Manual continue prompting -> goal-scoped agent loops
Long-running agent work is moving from manual continue prompts toward explicit goals, limits, subagents, schedules, and verifiable completion.
Tectonic shift
Before: Human repeatedly nudges one long chat forward After: Agent loop runs against an explicit goal, budget, checks, and stop condition Current stage: emerging This New Runtime record is an evidence-linked retrieval unit. Use its canonical page, machine-readable representations, dates, scope, and public source URLs to verify the claim before reusing it.
Source ledger
Publishable sources attached to this record.
| # | Source | Role | Public status |
|---|---|---|---|
| 1 | code.claude.comsource | primary receipt | source_urls |
| 2 | code.claude.comsource | supporting receipt | source_urls |
| 3 | code.claude.comsource | supporting receipt | source_urls |
A long-running agent does not become more reliable when the user says “keep going”. It needs a goal, budget, acceptance checks, resumable state, and a visible stop condition.
Evidence
The related pieces on Claude Code loops, cost controls, and AI-native team stages show the same pattern: agent autonomy is moving from the prompt into the operating model.
Bottleneck
The main bottleneck is not the model, but controllability: which actions are allowed, where the human confirms the result, how the loop knows that work is finished, and how the system recovers after failure.