· mcp
MCP authorization decides what context agents see
MCP authorization became a context control plane in 2026. RFC 8707 token scoping decides which sources an agent can ever pull into its own context window.
Blog
The Wire Blog
Practical context engineering for AI agents: how to structure, deliver, and manage the context that determines whether AI systems actually work.
Research-backed articles on context architecture, retrieval, agent security, and making AI tools more effective. Written by Jitpal Kocher.
· MCP (Model Context Protocol)
Stateless MCP: the spec is dropping session state
The 2026 MCP release candidate goes stateless: no initialize handshake, no session ID, any server instance answers any request. What stateless MCP means.
· MCP (Model Context Protocol)
MCP Tasks: long-running work as context offloading
MCP Tasks let a server return a durable handle instead of a blocking result, keeping a long-running tool call's interim state off the agent's context window.
· Context Engineering
Meta context engineering beats hand-tuned context
Meta context engineering (ICML 2026) learns the context-engineering process itself, beating ACE-style curation by 18 points while training 13.6x faster.
· Context Portability
Claude Fable 5 put a price on context portability
Claude Fable 5 returns refusals as HTTP 200s and retries them on Opus 4.8. The fallback API reveals exactly what agent context survives a mid-task model swap.
· Context Engineering
Five criteria of good context for AI agents
A 2026 paper formalizes five criteria for good AI agent context: relevance, sufficiency, isolation, economy, and provenance. Here's how to design for each.
· Multi-Agent System
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.
· Context Engineering
When to process AI context: ingestion, dreaming, query
There are three moments to process AI context: ingestion, a background pass some call dreaming, and query time. Match each kind of work to the right one.
· AI Hallucination
Claude Opus 4.8 hallucinates less by answering less
Claude Opus 4.8 tops a hallucination benchmark without getting more accurate. It learned to abstain. Why retrieval honesty is a context engineering win.
· RAG (Retrieval-Augmented Generation)
RAG, long context, or fine-tuning: how to choose
RAG, long context, or fine-tuning? A 2026 decision guide on cost, accuracy, and freshness, with a use-case table for choosing the right one in production.