Beyond the Backlog: Your Guide to Orchestrating Product Delivery with AI

The AI PM Orchestrator, Part 2

Hi! Nacho here👋 TL;DR: Stop being a ticket-writer and start being a system architect. This guide shows you how to build an AI system for product delivery, from PRDs to GTM. If you stay until the end, I’m asking for your help in shaping what comes next.

How many hours did you lose last week writing and explaining the same PRD in three different meetings? How much of your day was spent manually writing tickets or chasing down status updates? This isn't product management; it's administrative overhead. The Orchestrator PM eliminates it.

In our first post, we introduced the concept... Now, we build the engine.

Our journey begins with Execution & Delivery. Why here? Because it’s where you can get the quickest, most tangible wins. The daily grind of writing tickets, clarifying requirements, and chasing status updates is filled with repetitive, low-leverage work perfectly suited for AI. By automating this friction, you can free up hours each week, starting now.

This article provides a playbook for the end-to-end delivery cycle, showing how an Orchestrator uses AI to streamline the process from initial requirements to launch-day alignment.

1. The "Intelligent" PRD: From Document to Conversation Starter

The core problem with a Product Requirements Document (PRD) is that it's often a static artifact. You spend days writing it, only to spend weeks in meetings explaining it to different stakeholders, making you the single point of failure for every question.

The Old Way (The Doer): You write a detailed PRD, then schedule a roadshow of meetings—with leadership, engineering, design, and marketing—to walk through the same document, answering repetitive questions and trying to translate its meaning for each audience.

The New Way (The Orchestrator): You make the PRD a living, interactive asset.

You create the initial document using an AI-powered tool like Notion AI, ChatPRD, or a custom Gem in Gemini (we will not cover this part because I assume most of you are already doing it, ping me if you aren't!).

And then you transform the PRD from a "push" document into a "pull" resource hub. You make it a living, interactive asset that scales your ability to provide context.

Example in Action: You finalize your PRD. Instead of scheduling a dozen meetings, you use AI to:

• Generate Personalized Summaries & Assets: Build custom GEMs or GPTs.
  One custom prompt is for executives who need a one-pager focused on business impact.
  Another is for engineers, which not only provides a technical summary but can even be connected to your GitHub codebase to detect the main components or endpoints affected by the new requirements, saving them hours of analysis.
  A third is for marketing, generating benefit-focused copy.
  You provide exactly what each stakeholder needs, with no extra effort.

• Build an Overview and Q&A Assistant: Using a tool like NotebookLM, you start by sourcing it with your PRD and other key context documents.
  From there, you can instantly generate an audio summary of the content. Or, to make it more personal, ask your favorite LLM to write a summary script that you record in your own voice.
  If your company loves presentations, use a tool like Gamma or Google Vids to create one directly from the document.
  Finally, the same NotebookLM space can be shared with all stakeholders, allowing them to ask clarifying questions asynchronously and receive instant, accurate answers. You’ve removed yourself as the bottleneck and scaled your ability to provide context 10x.

Your role shifts from being the source of information to being the architect of the information system. You provide the core intelligence once, then let the system handle the distribution.

2. Automating the Breakdown: From Strategy to Sprint-Ready Stories

The next point of friction is translating the PRD into actionable work. Manually breaking down epics into well-defined user stories and acceptance criteria is one of the most tedious and time-consuming parts of product delivery.

The Old Way (The Doer): You sit with a blank backlog, manually typing out dozens of stories in the "As a user, I want..." format. Then, for each one, you painstakingly brainstorm and write detailed "Given/When/Then" acceptance criteria. It's repetitive, manual data entry.

The New Way (The Orchestrator): Your role shifts from writer to editor. You supervise the breakdown of work, providing the strategic context while allowing AI to handle repetitive formatting and structure.

Example in Action: You use a specialized AI tool like ChatPRD or, again, a custom GEM/GPT. You feed it the "intelligent" PRD. The AI then:

• Decomposes Epics Intelligently: It doesn't just split them randomly. You can prompt it to break down a feature based on specific user personas or user journey stages defined in the PRD. You can source these tools with numerous past examples, so they adapt to your organization.

