Safe Long-Run Mode (GPT-5.4 + Claude)#

Use this skill for tasks that may run long, span multiple systems, or risk losing progress if interrupted.

Core rule#

Do not run long tasks as one monolithic attempt. Split into phases, write checkpoints, and keep the work resumable.

Model selection#

Use GPT-5.4 for:

• coding
• docs
• research
• file-heavy transformations
• multi-agent delegated work
• repetitive build tasks
• long internal work where cost and throughput matter

Use Claude for:

• strategic judgment
• sensitive decisions
• nuanced synthesis
• client-facing polish
• brand voice refinement
• high-trust orchestration

Default to GPT-5.4 first. Escalate to Claude only when the task actually benefits from higher-quality judgment or tone.

Operating procedure#

1. Scope before acting#

Before starting, decide:

• what the final deliverable is
• which systems/tools will be touched
• what can fail or throttle
• what must be saved after each phase

2. Break work into phases#

Use phases such as:

1. gather / inspect
2. plan / write brief
3. execute / edit / build
4. validate
5. deploy or report

At the end of each phase, write artifacts to disk.

3. Always checkpoint#

For long tasks, save progress in files:

• draft outputs
• notes
• reports
• partial results
• tracker entries
• checkpoint summaries

Prefer a resumable workspace state over a perfect one-shot run.

4. Isolate long work#

Use subagents when:

• the task will take more than a few tool calls
• multiple files/systems are involved
• external APIs are involved
• failure should not pollute the main session
• specialized work can be delegated cleanly

5. Throttle external systems#

When interacting with Azure, Graph, Orgo, messaging providers, registries, websites, or any external API:

• batch reads when possible
• avoid tight polling loops
• serialize risky writes
• respect retry/backoff
• avoid one-item burst loops when a bulk operation is possible

6. Prefer resumability over perfection#

The goal is not "never fail." The goal is: if interrupted, resume with minimal loss.

System-specific guidance#

Azure / cloud control planes#

• validate auth first
• create foundational resources first
• verify after each layer
• log resource names/IDs
• do not chain long destructive commands blindly

Browser / Orgo / GUI automation#

• use explicit goals and stop conditions
• capture screenshots at checkpoints
• bound retry counts
• save artifacts locally
• prefer API/CLI over GUI when equivalent exists

Coding / documentation work#

• create a brief/spec first for complex tasks
• write files in chunks
• validate after each major change
• leave notes for resume if work is unfinished

What to tell the user#

When relevant, explain that safe long-run mode means:

• cheapest adequate model
• phased execution
• saved checkpoints
• subagent isolation
• controlled API usage
• resumable progress

Failure handling#

If a long task is interrupted:

1. summarize completed phases
2. point to saved artifacts
3. identify exact next step
4. resume from checkpoint rather than restarting

References#

• Read references/checklist.md for a reusable pre-flight checklist and model routing matrix.