Devtor

LLM ORCHESTRATOR

Overview01 Plan First02 Route Intelligently03 Execute & Learn
Overview
Prompt Optimization LayerTune prompts so cheaper models match production quality.Hybrid Model ArchitectureExpensive orchestrator delegates to cheap sub-agents. No wasted spend on simple tasks.Smart Model SelectionAuto-picks the best model per prompt, using expensive models only when needed.Model Limitation AwarenessKnows model limits — escalates or reroutes instead of hallucinating.
Granular Plan ModeGenerates detailed step-by-step plans when needed, and skips planning for simple tasks.Pre-Execution Token EstimationSee token usage and projected cost before build commands run.Token Budgeting SystemSet token budgets per session, task, or team — enforced before compute runs.Structured Plan OutputOutputs interactive plan.html — reviewable decisions, not markdown walls.
Smart Context ManagementOnly pass context relevant to the latest prompt — not the full session history.Context & Memory ControlAdd or remove context and memory to control what the model sees.
Interactive Think ModePause, redirect, or correct the agent mid-run — no full restart.Skill BuilderBuild skills with test and evaluation modes to benchmark and fine-tune behavior.CLI + Local Web IDEProvides a terminal CLI and localhost web IDE with embedded chat.AI Collaboration ModeShared agent sessions and handoffs — break out of solo AI silos.
Cross-User LearningIndexes resolved failures org-wide, like Stack Overflow for AI agent runs.Automatic Repository RulesGenerates repo rules from your codebase patterns on init.
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Capability

Interactive Think Mode

Interrupt an agent mid-execution. Redirect. Continue.

Summary

Pause, redirect, or correct the agent mid-run — no full restart.

The problem

Black-box agents run to completion before you can steer. Wrong assumptions waste minutes and tokens.

How Devtor solves it

Think mode streams reasoning steps to the terminal. Pause, inject corrections, or redirect scope — then resume without restarting the entire session.

Benefits

  • Visible intermediate reasoning in the terminal
  • Pause and redirect without full restarts
  • Fewer wasted runs from early misalignment
  • Human-in-the-loop control for high-stakes work

Use cases

  • Architecture decisions that need mid-run approval
  • Debugging agent loops that drift off-spec
  • Teaching junior devs how agents reason step-by-step

Part of the orchestration flow

03
Execute & Learn

Run once. Route smarter next time.

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Installation guide and CLI — coming soon.

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