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Jack Ryan

The agent designs the implementation, then writes it.

Coding agents can design your Zep implementation

Zep now ships one plugin for Claude Code, Codex, and Cursor. It gives your coding agent the Zep documentation MCP server and the new building-with-zep skill, which encodes how to design and evaluate an agent memory implementation around the use case you need to deliver.

Securing Agent Memory with ABAC

Securing Agent Memory with ABAC

Attach policies to any Zep API key to control the exact endpoints it can call and the graph data it can read.

Agent memory placement can cut your token bill up to 2x

Agent memory placement can cut your token bill up to 2x

Agent memory has to refresh every turn, but putting it in the system prompt breaks prompt caching and re-bills the whole conversation each turn. Here is the one-message fix, and the token savings it led to in an experiment.

Markdown is not agent memory

Markdown is not agent memory

Some of the most capable agents in production keep their memory in plain markdown files, and for a single agent and a single user it is hard to beat. The pattern breaks in predictable places: at scale, as facts change and errors compound, and under concurrent agents.

The Batch API: Load Large Datasets into Agent Memory

The Batch API: Load Large Datasets into Agent Memory

Zep's Batch API loads large datasets into agent memory faster, in batches up to 50,000 items, with a progress dashboard and no impact on real-time ingestion.

Smart Context Assembly: Fewer Tokens, Better Quality

Smart Context Assembly: Fewer Tokens, Better Quality

Today we're announcing Smart Context Assembly, an upgrade to how Zep's default Context Block is built: higher accuracy from fewer tokens, with no code changes.

Observations: Patterns and Insights from the Context Graph

Observations: Patterns and Insights from the Context Graph

Observations are a new context type in Zep that capture patterns and insights across your Context Graphs, automatically discovered and surfaced to agents.

Zep's 5 Context Types: How to Use and Combine Each One

Zep's 5 Context Types: How to Use and Combine Each One

Zep produces five distinct types of context from a user's graph. Each captures something different. Here's when to reach for each, and how to combine them in one prompt.

Context You Can Trace, Filter, and Trust

Context You Can Trace, Filter, and Trust

Every fact in your agent's context graph came from somewhere. Zep's provenance architecture traces facts back to their source data — and lets you filter retrieval by origin.

Stop Letting Your Agent Decide What It Needs to Know

Stop Letting Your Agent Decide What It Needs to Know

Your agent has the tools. It just doesn't call them — and smarter models won't fix that. Here's why the unknown unknowns problem is the hardest challenge in agent context, and what to do about it.

3 Decisions That Shape Every Agent's Context Architecture

3 Decisions That Shape Every Agent's Context Architecture

Every agent context architecture comes down to three decisions: scope, data sources, and retrieval strategy. A framework for reasoning about persistent context for AI agents.

Evaluation and Control: Evaluation Framework, zepctl CLI, and Dashboard Overhaul

Evaluation and Control: Evaluation Framework, zepctl CLI, and Dashboard Overhaul

An evaluation framework for testing Zep against your data, a redesigned dashboard with analytics, and zepctl — a CLI for administering Zep projects.

Build Better Context Graphs: Custom Instructions, Search Filters, and Webhooks

Build Better Context Graphs: Custom Instructions, Search Filters, and Webhooks

Custom extraction instructions, property-level search filters, exclusion filters, and webhooks — more control over how you build and query context graphs.

Context Templates: Context Engineering Made Simple

Context Templates: Context Engineering Made Simple

Key Takeaways * Context templates let you declare what context an agent gets (user summary, edges, entities, episodes, with per-section limits and types) instead of writing sequential retrieval calls in code. * Save a template once and reference it by ID, so your context configuration is version-controlled and reproducible across

How Zep Works: A Visual Guide to Knowledge Graphs for AI Agents

How Zep Works: A Visual Guide to Knowledge Graphs for AI Agents

Key Takeaways * Agents don't fail because the model is weak; they fail because the right context isn't there. Chat memory only sees conversations, static RAG goes stale, tool calls are slow, and context stays scattered across systems. * Unified: Zep ingests any text source (chat messages, documents,

Building Voice Agents with Memory: Zep x LiveKit

Building Voice Agents with Memory: Zep x LiveKit

Create personalized voice agents with long-term memory with minimal added latency

Agents That Always Remember What Matters

Agents That Always Remember What Matters

💡NEW User Summary Instructions: Zep now offers steerable user summaries. This post explores why these are useful and how best to implement them. Zep is a context engineering platform for AI agents built on a temporal knowledge graph that captures evolving user interactions and business data. On every chat turn,

Zep v3: Context Engineering Takes Center Stage

Zep v3: Context Engineering Takes Center Stage

Context is what makes or breaks agent applications. Early on, everyone focused on prompt engineering—tweaking the exact wording to get better responses. But as we've built more complex agents, it's become clear the real work is in context engineering: systematically assembling the right information around

Zep Q2 Feature Round-up

Zep Q2 Feature Round-up

In Q2, we focused on expanding the flexibility of Zep's knowledge graph capabilities, improving observability, and making it easier to work with episodes and relationships. Here’s a look at the major features and improvements shipped this quarter. Custom Entity Types This release introduces support for custom entity

Zep Q1 Product Round-up

Zep Q1 Product Round-up

Graph Explorer, an upgraded Playground, and a practical Cookbook—giving developers more control, better graph quality, and improved usability.

Building A Russian Election Interference Knowledge Graph

Building A Russian Election Interference Knowledge Graph

How we built a Knowledge Graph-based app for exploring Russian interference in the run-up to the 2024 US elections.

Exploring Russian Election Interference with a Knowledge Graph

Exploring Russian Election Interference with a Knowledge Graph

We built a visual exploration tool and AI assistant for analyzing Russian interference in the run-up to the 2024 US elections.