GPT-5.6 subagents: context isolation in the weights
GPT-5.6 Sol's Ultra mode gives each subagent its own context window. It solves context isolation but not handoff, and it multiplies your token bill fast.
Further reading
Articles about Context Rot
14 articles from the Wire blog, sorted newest first. Return to the Context Rot definition for context.
AI agent reliability is a context problem
AI agent reliability fails because the same task assembles different context every run. Non-determinism is a context engineering problem, not a model flaw.
Context bloat: why long-running agents break
Context bloat is when accumulated tool-call output crowds out an agent's task. Tool calls, not window size, break long-running agents. Here is the fix.
Sub-agent context isolation: the fix for context rot
Sub-agent context isolation gives each agent its own scoped window, stopping the context rot that kills multi-agent runs. Here's the pattern and its limits.
What 466 AGENTS.md files teach about context engineering
An MSR 2026 study of 466 open source projects maps the five modes developers use to write AGENTS.md context, and what 50% file staleness reveals about practice.
Agentic context engineering: how ACE evolves contexts
ACE (ICLR 2026) beats tuned prompts by 10.6% with self-evolving contexts that avoid brevity bias and context collapse, two real failures of prompt tuning.
Long context tripled hallucinations in 35 open models
A 172-billion-token study across 35 open models found hallucination rates triple from 32K to 128K context, and exceed 10% at 200K for every model tested.
Why every agent handoff corrupts your context
Every multi-agent handoff is a lossy compression event. Learn which five types of context degrade at agent handoff boundaries and how to preserve them.
Agent drift: why long-running AI agents lose the plot
Agent drift is how AI agents silently deviate from their goal over long tasks. Goal drift, stale context, and four more mechanisms cause it, not the model.
Why AI agents forget mid-task (and how to fix it)
65% of agent failures come from context drift, not token limits. Here's how context compression keeps long-running AI agents on track.
Why AI Agent Memory Keeps Failing
AI agent memory fails because it's a context engineering problem, not a storage problem. Research reveals three failure modes and what actually works.
Why AI Coding Assistants Can't See Your Codebase
84% of developers use AI coding tools, but only 29% trust the output. The problem has less to do with models and more to do with codebase context.
Why Does ChatGPT Forget Everything?
AI doesn't forget because it's broken — it forgets because everything gets crammed into one place. Here's the technical explanation and how to fix it.
Context Rot: Why AI Performance Degrades With More Information
Research shows LLMs drop from 95% to 60% accuracy as context grows stale. Here's how context rot degrades AI performance and why bigger windows won't help.
Put context into practice
Create your first context container and connect it to your AI tools in minutes.
Create Your First Container