Most MCP servers ship with a static bearer token. It’s one line in .mcp.json, it works on day one, and it’s the wrong answer the moment your server is anything other than a personal dev tool. Engram, the semantic memory layer behind my AI-native development workflow, started there too. A shared bearer header in .mcp.json, […]
When I wrote about replacing HighRadius in six weeks, I said the pace wasn’t raw AI speed — it was contextual continuity. Every agent session opened already knowing the architecture, the prior decisions, the history. Nothing was re-explained. Nothing was lost. That continuity layer now has a name and a front door. It’s called Continuum, […]
Most people treat “AI-Native development” as a productivity story. Write faster, debug faster, ship faster. That’s the small version. The larger version is this: with the right architecture and process discipline, a single developer can design, build, document, and validate an enterprise-grade platform in a timeframe that would be implausible otherwise. Not a prototype. Not […]
Nine days ago, I published a post about building a semantic knowledge system — a pgvector-backed memory layer that gives every AI agent I work with persistent, searchable context across all my repositories. The architecture was clean. The idea was sound. But it was still mostly a promise. Nine days later, I have the receipts. […]
AI coding assistants are powerful, but they have a fundamental limitation: they forget everything between sessions. Every new conversation starts from zero. Your agent doesn’t know what you built yesterday, what decisions you made last week, or why you chose Dapper over Entity Framework three sessions ago. I decided to fix that. Enter the Semantic […]