Exploring how artificial intelligence is evolving from a collection of tools into foundational cognitive infrastructure that fundamentally shapes how we think, decide, and understand reality in the digital age.

Discover how Claude-Flow transforms software development with AI swarm intelligence, achieving 84.8% SWE-Bench solve rates and 4.4x speed improvements through intelligent agent orchestration

The ongoing saga of turning my standards repository into an MCP server. Spoiler: It's working, mostly, and I've only rewritten it three times.

How I built a comprehensive standards repository that transforms Claude CLI into a context-aware development powerhouse with 90% token reduction.

Lessons learned from running LLMs and AI experiments at home while keeping data and systems secure

The first time I watched an AI analyze a screenshot and write working code based on the UI mockup, I realized we'd crossed into a new era of human-AI collaboration

Understanding how context window limitations influence LLM performance and the innovative approaches being developed to handle long-form content, from document analysis to extended conversations.

Evaluating how LLMs are transforming smart contract vulnerability detection, their current capabilities versus traditional tools, and the most promising approaches for improving blockchain security.

Running large language models on a raspberry pi cluster taught me more about efficiency and ingenuity than years of unlimited cloud computing budgets ever could

How the convergence of artificial intelligence and edge computing is creating responsive, private, and resilient systems that process data where it's generated, revolutionizing applications from autonomous vehicles to smart manufacturing.

Watching AI catch an APT attack that our traditional tools missed was thrilling - until I realized the same technology could automate sophisticated attacks against us

Exploring how engineers are drawing inspiration from billions of years of evolution to create more capable, efficient, and adaptable robotic systems that solve complex real-world challenges.

How multimodal large language models are learning to recognize ambiguity and ask clarifying questions, making robots better collaborative partners in real-world scenarios.

My first attempts at prompt engineering felt like trying to teach a brilliant but scatterbrained colleague - discovering the right words to unlock AI capabilities became both art and science

Deploying our first customer-facing LLM felt like releasing something powerful into the wild - the biases, mistakes, and unintended consequences that followed taught me why AI ethics isn't optional

How HPC systems are transforming from pure performance machines to intelligent, sustainable platforms that combine AI acceleration with innovative cooling and energy management.

The moment I realized our LLM was confidently making up facts about our company's products was when I understood why RAG isn't optional - it's essential for trustworthy AI systems

Reading 'Attention is All You Need' felt like discovering a secret that would reshape everything I thought I knew about natural language processing - and it did

After months of experimenting with both approaches in production systems, I've learned that choosing between open-source and proprietary LLMs isn't about ideology - it's about trade-offs

The first time I saw a convincing deepfake video, I spent an hour researching to convince myself it wasn't real - that moment changed how I think about digital evidence forever