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How to run several coding jobs in parallel with a token budget with Radiant

Build a graph of jobs where only real dependencies wait, and stop a repeating graph at a token budget.

Who it is forA developer splitting a feature into independent stages who wants them done faster and within a cost limit.

The problemRunning coding jobs one after another wastes time when many of them do not depend on each other.

The outcomeA graph where independent steps run at the same time, with tokens and dollar cost shown for each step and round.

What you need first

  • A Mac. The release DMG is for Apple Silicon.
  • Either a cloud model API key (for example Anthropic or OpenAI) or Ollama or LM Studio running on the Mac.
  • A project folder to point the agent at.
  • npm, only if you build from source instead of using the DMG.

Steps

  1. Create a graph with one step for each job, such as a docs update, a test addition and a refactor.
  2. Tick only the steps that a job actually reads. Everything left unticked runs at the same time.
  3. For a repeating graph, set a token budget so it can stop before it overspends.
  4. Start the graph and open the run view to see tokens and dollars at list price for each step and round.
  5. Check the output of each step in the Activity panel before you merge the results.

Prompt for your agent

Using the repo templetongroup/radiant, build a graph in a Radiant session on <project folder> with three independent jobs and run it. Expected output: a run view listing the tokens and dollar cost for each job. Verify that the independent jobs started at the same time, not one after another.

Caveat. Dollar figures in the run view are estimates at list price, not your actual provider bill.

Use this in your AI agent

Ask your agent

Using the Deduped MCP, get the setup steps for templetongroup/radiant and "Run several coding jobs in parallel with a token budget"

Add Deduped to Claude Code once

claude mcp add --transport http deduped https://dedupedai.com/mcp

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