Ralph Overnight Builds — Progressive Curriculum Entry

A graduated path to unattended Ralph runs: start with a single bounded task, add a PROMPT.md spec file, add verification, and only then remove the human from the loop for overnight builds.

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Staged path from basic prompt → PROMPT.md spec → overnight Ralph run: start with a single bounded task, add a spec file, add verification, only then remove the human from the loop.
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Implementation note

When to use: you are tempted by overnight Ralph runs but have not run one before — this is the curriculum that gets you there without learning each failure mode the expensive way. How it works: a staged path where each stage adds one piece of rigor. Start with a single bounded task run under supervision. Then move the task definition into a PROMPT.md spec file. Then add verification, so done is machine-checked rather than asserted. Only after all three are solid do you remove the human from the loop and let it run overnight. Each stage exercises the discipline the next one depends on. Safety: the sequencing is the safety mechanism — unattended operation is earned last, after bounded scope, a written spec, and objective verification are already proven on supervised runs. Most overnight-loop disasters trace to a skipped stage. When you do go unattended, add the standard rails: iteration caps, budget limits, sandbox, branch.

Source: Claude Code Masterclass newsletter

More planning loops

loop-init, loop-audit, loop-cost CLI patterns

/ralphnew

Three starter CLI tools that turn loop design into a repeatable workflow: scaffold a loop with a goal, budget, and verify step; audit an existing loop design; and estimate cost before you run.

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Starter CLI tools: `loop-init` scaffolds a loop (goal, budget, verify step), `loop-audit` reviews an existing loop design, `loop-cost` estimates spend before running.
planningmedium risk

Ralph the PRD backlog

The canonical Ralph loop: each iteration starts fresh, reads the PRD and guardrails, ships exactly one backlog item end-to-end, and records what it learned.

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/loop start each iteration with fresh context: read PROMPT.md, prd.json, and .ralph/guardrails.md; pick the single highest-priority item in prd.json not marked done, implement it with tests, run the full check suite, commit and mark it done only if green; if blocked or a check fails twice the same way, append the lesson to .ralph/guardrails.md and move on; stop when every item is done or after 30 turns
planninghigh risk

Set agent continuation budget

/goalnew

Configure max turns before agent stops, preventing runaway loops and controlling execution cost.

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/goal budget <n Set max continuation turns
planninglow risk