Context Engineering: The Foundation of Reliable AI Agents - Zep

What is Context Engineering?

Context Engineering is the practice of systematically assembling all necessary information—user history, business data, instructions, and tools—around a language model so it can accomplish tasks reliably.

Think of it like briefing a new employee. You don't just give them a task and hope for the best. You provide background on the company, relevant project history, access to necessary tools, and clear guidelines. Context Engineering does the same for AI agents.

While prompt engineering focuses on asking better questions, Context Engineering ensures the AI has everything it needs to give the right answer.

APPLICATION & INTERFACE

AGENT FRAMEWORK

CONTEXT ENGINEERING

ZEP CAPABILITIES

Context Orchestration

Agent Memory

Graph RAG

Search Tools

Prompt Construction

Tool Integration

LLM

Why Context Engineering Matters Now

The Problem

LLMs are stateless. They only know what's in their immediate context window.

Hallucinate

Make up facts because they lack relevant context

Generic Responses

Lack understanding of user preferences and history

Miss Business Context

Ignore crucial business data that changes recommendations

Repeat Conversations

Start from scratch instead of building on past interactions

Fail Complex Tasks

Struggle with tasks requiring multiple pieces of information

Poor User Experience

Frustrate users with irrelevant or incomplete responses

tobi lutke@tobi·Jun 18, 2025

I really like the term "context engineering" over prompt engineering. It describes the core skill better: the art of providing all the context for the task to be plausibly solvable by the LLM.

Andrej Karpathy@karpathy·Jun 25, 2025

+1 for "context engineering" over "prompt engineering". People associate prompts with short task descriptions you'd give an LLM in your day-to-day use. When in every industrial-strength LLM app, context engineering is the delicate art and science of filling the context window

How Zep Transforms Context Engineering

Zep automatically handles the complex work of context engineering by building temporal knowledge graphs that capture user interactions and business data, then dynamically retrieving and formatting relevant context for your agents.

For Developers: Deploy Personalized Agents in Days

Instead of building complex retrieval infrastructure for months, Zep provides:

Robbie

2024-09-07 14:27

I only wear Adidas shoes. I love them!

Facts

Robbie only wears Adidas shoes.
Robbie strongly favors Adidas shoes.

Robbie

2024-10-14 09:12

My shoes fell apart and I need to return them. I'm super angry! I'll be wearing Nike going forward!

Facts

Robbie only wears Adidas shoes.
Robbie strongly favors Adidas shoes.
Robbie's Adidas shoes fell apart.
Robbie needs to return their shoes.
Robbie is angry about their Adidas shoes falling apart.
Robbie intends to wear Nike shoes in the future.

Agent Memory

Deploy Agents with Perfect Memory

Your agents remember user preferences, past conversations, and business context across all interactions. No more starting from scratch or losing important details.

Explore Agent Memory

Graph RAG

Retrieve Business Knowledge Like an Expert

Connect agents to your business data with Graph RAG that understands relationships and context, and automatically handles dynamic data. Your agents access the right information at the right time.

Discover Graph RAG

FACTS and ENTITIES provide relevant context for the current conversation.

# Key facts with their date ranges
# format: FACT (Date range: from - to)

  - Emily Painter cannot log in. (2024-11-14 02:13:19+00:00 - present)
  - Account Emily0e62 is suspended due to payment failure. (2024-11-14 02:03:58+00:00 - present)
  - Payment failed using card ending in 1234. (2024-09-15 00:00:00+00:00 - present)
  - Failure reason: Card expired. (2024-09-15 00:00:00+00:00 - present)


# Key entities and their descriptions
# ENTITY_NAME: entity summary

  - Emily0e62: User account owned by Emily Painter, currently suspended due to payment failure and login issues.
  - Card expired: Reason for the failed payment transaction.

Context Assembly

Automated Context Creation

Stop manually crafting prompts. Zep automatically assembles relevant user memory and business context into optimized prompts for reliable agent performance.

See Agent Context

For Engineering Leaders: Measurable Performance with Enterprise Compliance

Zep delivers quantifiable improvements while mitigating business risks:

Performance Gains

• 100%+ accuracy improvements through comprehensive personalized context
• 90% latency reduction with 98% token efficiency
• Sub-second retrieval for real-time applications

Enterprise-Ready

• SOC2 Type 2 and HIPAA compliance for regulated industries
• Temporal fact management with automatic invalidation of outdated information
• Custom fact rating systems for quality control

Business Context Integration

• Connect user conversations with CRM, billing, and support data
• Group graphs for shared organizational knowledge
• Real-time data integration without expensive recomputation

Context Engineering in Action

Without Context Engineering

User: "Schedule my usual meeting with the team"

Agent: "I need more information about your usual meeting preferences, team members, and availability."

With Zep's Context Engineering

User: "Schedule my usual meeting with the team"

Agent has access to: Meeting history, team preferences, calendar patterns, project context

Agent: "I'll schedule your weekly project sync with Sarah and Mike for Tuesday at 2 PM in Conference Room A, with the Q1 planning agenda you used last time."

Context Engineering

The Foundation of Reliable AI Agents