical solutions. Let’s look at what the report tells us about these opportunities. Where We Are Now Businesses of all sizes are

The tech world has been buzzing about MCPs (Machine Conversation Protocol), but beneath the viral discussions lies a fundamental shift in how AI assistants interact with the world around them. This isn’t just another technical buzzword – it’s a potential game-changer in how we build and use AI systems. The Evolution of AI Assistants The

Implementar un modelo de machine learning (ML) en un Jupyter Notebook o un entorno local es solo el comienzo. El verdadero desafío comienza al llevar ese sistema a producción, donde debe ser robusto, escalable y mantenible en el tiempo. El conjunto de prácticas conocido como MLOps (Machine Learning Operations) abarca todos los pasos necesarios para