The Infrastructure That Outlives the Technology
A look at why the durable infrastructure beneath AI may matter more over time than the fast-changing technologies built on top of it.
Articles
The Skills We Keep
A reflection on how AI changes the practice that builds technical judgment, and why the skills worth keeping need to be protected deliberately.
Your Software Has New Users
Enterprise software is entering a new era where it must support not just human users, but agents that can participate directly in work.
A Different Lens on LLM Reasoning
A different lens on LLM reasoning. Intelligence may scale with internal computation depth, not just longer chains of thought.
What Happens After Tokens Get Cheap
When tokens get cheap, competition shifts from production economics to systems thinking.
Thinking Clearly About AI and the Economy
A practical mental model for leaders trying to understand how AI may show up in the broader economy over time.
A Shift in How We Build Software with AI
For technology leaders: why AI coding agents demand a new engineering control model and how specification-driven development enables scale.
Building Teams Around the Analyst - Agent Pair
Analyst-Agent Pair for modern teams: practical patterns for agentic workflows with evaluations, observability, and guardrails.
Practical Memory Patterns for Reliable, Longer-Horizon Agent Workflows
Memory Design for AI Agents: a practical guide to working, episodic, semantic, procedural, and preference memory—with patterns and evaluation tips.
The Agentic Shift in Knowledge Work
Agentic AI is moving from prompts to outcomes. Learn how MCP, orchestration frameworks, and persistent memory enable enterprise-grade agents, plus four high-impact use cases and a practical next-step checklist.
Content Chunking: A Foundation of Effective AI in Knowledge Work
Learn how content chunking transforms unstructured data into machine-readable segments, enhancing generative AI systems' effectiveness. Discover strategies like fixed-length, dynamic, hierarchical, and multi-modal chunking to improve embeddings, semantic retrieval, and AI accuracy. Explore the vital role of knowledge workers in refining, structuring, and validating content for optimal AI performance.
Knowledge Systems and Synthetic Data: The Role of Generative AI in Data Augmentation
Most modern, business-focused software systems rely on high-quality data to function effectively. As artificial intelligence continues to shape these systems that support knowledge work, the demand for high-quality, diverse, and reliable data has never been greater.
RAG (Retrieval Augmented Generation) at Work
Explore Retrieval Augmented Generation (RAG) and its transformative impact on knowledge work. Learn how RAG integrates retrieval and generation to deliver accurate, context-rich insights by leveraging embeddings, vector databases, and generative AI. Discover practical applications for productivity and decision-making.
Vector Databases Explained: A Key Tool for Knowledge Management
Discover how vector databases are revolutionizing knowledge management by efficiently storing and retrieving unstructured data. Learn about their core components, advantages, and real-world applications in this comprehensive guide.
Embeddings in Action: How AI Understands & Retrieves Knowledge
Explore how AI uses embeddings to understand and retrieve knowledge across different media, enhancing the accuracy of semantic search and boosting productivity for knowledge workers.
Transformer-Based AI Models: Overview, Inference & the Impact on Knowledge Work
Explore the evolution and impact of transformer-based AI models on knowledge work. Understand the basics of neural networks, the architecture of transformers, and the significance of inference in AI. Learn how these models enhance productivity and decision-making for knowledge workers.