Notes from the team.
Engineering decisions, retrieval evals, and field lessons on building memory for AI agents. Less marketing, more substance.
Why AI Agents Need Centrally Managed Skill Files
Agent skills (SKILL.md files) are sprawling across repos, machines, and teams. The case for a single, governed registry — and how AgentPrizm provides one.
Gene Avakyanagent skillsAgentSkillsdeveloper tools · 7 min readVersioning and Governing Agent Skills — Not Just Copy-Pasting SKILL.md
Copy-pasted SKILL.md files rot: they drift, lose provenance, and leak secrets. How AgentPrizm versions, scans, and governs the skills your agents share.
Gene Avakyanagent skillsgovernanceversioning · 7 min readHow Agents Find the Right Skill: Semantic Discovery for SKILL.md
Folders of SKILL.md files do not scale. How AgentPrizm lets agents discover skills by intent — semantic search over a governed registry, via MCP or REST.
Gene Avakyanagent skillssemantic searchMCP · 8 min readAn Open Marketplace for Agent Skills: Install, Fork, and Copyleft
A public marketplace lets agents share SKILL.md capabilities safely. How AgentPrizm handles install vs fork, copyleft lineage, and moderation.
Gene Avakyanagent skillsmarketplaceopen source · 7 min readThe Coming Economy of Agent Skills
If skills are reusable units of agent capability, a marketplace around them creates real economic opportunity. Where AgentPrizm is headed — and where it is today.
Gene Avakyanagent skillsmarketplacemonetization · 6 min readGive Claude Code Persistent Memory in 90 Seconds
Claude Code forgets everything between sessions. This tutorial shows how to add persistent memory to Claude Code and any MCP client in under two minutes.
Gene Avakyanagent memoryMCPClaude Code · 8 min readThe Best Memory Layer for AI Agents in 2026
How to evaluate the best memory layer for AI agents: a criteria checklist, fair profiles of top tools, and recommendations by use case.
Gene Avakyanagent memorymemory layercomparison · 7 min readAgentic Memory vs RAG: What's the Difference?
Agentic memory and RAG both retrieve context for an AI prompt, but they solve opposite problems. Here's the precise distinction and when you need each.
Gene Avakyanagentic memoryRAGAI engineering · 7 min readWhat Is an AI Memory Layer? A Plain-English Guide
An AI memory layer is infrastructure that gives stateless AI agents persistent, governed memory across sessions. A plain-English guide to what it is, and is not.
Gene Avakyanagent memoryAI infrastructureexplainer · 7 min readRight to Forget for AI Agents: Deletion, Audit, and GDPR in Practice
As AI agents store memories about real people, deletion becomes a legal and trust requirement. How right-to-erasure, audit trails, and soft vs hard delete actually work.
Gene Avakyanagent memoryGDPRcompliance · 7 min readConfidence Scores in Agent Memory: Teaching Agents What They Don't Know
Not every memory deserves equal trust. A confidence score lets an agent tell a hard fact from a shaky guess — and know when to ask instead of act.
Gene Avakyanagent memoryAI reliabilityconfidence · 7 min readBigger Context Windows Won't Fix Agent Memory — Here's Why
Million-token context windows feel like they replace agent memory. They do not. Here is why bigger windows and a memory layer solve different problems.
Gene Avakyanagent memorycontext windowsLLM · 8 min readAgent Memory for Sales: Stop Re-Learning Every Account
A sales agent that starts from zero loses the compounding value of relationship memory. What to remember per account, and how to survive turnover.
Gene Avakyanagent memorysalesuse cases · 8 min readAgent Memory for Customer Support: Remember the Customer, the Device, the Promise
A support bot that forgets makes customers repeat themselves. A memory layer lets it remember the customer, the device, the workaround, and the promise.
Gene Avakyanagent memorycustomer supportuse cases · 8 min readZep vs. Mem0 vs. AgentPrizm: Hosted Agent Memory in 2026
A fair, sourced comparison of three hosted agent-memory platforms — Zep, Mem0, and AgentPrizm — across hosting, integration, governance, and pricing shape.
Gene Avakyanagent memorycomparisonvendor selection · 7 min readThe 6 Memory Types Every AI Agent Needs (and What Happens When You Confuse Them)
AI agent memory types are not interchangeable. Here are the six AgentPrizm uses, with concrete examples and the failure modes that show up when you collapse them into one blob.
Gene Avakyanagent memoryAI engineeringmemory types · 7 min readSetting Up a Persistent Memory MCP Server in 10 Minutes
A practical guide to connecting an MCP memory server to Claude Code, Cursor, or Claude Desktop so your AI agent remembers context across sessions.
Gene AvakyanMCPagent memorytutorial · 7 min readHow to Give an AI Agent Long-Term Memory: A Developer's Guide
Long-term memory for AI agents is not a longer context window. A clear guide to why LLMs forget, what real agent memory needs, and how to build it.
Gene Avakyanagent memoryLLMAI engineering · 7 min readFact Validity Windows: Why Agent Memory Needs an Expiration Date
Facts expire. A fact validity window tells agent memory when something was true, so old facts stop poisoning new decisions. Here is how it works.
Gene Avakyanagent memorydata qualityAI engineering · 8 min readContainer Scoping for AI Agents: How to Keep Multi-Agent Memory Clean
Once you have more than one agent, user, or tenant, agent memory needs scopes. How container scoping prevents cross-customer data bleed and noisy recall.
Gene Avakyanagent memorymulti-agentarchitecture · 8 min readBuild vs. Buy: Should You Roll Your Own Agent Memory Layer?
Building agent memory is easy to start and hard to finish. Here is what the work actually entails, when building is right, and when buying wins.
Gene Avakyanagent memoryengineering strategybuild vs buy · 7 min readWhy We Store Memory Embeddings on a $20/mo VPS (And What It Cost Us)
The honest story of running an agent memory layer — embeddings, vector search, the whole thing — on one $20/mo VPS, and the tradeoffs we made on purpose.
Gene AvakyanengineeringinfrastructurestartupsShip agents that remember.
Six lines of code. Confidence scores, validity windows, and audit trails included. Free until your agents ship.