AI Context Problem

Why AI Coding Agents Lose Context

Every session starts from zero. You re-explain your tech stack, your decisions, your constraints. It doesn't have to be this way.

The Problem

You spent an hour yesterday explaining your authentication architecture to Cursor. Today, it suggests the exact approach you rejected. It has no memory of yesterday's conversation.

This is the fundamental limitation of AI coding agents: they're stateless. Every session starts fresh. The context window holds only what you've said in the current conversation, and when you close the session, that knowledge disappears.

Why This Happens

1. No Persistent Storage

AI models don't have built-in memory across sessions. They process your current prompt, generate a response, and forget. There's no database of "things Drew decided" that persists between conversations.

2. Context Window Limits

Even within a session, there's only so much context the model can hold. Long conversations get truncated. Important decisions from earlier in the session can fall out of the window.

3. No Access to External Knowledge

Your AI agent can read your codebase, but it can't read your Slack conversations, your Linear tickets, or the meeting where you decided to use Postgres instead of MongoDB. That context exists, just not where the agent can see it.

The Real Cost

Teams report spending 20+ hours per week re-explaining context to AI agents. That's half a developer's time just getting the agent back to where it was yesterday.

What You Lose

The Impact

Without persistent context, AI agents make technically correct decisions that are wrong for your product. They suggest features you've explicitly ruled out. They use patterns that don't fit your architecture. They build for generic users instead of your actual customers.

You end up babysitting the agent instead of leveraging it. Every session requires onboarding, like hiring a new contractor who knows nothing about your business.

How to Solve Context Loss

There are three levels of solutions, from basic to comprehensive.

Basic

Static Rules Files

Create a .cursorrules or CLAUDE.md file with your conventions. Loads at session start.

Limitation: Manual updates, no decision memory, gets stale.

Better

AGENTS.md + Skills

Structured rules with reusable skills and commands. More organized than basic rules.

Limitation: Still file-based, no live data, decisions aren't searchable.

Best

Brief MCP

Live product context via MCP. Decision history, customer personas, strategic constraints. Updates automatically from your tools.

Get started →

Stop Re-Explaining Every Session

Brief gives your AI coding agent persistent memory. Decisions, customers, constraints, all accessible via MCP.