AI
Artificial intelligence, machine learning, and everything LLM
#2693: Format Adherence in AI: Beyond the Benchmarks
Why your AI ignores formatting instructions and how to fix it with pipeline architecture, not model swaps.
#2692: Type Safety: Static vs Dynamic, Soundness & More
Static vs dynamic, strong vs weak, and the truth about TypeScript's unsoundness. A deep dive into type theory.
#2691: Can AI Agents Safely Manage Your API Keys?
Is it time to let AI agents handle your API key creation and rotation? We explore the real security tradeoffs.
#2690: Where Agent Builders Actually Gather
The MCP community, A2A protocol, and Linux Foundation are building the professional identity of agentic AI right now.
#2689: Why CLI Beats MCP for AI Agents Sometimes
Why a plain command-line tool can outperform a purpose-built MCP server for AI agents — and what that means for the protocol's future.
#2688: Declutter Your Apartment with AI Video Analysis
Use multimodal AI and smart frame extraction to turn a walk-through video into an actionable decluttering plan.
#2687: When Pre-Flight Checks Help (or Hurt) Agentic AI Plugins
How to decide when a pre-flight check is worth the latency cost — and how to write good ones.
#2685: Plugin Data Storage for AI Agents
How to separate user data from plugin code across Linux, macOS, and Windows in agentic AI environments.
#2684: When Agent Skills Collide: Context Windows & Plugin Design
How to handle overlapping agent skills and whether context windows will ever make the problem go away.
#2683: MCP vs Agent Skills: Context Wars
When 12M token windows arrive, do MCP servers or agent skills win? Plus: federated access for agent teams.
#2682: Live Retrieval vs. RAG: What an Agent Actually Does
Does every AI conversation create a tiny vector store? We unpack the real tradeoffs between live document fetching and pre-indexed RAG.
#2677: Memory Layers for AI Agents: SaaS vs Self-Hosted
Zep, mem0, Letta, Graphiti, Cognee — which memory layer should you commit to for your AI agent?
#2676: Vector Database Schema Design for AI Memory Layers
Stop dumping vectors blindly. Design metadata schemas and namespaces for retrieval that actually works at scale.
#2675: Docs That Win Clients: A Consultant’s Guide
The key documents every consultant needs—and how AI makes them effortless to create and maintain.
#2674: Why Your Agent's Context Window Is Getting Eaten Before You Start
Stop shipping the whole toolbox to every session. A bridge plugin pattern that fetches skills on demand instead.
#2673: Vector DB Backups & Editing: What Pinecone Can (and Can't) Do
Can you edit or delete individual chunks in Pinecone? And can you actually back up a vector index? Yes—but with critical caveats.
#2672: 12M Token Context: Subquadratic Cracks Attention Scaling
A startup claims linear attention scaling at 12M tokens, beating GPT-5.5 on retrieval benchmarks.
#2669: Low-Touch Lead Qualification for Solo Consultants
Stop wasting hours on calls with unqualified leads. Learn low-touch vetting that filters bad fits without sounding hostile.
#2668: OCR vs VLMs: Reading Labels on Camera
Tesseract, EasyOCR, or a cloud vision model? How to build a fast, reliable label scanner for real-world conditions.
#2665: Partner Certs vs Personal Certs: What Actually Matters
Solo operators face structural barriers in vendor partner programs. Here's how personal and partner certifications actually differ.