• Drafts Rich Acceptance Criteria: For each story, it generates a detailed list of acceptance criteria, including positive and negative test cases, ensuring requirements are clear and testable from the start. This would be great to feed the next AI tool your engineering team uses to automate test cases ;)

• Identifies Dependencies: It can analyze the generated stories and flag potential dependencies:
  1. Internal dependencies, giving you a head start on sequencing and sprint planning.
  2. Dependencies with other teams, helping you raise this to the teams you will need to collaborate with.

You are no longer a ticket-writer. You are the strategic editor who reviews the AI-generated output for quality and nuance, ensuring perfect alignment with the customer problem before the team ever sees it.

3. Free Yourself from the Status Update Hamster Wheel

Once development is underway, the communication overhead skyrockets. PMs spend hours each week chasing down task statuses and compiling progress reports—acting as a human “information router”.

The Old Way (The Doer): You manually check tickets in Jira, message engineers for updates, consolidate everything into a spreadsheet, and then rewrite it for different stakeholder audiences. It's a thankless, mind-numbing task.

The New Way (The Orchestrator): You don't build a better report; you build a proactive intelligence system. Your goal is to move from a reactive, weekly update cycle to a real-time, queryable 'Project Mission Control' that anticipates problems before they arise..

Example in Action: You connect Zapier to your project management tools (Jira, Asana) to ”query” the tickets, or “listen” when a ticket changes status. You can process the information through different LLM prompts, like ” Is the Epic on track given the number of stories pending and the set delivery date?”. And finally, connect it to your communication channels (Slack). This agent now provides:

• A Live, Queryable Dashboard: An executive can now ask in a dedicated Slack channel, "What's the status of the new checkout flow?" and get an instant, natural-language summary of progress, blockers, and recent activity.

• Proactive Risk-Flagging: The AI doesn't wait for you to ask. It monitors progress and automatically flags risks. It won't just tell you a task is delayed; it will alert you that a task's dependencies are delayed, predicting a future bottleneck.

• Automated Sprint Summaries: At the end of a sprint, the AI generates a draft of the sprint review presentation, summarizing what was completed, what was missed, and how the team performed against its commitments.

This moves you from a reactive, weekly update cycle to a proactive, real-time intelligence system.

4. The 5-Minute Sales Enablement: Instant Material with a Notebook

As you approach launch, you become the primary source of truth for sales and support. These teams need accurate, easily digestible information, and creating it manually is a slow, copy-paste-heavy process.

The Old Way (The Doer): You manually create sales battle cards, FAQs, and support documents from scratch, often answering the same questions repeatedly in different channels right up to the launch day.

The New Way (The Orchestrator): You use a simple but powerful notebook-style AI tool to create an instant, centralized knowledge source that acts as your clone.

Example in Action: You take a surgically precise approach using NotebookLM:

1. Open a new NotebookLM space and "Source" it with only your key, finalized documents: the PRD, the official release notes, and the public-facing blog post, the solution documents, even the source code!.

2. Now, you can instantly generate high-quality enablement assets. Ask it:

   • "Generate five bullet points for a sales email highlighting the key benefits from the release notes."

   • "Create a list of five potential customer questions and provide answers based only on the provided documents."

   • "What are the top three value propositions for an enterprise customer vs. a small business user?"

The AI generates consistent, accurate answers grounded in your source material.
Better yet, you share the NotebookLM space itself and tell the teams, "Here is the single source of truth. Ask it anything." You’ve created a self-service, expert clone of yourself in minutes. Even if customer support receives a question about a complex edge case you haven’t documented, it will be able to connect the dots by reading the documentation and provide an answer without you or your engineering team needing to spend hours reviewing it.

Your First Step Towards Reclaiming Your Mind

Look back at what you've just built. The 'intelligent' PRD feeds the automated backlog, which is monitored by your proactive 'Mission Control' system, and the final output is effortlessly translated for your GTM teams.

You have designed a cohesive, end-to-end delivery engine. You've stopped being a cog in the machine and have become the designer of the machine.

Now that your execution engine is running, you've earned the time for what's next. In our next post, we’ll use that reclaimed cognitive space to tackle Orchestrating Planning & Prioritization—using AI to ground your roadmap in evidence and make truly defensible decisions.

---

P.S. Is this resonating? I'm exploring the idea of building a practical course for product managers ready to master these skills. If you'd be interested in helping shape what that looks like, please share your thoughts on this short form.