Over the last two years, we learned how to build agents.
They can write code, call tools, summarize documents, generate plans, and take action. Early demos look impressive. For a few minutes, they feel transformative.
Then the system runs longer. An hour passes. Context grows. Decisions accumulate.
That is where things break.
Not because the model lacks capability, and not because the prompt was slightly off. Single agents do not scale into sustained work without losing intent, correctness, or control. By the end of 2025, enough teams had encountered this failure mode that a new abstraction became unavoidable.
2026 is the year agent orchestration becomes the dominant abstraction.
Agents are good at starting
Orchestration is how they finish!
Most agents are excellent at initiation.
They produce plans. They draft outlines. They open tabs. They generate artifacts quickly and confidently. Everything looks productive.
Then the work drags on.
Finishing requires a different class of behaviour. Focus must be maintained across long running tasks. Partial decisions must remain consistent with earlier intent. Errors must be caught early, not discovered after actions are irreversible.
This is the gap teams keep running into.
Agents start work very well.
They do not reliably finish it on their own.
In practice, this has become the real benchmark. Not whether an agent can generate something impressive, but whether it can Get Stuff Done (GSD) without constant human babysitting and without creating new cleanup work downstream.
That is not a model problem.
It is an orchestration problem.
Why single agents plateau
A single agent works well when the task is short, reversible, and loosely specified. That describes chat. It does not describe real work.
As tasks stretch from minutes into hours, the failure modes change. Intent drifts. Assumptions harden silently. Intermediate artifacts become inconsistent with each other. Corrections arrive late, when the cost of fixing them is already high.
Prompt tuning and switching models does not solve this.
The limitation is structural. Sustained work requires coordination, verification, and explicit ownership of decisions. That logic does not live inside a single prompt or a single agent loop.
What changed to make orchestration viable
This prediction is not speculative. It is grounded in concrete shifts that landed over the past year.
Tool calling stabilized and became a dependable interface rather than an experiment. Schema driven outputs and formal tool contracts dramatically reduced ambiguity at the boundary between models and systems
Inference loops moved from research to practice, allowing systems to refine intermediate results instead of relying on single pass generation. At the same time, evaluation harnesses became a first class discipline rather than a novelty.
Before this, orchestration was a theory.
In 2026, it is infrastructure.
Why finishing work became the scarce capability
The market has already noticed that finishing is the hard part.
In late 2025, Meta announced the acquisition of Manus, an agent focused startup. The strategic value was not a new model or a breakthrough in reasoning. It was the agent harness
Manus focused on agents that could plan, execute, recover, and complete complex tasks end to end. That required long running tool loops, memory outside the context window, periodic goal re articulation, and cost efficient execution over time.
What mattered was not intelligence at the token level.
What mattered was the system wrapped around it.
This pattern is showing up everywhere. Different teams, different tools, same conclusions. When the industry independently converges on the same solutions, it is usually because the abstraction has shifted.
Orchestration is an event stream, not a call stack
One useful way to understand why orchestration works is to stop thinking about agents as functions and start thinking about them as participants in a stream of events.
- Plans are events.
- Intermediate artifacts are events.
- Failures, retries, approvals, and corrections are events.
In my work on Vibe Decoding, I described systems where agents react to streams of events rather than linear instructions
In that framing, orchestration is not a central brain telling agents what to do. It is a system that observes, interprets, enriches, and routes events so that work keeps moving in the right direction.
This matters because intent does not live in any single agent. It emerges from the sequence of actions, decisions, and corrections over time. Orchestration systems that treat agent output as an event stream can detect drift, escalate uncertainty, and re align goals before failures compound.
This is one of the reasons orchestration scales where single agents do not.
A well-known orchestration pattern called the Ralph Wiggum loop demonstrates this principle in practice. It turns a one-shot model invocation into a persistent iterative workflow that keeps an agent working until explicit success conditions are met, intercepting normal exit behaviour and reinvoking the prompt until the work is truly complete.
This approach captures a fundamental orchestration principle: iterating over intermediate state with evaluation conditions is essential for agents to GSD in practice.
From using agents to managing them
The most important change in 2026 is not technical. It is conceptual.
Engineering leaders stop thinking in terms of using agents and start thinking in terms of managing them.
A single agent can generate a complex plan quickly. That part works. Execution is where things fail.
Orchestration changes the shape of the work. One agent produces the plan. Multiple specialized agents execute in parallel. Progress is written to shared artifacts. Verification agents review outputs. A coordinator reconciles conflicts and decides what ships.
Humans step in at defined checkpoints, not continuously.
This is how agents start to GSD.
Responsibility does not disappear
As agents become more capable, responsibility becomes harder to avoid.
If your agents can take action, you are accountable for those actions. Saying “the agent did it” is not an excuse. It never was.
Delegation does not remove responsibility. It concentrates it.
This is why orchestration matters. It creates explicit decision boundaries. It separates generation from approval. It makes authority visible instead of implicit.
Without that structure, autonomy becomes risk instead of leverage.
What stops mattering in 2026
This shift makes some debates uninteresting very quickly.
Models become commodities. Prompt engineering becomes table stakes. Individual agent cleverness stops being a durable advantage.
Serious teams stop arguing about which prompt is better or which agent is smarter. They focus on composition, failure containment, intent preservation, and authority.
This mirrors earlier transitions in software engineering, where teams stopped optimizing individual functions and started designing systems.
The same thing is happening here.
The real takeaway
Agents starting work was never the hard part.
Finishing is.
Orchestration is how probabilistic systems become reliable. It is how short bursts of productivity turn into sustained execution. It is how teams get leverage without losing control.
Some of the more forward looking architectures already point in this direction, treating iteration, refinement, and feedback as first class system concerns rather than accidents.
That is why 2026 is the year agent orchestration becomes the dominant abstraction.
Agents can start.
Orchestration is how they GSD.