Hire an AI implementation brief writer

Everything it can hand back

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

• A short explanation of the problem and the main design ideas behind the fix
• A risk review with at least three ways the plan could fail
• A list of what is out of scope for this change
• A file list marked new, change or delete, each with one reason
• A test list and a rollback path

How it does the job well

• Write no application code. Short config or command examples inside the plan are fine if the user needs them.
• Do not praise a weak plan. If the shared details are thin, say so in the risk review.
• Do not claim any test passed or any file was read that the user did not share.
• Actions that change live systems, delete data or spend money need the user's clear yes. Put them in the plan as approval points.
• Read the existing code, its conventions and its tests before changing anything. Match the project's patterns.
• Make the smallest change that fully solves the request. Keep unrelated refactors out.
• Reproduce a bug before fixing it, and add a test that fails without the fix.

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 change a database, an API or a core module and want the risks written down first.

• Concept primer. The core problem, the design ideas that apply and how well-known systems handle the same thing.
• Risk review. At least three ways the plan could fail, what else it could break and what is out of scope.
• Blueprint. A diagram of the main parts and a file list marked new, change or delete, each with a reason.
• Validation. Tests to run, edge cases and the manual checks a person does before accepting the work.
• Rollback. The steps to undo the change and how the system behaves if a dependency fails.
• Assumptions and gaps. Everything the agent could not verify, so you can check it before work starts.

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 Margaret Hamilton and John Carmack would. This is a way of reviewing the work. It does not mean they wrote or endorse it.

Capabilities

• Check the ground truth. It reads the project details you share and lists what it could not verify as assumptions.
• Explain the problem. It states the core problem, the design ideas that apply, and how well-known systems solve the same thing.
• Attack the plan. It looks for weak assumptions, what else could break, and risks from timing, permissions and outside services.
• Fence the scope. It lists the features and clean-ups that are not allowed in this change.
• Write the blueprint. It lists each file as new, change or delete, and draws how the main parts connect.
• Plan the proof and the exit. It lists tests, manual checks and the steps to roll the change back.

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 specialized-master-plan-architect 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/specialized-master-plan-architect/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

• The change you want, in a few plain sentences, and why
• How your project is built, such as a file tree and its package or config files
• What must not change in this work (optional)
• Known problems, past outages or risky areas (optional)
• Who will do the work, such as a person or an AI coding tool (optional)

Helpful context (optional)

• The output of a file tree command for your project.
• Your main config files, such as package.json or requirements.txt.

Tools and access

• Claude, ChatGPT or Gemini: Any of them can read a file tree and config files. Use an AI that can open your project files for a plan based on the real code.

Functions and deliverables

• Implementation brief writer: Turn a software change into a written implementation plan with risks, files to change, test steps and a rollback path. No code is written.
  • A short explanation of the problem and the main design ideas behind the fix
  • A risk review with at least three ways the plan could fail
  • A list of what is out of scope for this change
  • A file list marked new, change or delete, each with one reason
  • A test list and a rollback path
  Source: Michael Sitarzewski and Agency Agents contributors.
• Software package upgrade planner: Get a staged plan to move one package to a new major version, with what will break, a test for each step and a way back if it fails.
  • A list of likely breaking changes, each with its source
  • A table of which other packages must change first
  • Numbered upgrade stages, one major step each
  • The tests to pass before each next stage
  • A return point for every stage
  Source: sickn33.
• AI coding task brief writer: Describe the change you want. Get a handoff note with scope, checks and stop rules for a coding agent.
  • A handoff note
  • Scope and stop rules
  • Checks the agent must pass
  • A review path for the result
  Source: RampStack.
• Code change report writer: Share a completed coding task and its evidence. Get a clear record of what changed, why and what was actually checked.
  • A titled write-up with a short overview
  • A file-by-file list of changes
  • Before and after code snippets
  • A verification section with build and test results
  Source: bear2u.
• 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.
• Margaret Hamilton: Review a system failure plan using Margaret Hamilton’s recorded approach. Check handoffs, priorities, warnings and what happens when people make mistakes.
  • Your problem worked on the way Margaret Hamilton would: their questions, their method, their push-back
  • The answer or the work, in Margaret Hamilton's voice, using their ideas by name
  • Anything that goes beyond their public record, marked
  • One suggested next step
• John Carmack: Find a bug, slow step or excess scope through John Carmack’s recorded approach. Follow the actual run, measure first and expose hidden state.
  • Your problem worked on the way John Carmack would: their questions, their method, their push-back
  • The answer or the work, in John Carmack'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 change a database, an API or a core module and want the risks written down first.
• A teammate or an AI coding tool will do the work, and you want a plan to hand over that sets the limits.
• You inherited a codebase and want to understand why it works as it does before you change it.
• You want a second view that challenges your plan, not one that agrees with it.

Limits to check before starting

• You want the code written. Use the Full stack developer.
• You are choosing between designs and want decision records. Use the Software architect.
• You want a quick prototype with a small scope. Use the Software prototype designer.
• You have no project files or goal to share. The plan would be guesses.

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 and add it to your AI as a skill. If you cannot, paste SKILL.md and then references/source-agent.md into a new chat.
• Paste your goal and your project details. A file tree and the package or config files are the minimum. Say MISSING for anything you cannot share.
• Say "Write the plan. Do not write code." Your AI asks once for anything it needs.
• Read the risk review first. Check each risk against what you know about your project, and correct any wrong assumption.
• Ask for a revised plan, then give the final plan to the person or tool doing the work. Ask them to stick to the file list.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/specialized-master-plan-architect 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.