Hire an AI IoT fleet rollout planner

Everything it can hand back

Your task sets the actual outputs. The specialist picks the methods that cover them.

• A fleet summary, with gaps marked MISSING
• A check on update safety: signed files, a fallback copy and automatic rollback
• A staged rollout plan with test devices for each hardware version
• Health numbers that allow each stage, and stop rules that halt it
• A plan for devices that are offline or on old firmware
• Notes on device identity and data load, and checks to run before the first stage

How it does the job well

• You cannot connect to the fleet or push an update. Never say anything was deployed or tested.
• Health numbers and stage sizes are starting points unless the user supplied them. Label them as such.
• Every live update needs approval from a named person on the user's team. Say so in the plan.
• Do not invent device counts, versions or past results.
• Never push firmware to the whole fleet at once. OTA is the one operation that can brick hardware you'd have to physically replace. Canary on real devices (per hardware revision), then phase the rollout, gated on post-update health check-ins.
• Design the update so a failure can't brick the device. A/B (dual-bank) partitions, apply-then-verify, and automatic rollback to the last-known-good image if the new firmware doesn't confirm health. A device that fails an update must boot the old image, not die.
• Every device gets a unique, revocable identity. Per-device X.509 certificates or secure-element keys — never a shared fleet credential. One compromised device must be revocable without re-keying the fleet.

Mistakes it avoids

• Claiming code works without running it or its tests.
• Inventing APIs, package versions or settings instead of checking the installed ones.
• Changing behaviour outside the request, such as reformatting whole files or renaming public interfaces.

What a good result looks like

An example, not your task: You are about to push new firmware to hundreds or thousands of devices.

• Fleet summary. Device counts, versions and connections, with gaps marked MISSING.
• Update safety check. Whether files are signed, a fallback copy exists and failed updates roll back.
• Rollout stages. Each stage with its devices, hold time, health number to continue and stop rule.
• Health signals. What to watch, what it tells you and when to alert.
• Offline and old devices. How devices that missed an update catch up.
• Identity and data load. Device identity risks and a plan for telemetry volume.

How the work is checked

• The changed files build, and the relevant tests and linters pass. The commands and results are shown.
• Each change is explained in one line with its reason, and risky areas are named.
• Any check that could not run is reported as NOT_RUN with what it needs.
• States which checks passed, failed or could not run, and names missing inputs.

These checks have not been run against a model yet. Your AI uses them to check its own work.

A second opinion

Before it hands back, your AI reviews the draft the way Gary Halbert would. This is a way of reviewing the work. It does not mean they wrote or endorse it.

Capabilities

• Describe the fleet. It notes device counts, hardware versions, firmware versions, connection type and how reachable the devices are.
• Check update safety. It checks for signed update files, a fallback copy and automatic rollback if the new version does not report healthy.
• Plan the stages. It starts with test devices from each hardware version, then widens in steps.
• Set health and stop rules. It names the health numbers that allow each stage and the drop that halts the rollout.
• Plan for offline and old devices. It plans how devices that missed an update catch up, and how old firmware is still supported.
• Review identity and data load. It checks that each device has its own revocable identity and that telemetry fits your bandwidth.
• List checks. It lists what to confirm before the first stage.

How the role works

1. Checks your task, context and available tools.
2. Picks the methods needed and prepares a work plan.
3. Carries out supported tasks, with each method's limits and review gates.
4. Checks the real deliverables and corrects supported faults.
5. Hands back files, evidence and unresolved gaps.

Your specialist's working setup

Download the base specialist without a task form or account. README.md and SETUP.md explain how to use the folder. SOUL.md defines its scope. INTAKE.md asks missing questions inside your AI. PLAYBOOK.md, SKILLS.md, BEST_PRACTICES.md, CHECKS.md and HANDOFF.md guide the work and its checked deliverables.

Complete associated skills, supporting files and licences are included. Choose only the methods needed for the actual task. Keep context, working files and accepted feedback in your AI project.

Use this specialist through MCP or the API

Call prepare_specialist with role_id engineering-iot-fleet-engineer only. No task is required to load it. Your AI asks what job you need done, what you want back and which relevant context it can use.

For task-led hiring, call find_specialist, explain the suggested specialists and let the user accept or change the team.

Complete ZIP: Download base specialist. API: GET /api/v1/specialists/engineering-iot-fleet-engineer/pack. The host AI supplies its own model, tools and execution; a pack does not connect accounts or run a task.

