Agent Handoffs Need a Context Layer
A neutral layer for routing context across tools, models, and trust boundaries.
Agents will not scale by working alone. They will scale by learning how to hand work off.
Your trusted agent will hand off work to specialized agents across tools, models, and trust boundaries. Some will access private data. Some will operate inside vendor systems. Some will represent people or organizations you do not control.
Every handoff is a decision: what travels, what stays, and what should never have moved.
The surrounding infrastructure for the agent-to-agent economy is already being built. Communication protocols are converging: Anthropic's MCP, Google's A2A. Payments are maturing: Coinbase's x402, Stripe's MPP, Visa's Trusted Agent Protocol. Identity and reputation are being built from several directions: Microsoft Entra Agent ID, Okta AI Agents, Ethereum ERC-8004, World ID.
These are necessary primitives. But they do not decide what context crosses the boundary.
That is the missing layer: context routing. Not communication. Not payment. Not identity.
The path to context routing
The context layer has one job: route the right context to the right agent at the right time.
We are building toward that in three phases.
Phase 1: Structuring context
Flat context does not scale. Long-running sessions accumulate tool outputs, bury constraints, and degrade through compaction. This is what we have called context collapse in prior writing.
The first step is to treat context as structured, retrievable state rather than a single growing stream. Each episode captures a unit of agent work: the user message, tool calls, tool results, agent response, decisions, and constraints needed to recover that work later. Episodes are indexed for retrieval and curated at each step.
This is the foundation. It is shipped.
Phase 2: Scaling context with sub-agents
Once context is structured, it can be scoped and distributed. That makes sub-agents practical.
A single agent should not carry the full trace of every branch in a task. When a task splits, context should split with it. A search agent gets the query, source constraints, and retrieval objective. A synthesis agent gets the relevant findings, original goal, and constraints that must survive. Different job, different context.
Context stops scaling vertically inside one window. It starts scaling horizontally across sub-agents, each working with only the context it needs.
The hard problems are decomposition and composition: what should be split out, what should each sub-agent receive, and how do results come back without losing constraints or creating more noise.
The next step is to make this operational: scoped sub-agent creation, context packets for each task, structured return values, and traceable composition back into the main agent. The goal is not to spawn more agents. The goal is to make delegation reliable without bloating the parent context.
Well-managed context matters more than model scale. Better context management and better decomposition let smaller or open models do work that would otherwise require frontier systems.
Proving that out means showing real workflows where smaller models complete tasks that otherwise need larger models, longer windows, or repeated retries.
This is where active research sits.
Phase 3: Routing context across agents
This is the frontier.
It starts with your own agents. Then agents you trust. Then agents in the wild.
Every step outward increases the trust boundary. As context moves across those boundaries, the risks rise. Agents can overshare. They can share too little, losing critical constraints. They can be manipulated into revealing context they should not expose.
Privacy, sovereignty, and user intent are no longer implicit. They have to be carried explicitly.
Communication protocols help agents connect. They do not decide what should ride across those connections, or with what boundaries.
That is the layer we are building toward: harness-independent and model-independent, sitting above communication protocols as the context decision layer.
This is not a solved problem. It is a necessary one.
This is where we are heading.
Why this matters
The agent-to-agent economy is coming regardless. The question is who owns the boundary.
If context routing lives inside one runtime, your agents are captive to that runtime. It decides what gets shared, what gets summarized away, what constraints survive, and what the next agent is allowed to see. Your trust boundary becomes a product feature controlled by someone else.
That is not enough for an agent world that crosses tools, models, companies, and users.
The context layer has to be open and neutral. Structurally, it can be. Storage vendors are paid to retain context, not to decide what should not move. Orchestration frameworks describe who calls whom, not what travels with the call. Model vendors ship their own harnesses, and a neutral routing layer cuts against the logic of lock-in. None of them is the routing layer.
For enterprises, this is not just architecture. It is explainability, auditability, and compliance. If agents hand work to other agents, teams need to know what moved, why it moved, who received it, and under what policy.
If context routing is neutral, three things become possible: agents work across runtimes, constraints survive handoffs, and delegation works across vendors instead of only inside one stack.
Contexto is the Context Engine we are building for that world. Harness-independent, model-independent, and built in the open.
Because the future is not one agent doing everything. It is agents collaborating with other agents. And when that happens, the most important infrastructure is not just who can connect, who can pay, or who can prove identity. It is who routes the context.