Signal Archive
Future-facing notes from the memory layer.
Product updates, operational playbooks, and technical deep dives on building durable context for AI teams.
Every post below is tied to verified workflows in vem.
All Posts
Your AI Agent Now Remembers Your Project: Persistent Memory with vem
How to give your AI coding agents (Claude, Copilot, Cursor) long-term memory of your architecture, decisions, and sprint state using vem's memory layer and MCP server.
Mastering vem Tasks: Create, Prioritize, Implement, and Ship — A Complete Guide
A complete hands-on walkthrough of every vem task feature — rich metadata, lifecycle management, per-task agent context, impact scoring, flow metrics, agent-powered implementation, and PR iteration.
Sprint-Driven AI Development with vem cycle
Learn how to organise your AI-assisted work into goal-driven cycles, track throughput with flow metrics, and give your agents real-time sprint context.
Version-Controlling Your AI Agent Instructions with vem
Stop copy-pasting AGENTS.md across machines. Learn how vem instructions lets you push, pull, version, and instantly roll back your AI instruction files.
Cross-Session Memory: Importing Copilot, Claude, Gemini, Cursor, Windsurf, and Codex Sessions into vem
Every AI session contains knowledge that should outlive the chat window. Learn how vem sessions captures and imports agent work into your permanent project memory.
Keeping Memory Healthy: vem summarize, diff, and doctor
Stale memory misleads agents. Learn the three tools that keep your .vem/ directory accurate, current, and diagnosable.
Mastering VEM CLI: A Guide to 10x AI-Assisted Development
Learn the task-driven, agent-first workflow that keeps your AI agents perfectly aligned with your codebase context.
A best-practice pipeline for teams using vem end to end
A practical workflow that connects npm install, cloud sync, agents, and Git verification so teams get the full vem ecosystem.
The full vem workflow: from task intake to verified memory
A practical, end-to-end workflow for teams using vem across CLI, agents, and the web dashboard.
Memory as infrastructure for AI teams
Treating context like production data unlocks safer agent handoffs, faster reviews, and durable collaboration.
How to get productive with the vem CLI on day one
Learn the core CLI flows to create tasks, capture decisions, and commit verified memory alongside your code.
How to run the vem web app for teams and admins
Stand up the dashboard to manage organizations, seats, and memory artifacts with a clean UI layer.
Securing project memory with Custom Auth and MFA Enforcement
We moved beyond third-party auth to build a deeply integrated security layer with TOTP and organization-wide enforcement.
Detecting Truth Drift: why evidence-backed memory matters
Prevent agent hallucinations and maintain high data integrity with automated evidence verification.
Beyond Grep: AI-powered semantic search with 'vem ask'
Use vector embeddings and RAG to answer complex architectural questions across your entire project history.
Bridging the Gap: MCP tools and Agent Protocols
Learn how to choose between real-time MCP toolcalls and manual memory exchange blocks.
How to run the indexer and verify memory snapshots
Understand the indexer service that ingests Git state, marks snapshots as verified, and powers fast search.
How to answer project questions with verified memory
Use the search layer to retrieve the right tasks and decisions before an agent writes a single line of code.
Dnotech testimonial: a memory layer that finally sticks
Dnotech explains how vem helped their teams ship faster by making agent context durable and auditable.
How to operate the vem MCP server for agents
Keep agents aligned with tasks, decisions, and context packs through explicit tool calls.
Building Your AI Workflow in the Open: How to Get the Most from the vem Community
A practical guide to engaging with the vem developer community — from starring the repo and contributing docs to sharing your workflows.
How Developers Discover AI Tools in 2026: A Practical Content Strategy
What actually drives discovery and adoption of developer tools in the AI era — from SEO and documentation to community channels and workflow-sharing. A meta-analysis of what works.