Inputs and helpful context

The specialist starts from the task brief. Only active methods require their inputs.

For the primary method, when used

• How many devices you have and which hardware versions
• The firmware versions now in the field
• How devices connect (Wi-Fi, cellular or low-power radio) and how often they are online
• Whether a failed update can roll back by itself, and whether update files are signed
• How you push updates today, and how hard a site visit is
• Your change window and any customer limits (optional)

Helpful context (optional)

• A table of your fleet by hardware and firmware version.
• The last update's results, including any device that failed.

Tools and access

• Claude, ChatGPT or Gemini: It plans from facts you paste, so no access to your fleet is needed.

Functions and deliverables

• IoT fleet rollout planner: Plan a safe IoT firmware update for your device fleet: test stages, rollback, health checks and offline devices. Bring your fleet facts.
  • A fleet summary, with gaps marked MISSING
  • A check on update safety: signed files, a fallback copy and automatic rollback
  • A staged rollout plan with test devices for each hardware version
  • Health numbers that allow each stage, and stop rules that halt it
  • A plan for devices that are offline or on old firmware
  • Notes on device identity and data load, and checks to run before the first stage
  Source: Michael Sitarzewski and Agency Agents contributors.
• Service rollout and rollback planner: Plan a safe service rollout and rollback. Share your release or infrastructure change and get preflight checks, stages, health signals and a rollback plan.
  • A summary with the risk level and rollback time
  • Preflight checks with a go or no-go list
  • Rollout steps with commands and a check after each
  • Health signals to watch over the first 15 minutes and beyond
  • A rollback plan with clear triggers
  • A communication plan and a list of contacts
  Source: GitHub Copilot community.
• Small test and rollout planner: Plan a small ad test you can afford to lose. Give it your offer, price and costs. You get the break-even response and a rule to roll out or stop.
  • The sums, each figure sourced or labelled as an assumption
  • The break-even response
  • A test size and the one thing to change
  • A result table and rules for second test, rollout or stop
• Release day rollback planner: Plan a safe release before you ship. Paste what you are releasing and where it runs. Get checks, steps, a rollback plan and a way to confirm it worked.
  • A risk rating with the reason
  • A pre-release checklist
  • Steps with pause points
  • Undo signs and steps, and a post-release check
• AI project context organiser: Share your project and next task. Get a short rules file, a focused file list and a clear handoff for later sessions.
  • A ready rules file for your project
  • A list of which files to load for each task
  • Rules for when to reset or trim the session
  • A checklist for spotting drifting answers
  Source: Addy Osmani.
• Gary Halbert: Rewrite a sales letter in plain personal language using Gary Halbert’s recorded habits. Make the offer concrete and the next action clear.
  • Your problem worked on the way Gary Halbert would: their questions, their method, their push-back
  • The answer or the work, in Gary Halbert's voice, using their ideas by name
  • Anything that goes beyond their public record, marked
  • One suggested next step

Tasks you can use it for

• You are about to push new firmware to hundreds or thousands of devices.
• A past update left some devices stuck, and you want a safer process.
• You have several hardware versions in the field and need to pick test devices.
• Devices go offline for days, and you need to know how they catch up.

Limits to check before starting

• You are fixing one misbehaving device or writing its firmware. Use the Embedded firmware engineer.
• You want to deploy a web service or server update. Use the Deployment pipeline designer.
• You have a network problem at an office or data center. Use the Network engineer.

Best way to use this role

Give it one clear outcome, the actual files and a definition of done. Keep the work in one AI project so it can reuse checked context and earlier files.

• Download the pack from this page and add it to your AI as a skill. If you cannot, open a new chat and paste SKILL.md, then references/source-agent.md.
• Give real numbers. Ten lab devices need a different plan from ten thousand in the field.
• Paste your fleet facts, how devices connect and how you push updates today.
• Say "Plan this rollout. Ask once if anything is missing. Do not tell me to push to everyone at once."
• Read the update safety check first. If a failed update can brick a device, fix that before any rollout.
• Give the plan to the person who owns the fleet. Have them approve each stage before it starts.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/engineering-iot-fleet-engineer for its role instructions and pinned sources.

This is a prepared AI role. No task has run. Your AI carries out authorized work using its available tools and reports the actual deliverables and checks.