Your agent needs a context budget (or it'll drown in its own data)

Your agent starts sharp. Clean memory, focused instructions, clear objectives. Then you give it access to your codebase, your docs, your email, your calendar. Three weeks later, it's slow, confused, and constantly asking for clarification on things it used to handle perfectly.

The problem isn't the model getting dumber. It's context pollution.

Every interaction adds to your agent's working memory. Every file it reads, every API response it processes, every conversation thread it follows — all of it stays loaded until you hit the context window limit. Then the model starts dropping the stuff it thinks is least important, which is rarely what you'd choose to drop.

The fix is a context budget: explicit rules about what gets loaded, when, and for how long.

Here's the pattern that works:

## Context Budget Rules

# Core context (always loaded)
- Agent identity and core instructions
- Current session objectives
- Active project context
- Last 5 interactions

# Conditional context (load on demand)
- Full codebase scan: only for architecture questions
- Email history: only for communication tasks
- Documentation: only when explicitly referenced
- Calendar data: only for scheduling tasks

# Ephemeral context (auto-expire)
- API responses: expire after task completion
- File contents: expire after 10 minutes of inactivity
- Search results: expire immediately after use
- Debug logs: expire after problem resolution

The key insight: your agent doesn't need to remember everything, it needs to remember the right things at the right time.

I implement this with context tags in my agent instructions:

Before loading additional context, check:
1. Is this CORE (always needed)?
2. Is this CONDITIONAL (needed for this specific task)?
3. Is this EPHEMERAL (use once and discard)?

If CONDITIONAL: Load only what's needed for current objective
If EPHEMERAL: Set explicit expiration (time or task completion)

When context budget hits 80%:
1. Archive completed task context
2. Compress repetitive information
3. Escalate if core context is at risk

Pro tip: Your agent should announce when it's approaching context limits and ask what to prioritize. Don't let it make those decisions silently.

The difference is dramatic. Instead of a confused agent drowning in irrelevant context, you get a focused agent that loads exactly what it needs, when it needs it, and cleans up after itself.

Context management isn't just about performance — it's about maintaining your agent's ability to think clearly over time. Treat context like memory in a resource-constrained system: precious, limited, and requiring active management.

If you're building agents that need to maintain focus across long-running sessions, you need operational discipline from day one.