// term 85 · Agentic Systems
Planner Model
Task Sequencing Intelligence
A model or component dedicated to converting high-level goals into executable sub-task sequences — the strategic layer of agentic architectures. The planner decides what should happen and in what order; executors handle the doing. Separating the two is how complex AI workflows stay coherent.
// Pattern
plan / execute
Strategic decomposition separated from tactical completion — each layer optimized, prompted, and even modeled differently.
// Economics
asymmetric
Strong models plan; cheaper models execute — the cost structure that makes complex workflows affordable.
// Output
the plan
An explicit, inspectable task graph — reviewable before execution, trackable during, auditable after.
// full definition
What Planner Model actually is
Complex work has two distinct cognitive jobs: deciding what should happen, and making each piece happen. Agent architectures that fuse them — one model improvising strategy mid-execution — drift, lose the thread, and optimize steps at the expense of the goal. The planner-executor pattern separates the layers: a dedicated planner converts the objective into an explicit sequence of sub-tasks with dependencies; executors complete the steps; results return to the planner, which tracks progress and revises. Strategy stays coherent because something owns it.
The separation pays in three currencies. Coherence: the plan is a persistent artifact — the workflow's spine — surviving the context churn of step-level execution; long tasks stay aimed at their goal. Economics: planning is hard and rare, execution is easier and constant — a frontier model plans while cheaper models execute steps, often cutting workflow costs severalfold at equal quality. And governance: an explicit plan is reviewable before anything runs — the inspection point where humans approve, adjust, or veto strategy while it's still just intent.
The planner's craft is the plan's quality across dimensions executors can't fix: decomposition that actually partitions the goal, dependency ordering that respects reality, step specifications complete enough to execute without re-deriving intent, and constraint fidelity — budgets, permissions, policies threaded into the structure. Equally craft: replanning. Execution results arrive as feedback — failures, surprises, new information — and the planner's revision quality under that feedback, more than its first draft, determines whether workflows finish.
Architecturally, planners appear at every scale: a planning pass inside a single agent's loop, a dedicated orchestrator over a multi-agent fleet, a standing service decomposing incoming work across systems. The pattern's risks concentrate at its strengths' edges — plans wrong at the strategy level fail globally where step errors fail locally, stale plans misdirect until replanning catches up, and over-planning burns budget structuring work that needed doing more than designing. The balance is empirical: plan depth proportional to task complexity, revision cadence proportional to environmental surprise.
// how it works
The strategy layer of agent systems
Planner-executor architectures split thinking from doing — the planner decomposing and sequencing, executors completing steps, results flowing back to replan.
Goal Analysis
The planner interprets the objective and its constraints — scope, resources, policies — the inputs every plan must honor.
Decomposition
The goal splits into sub-tasks that genuinely partition the work — the structural judgment that defines the plan.
Sequencing
Dependencies order the steps, parallel branches surface — the task graph taking executable shape.
Plan Review
The explicit plan is inspectable — by humans at stakes, by validators always — strategy approved while it's still intent.
Delegated Execution
Executors complete steps — often cheaper models or specialized agents — results flowing back as progress and surprise.
Replanning
The planner revises against feedback — steps adjusted, branches pruned, strategy maintained through contact with reality.
// anatomy
The components teams must understand
01
Planner Core
The strategy engine
The model owning decomposition and sequencing — typically the strongest reasoning in the architecture, spent where it leverages.
02
Task Graph
The plan as artifact
Explicit steps, dependencies, and specifications — the persistent spine that keeps long workflows aimed.
03
Executor Pool
The doing layer
Cheaper models and specialized agents completing steps — tactical capability matched to tactical work.
04
Progress Ledger
State across steps
What's done, pending, failed, and learned — the tracking that makes replanning informed rather than blind.
05
Replanning Loop
Strategy under feedback
Plan revision against execution results — the capacity that matters more than first-draft elegance.
06
Review Gate
Strategy, inspectable
The plan surfaced for approval before execution — governance attached at the layer where it's cheapest.
// strategic implications
What this changes for the business
01 · Architecture
Separate strategy from execution
Fused improvisation drifts; explicit planning holds workflows together across length and surprise. For multi-step AI work, the planner-executor split is the structural decision that determines whether complexity stays coherent — make it deliberately.
02 · Economics
Spend the strong model where it leverages
Planning concentrates the hardest reasoning into the fewest calls — frontier models plan, cheaper models execute. The asymmetric routing often cuts workflow costs severalfold at equal quality; uniform model assignment leaves the savings on the table.
03 · Governance
Review the plan, not just the results
An explicit task graph is inspectable before anything runs — the cheapest point to catch strategic error and enforce policy. At stakes, gate execution on plan approval; the artifact exists precisely so oversight can attach to it.
// common misconceptions
What Planner Model is not
Myth
“A capable model doesn't need a separate planning layer.”
Reality
Capability improvises well over short horizons; long workflows drift without an owned, persistent strategy. The planning layer is structure, not compensation — it's what keeps strong models aimed across length.
Myth
“The plan is the hard part — execution follows.”
Reality
Plans break on contact with reality as a matter of course; replanning under feedback is where workflows survive. Evaluate planners on revision quality through surprise, not first-draft elegance.
Myth
“More detailed plans are better plans.”
Reality
Over-specification burns budget and shatters on the first surprise — detail beyond the environment's predictability is waste. Plan depth proportional to task complexity, revision cadence proportional to volatility.
// from literacy to leverage
Know the term. Now build the strategy.
Vocabulary is the entry fee. Turning these primitives into pipeline, moats, and margin is the work. That's the conversation.