Your AI Agent Configuration Should Be Task-Aware, Not Always-On
Default: thinking mode enabled.
Result: you're paying for reasoning on tasks that don't need it.
The waste pattern
You're running a straightforward refactor. Rename a variable, update the references, run the tests. The model sits there, thinking. Extended reasoning tokens pile up. The task that should take thirty seconds takes two minutes.
The output is the same as it would have been without thinking. Except now you've paid for the cognitive overhead of a model reasoning through a problem that didn't require reasoning.
This is the thinking mode trap. It feels prudent to leave it on. More thinking equals a smarter result, right?
Not when the task is already within the model's capability envelope.
The configuration principle
Thinking mode is a tool, not a default. Some tasks benefit from extended reasoning: complex architectural decisions, tricky debugging where causality chains are non-obvious, multi-step refactors that require maintaining state across files. Most tasks do not.
The practical split depends on which model you're using and what you're asking it to do.
"If it's something that can be achieved without thinking, then sure, you should go without thinking. Because the thinking is just going to waste more tokens and take a lot longer to complete the task."
Hannes Rudolph,
The question is not "should I use thinking mode?" The question is "does this specific task benefit from extended reasoning?"
The model-aware heuristic
Different models have different capability baselines. A task that requires thinking on a smaller model might complete without thinking on a more capable one.
"When I run Opus, I don't do thinking. When I run Sonnet, I use minimal thinking."
Guest,
The pattern: more capable models need less reasoning scaffolding. Their base capability already handles the task. Adding thinking mode just adds cost and latency without changing the output.
This means your configuration should vary by model, not just by task type. Running Opus with thinking enabled by default is paying twice for capability you already have.
The audit checklist
Before running a task, ask:
-
Is this task within the model's base capability? If you're using Opus for a straightforward refactor, you probably don't need thinking.
-
Does the task require multi-step causal reasoning? Debugging a race condition? Thinking might help. Renaming a function? It won't.
-
Have I run this task type before without thinking? If the output quality was fine, keep it off.
-
Am I paying for latency I don't need? Thinking mode adds time-to-first-token. If you're iterating quickly, that overhead compounds.
The goal is not to eliminate thinking mode. The goal is to use it selectively, on tasks where extended reasoning actually changes the output.
Always-on vs. task-aware configuration
| Dimension | Always-On Thinking | Task-Aware Configuration |
|---|---|---|
| Token cost | High - pays for reasoning on every task | Optimized - reasoning only when beneficial |
| Latency | Consistent delays on all tasks | Fast for simple tasks, slower only when needed |
| Output quality | No improvement on simple tasks | Same quality, matched to task complexity |
| Model utilization | Ignores model capability differences | Adapts configuration to model strengths |
| Iteration speed | Slow feedback loops | Fast iteration on routine work |
Why this matters for your workflow
For an engineer running 20-30 tasks per day, the difference between "thinking on everything" and "thinking on 5 tasks that need it" compounds.
Token costs drop. Latency drops. The tasks that need reasoning still get it. The tasks that don't finish in the time they should have finished in the first place.
The configuration shift is small: audit which task types benefit from thinking, then adjust your settings accordingly. Most coding workflows, especially on capable models, complete without it.
How Roo Code enables task-aware configuration
Roo Code supports task-aware agent configuration through its BYOK (bring your own key) model. Because you connect directly to your LLM provider, you control exactly which model runs each task and whether thinking mode is enabled.
The key pattern: configure your agent per task type, not globally. Roo Code's mode system lets you set different model configurations for different workflows. Run Opus without thinking for quick refactors. Enable extended reasoning only when you hit complex debugging or architectural decisions.
This approach lets developers spend tokens intentionally for outcomes rather than paying a blanket reasoning tax on every interaction with the agent.
The configuration change
If you're using Roo Code with Opus, try disabling thinking mode as your default. Turn it on explicitly when you hit a task that stalls or produces low-quality output without it.
Track which tasks needed thinking. The list is probably shorter than you expect.
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