Reactive versus Planned Agents

Reactive and planned agents represent two different approaches to control. A reactive agent decides what to do next based on the current state. A planned agent creates a broader strategy before executing steps.

Neither architecture is universally better. The right choice depends on the task, risk level, latency requirements, tool reliability, and how much control developers need.

A reactive ReAct agent is like a skilled troubleshooter exploring a problem. A plan-and-execute agent is like a project manager creating a checklist before beginning work.

Reactive agents

Reactive agents operate step by step. They observe the environment, choose an action, receive the result, and continue.

observe → decide → act → observe → decide → act

This is useful when the environment is uncertain. For example, a browser agent searching for a recent article cannot know which result will be best until it sees the search results. A debugging agent cannot know the root cause until it inspects files and runs tests.

Strengths of reactive agents:

• Flexible
• Simple to implement
• Good for exploration
• Adapts quickly to observations
• Low planning overhead

Weaknesses:

• Can lose long-term direction
• Can repeat actions
• Harder to predict
• Harder to evaluate at the workflow level
• May stop before completing all subtasks

Planned agents

Planned agents create a strategy before acting.

goal → plan → execute steps → validate → finish

This is useful when a task has known stages. For example, generating a market research report, migrating a code module, or preparing a compliance summary benefits from explicit structure.

Strengths of planned agents:

• Better long-horizon coherence
• More inspectable
• Easier to approve before execution
• Good for workflows with required steps
• Supports progress tracking

Weaknesses:

• Higher latency and token cost
• Plans may be wrong or too rigid
• More engineering complexity
• May over-plan simple tasks

Decision matrix

A practical decision matrix can help:

Use direct response when:
- No tools are needed
- The task is simple
- The answer is stable and low-risk

Use ReAct when:
- The task needs one or more observations
- The path is uncertain
- The agent must adapt step by step
- The workflow is short or medium length

Use plan-and-execute when:
- The task has multiple dependent stages
- The user expects a complete deliverable
- Human review of the plan is useful
- The process must be auditable

Use a structured workflow when:
- The business process is known in advance
- Compliance or reliability matters
- Only certain paths should be allowed

Hybrid architectures

Many strong systems are hybrids. An agent may plan at the top level, then use ReAct inside each step.

Example:

Planner:
1. Inspect failing test.
2. Inspect related source file.
3. Propose fix.
4. Run tests.

Executor for step 1:
ReAct loop to locate and read test file.

Executor for step 2:
ReAct loop to inspect imports and related source files.

This gives the system both direction and flexibility.

Another hybrid approach uses deterministic workflow nodes around agentic nodes:

[Classify request] → [Agent research loop] → [Validate output] → [Human review if high risk]

This architecture is common in production because it limits where the model has freedom.

Example: choosing an architecture

Suppose you are building an AI assistant for internal engineering documentation.

Request 1:

What is feature flagging?

Use direct response.

Request 2:

Where in our docs do we explain feature flag rollout policy?

Use ReAct with document search and fetch tools.

Request 3:

Create a migration guide for replacing our old feature flag library.

Use plan-and-execute. The agent should inspect docs, identify old and new APIs, compare examples, draft a guide, and validate completeness.

Request 4:

Update the official migration guide and publish it.

Use a structured workflow with human approval before publishing.

Evaluation differences

Reactive agents are evaluated by looking at whether each action was appropriate given the current observation. Planned agents are evaluated by looking at plan quality, step completion, replanning decisions, and final outcome.

For ReAct:

Did it call the right tool at the right time?
Did it interpret observations correctly?
Did it avoid unnecessary loops?

For plan-and-execute:

Was the plan complete?
Were steps executed in the right order?
Did it replan when assumptions failed?
Did the final output satisfy the original goal?

Practical takeaway

Architecture is a control decision. Reactive agents maximize flexibility. Planned agents increase structure. Workflow agents maximize predictability.

The best architecture is the one that gives the model enough freedom to solve the task, but not so much freedom that the system becomes unreliable, expensive, or unsafe.