The Product Manager's Guide to AI-Powered Productivity: Principles & Practice
A framework for integrating AI into your product management workflow without losing the human touch
The landscape of product management is undoubtedly impacted by AI. Product managers are exploring how to implement AI into their products, where possible, and leveraging the tools in their day-to-day workflows.
How does AI tie into basic productivity?
Core productivity principles
One main objective of productivity is to have an underlying system or method of organizing actions and work into some kind of meaningful output.
Most people are driven toward being more productive to try to increase their output or just maintain sanity in demanding situations.
It is important to remember that productivity principles are simple:
Getting items organized
Establishing a simple system
Periodic reviews of this system and way of organizing things
I won’t talk here about how to create these systems and get organized as much has been written on this topic and there are countless ways to accomplish this.
I will, however, share a couple of key ideas that might be helpful:
Don’t overthink it - If you have something that works for you now, great. If not, start with the simplest way to accomplish your goal.
Try new things - If listening to a certain type of music helps you while you work, do it. If not, and you prefer to work in silence, so be it.
Find something that works for you - Do you have a go to productivity system? A few systems: Getting Things Done, working in Sprints, Shape Up, or Ivy Lee Method?
How does productivity work for product managers in an AI-enabled world?
Leveraging AI tools for productivity
Context is king when it comes to working effectively with AI. The underlying models that have been built over time are amazing and the vast information they understand is immense.
That being said - for you to get the maximum value out of working with AI technology, such as ChatGPT, Claude, Gemini, Microsoft Copilot, etc. - you need to share context about what you are trying to solve.
Quick thought on confidentiality
Be aware of confidentiality rules for your current employer or if you are a founder or business owner, be aware of the privacy policies of the AI tools you leverage.
Mainstream AI products have built in privacy tools and settings where you can adjust and opt-out of training on your content. Here is some information on ChatGPT’s opt-out as well as Claude’s opt-out, for example.
How to share context with AI
First, what do I mean by ‘context’? It might help to think of it this way, what do you need to share with your AI copilot to help you accomplish the result you are looking for?
Artificial intelligence and machine learning models can comprehend a vast amount of context quickly. That certainly is not a challenge. However, to give you precise feedback on what you are working on, it helps to understand the specific context in which you are chatting, or talking via voice, about.
Organize with Projects
In the last several months major AI tools ChatGPT and Claude have introduced ‘Projects’. More details on ChatGPT Projects and Claude Projects.
The Projects feature is available to paid subscribers for both ChatGPT and Claude. I imagine in the future, this could be something that they would open to free users, but for now, it is gated.
What are some of the advantages of using Projects to organize your work?
Built in context - When you use the projects functionality built-in to these AI tools, chats you engage in within the project understand and refer to the information you’ve shared.
Organization and structure - Without using the projects structure it can become challenging to manage and recall many chats.
Product management work typically spans over weeks, months, and even years. Being able to organize your AI chats within projects helps make it more streamlined to go back and refer to the information you might need to recall later.
What context should you share?
This is up to you, however, one fitting example that resonates with me, is to think of onboarding AI like a new team member on your team. This was mentioned by
in a podcast episode recently with and .Onboard AI like a new teammate on your team
Some ideas of things you can share:
Key knowledge documents
Product roadmap
Product vision
Visuals for prototyping
What if you don’t have access to ‘Projects’ since it is only for paid users currently?
You can still attach documents to individual chats with most AI providers. This can still allow you to ‘onboard’ your AI copilot to understand the context of what you are trying to solve for.
Integrating AI into existing workflows
As a product manager, you are working to drive specific business outcomes while ensuring customer-centricity stays at the center of what is delivered.
To do this, while balancing multiple priorities, engaging cross-functionally and communicating often, how do you balance this with the deep work you need to do?
Map out some of the common things you work on, some of these could be roadmaps, strategy, planning meetings, customer interviews, discussing design mockups, and reviewing data.
How can you integrate AI into these workflows?
It depends on your situation, however, here are a few ways to get started.
Brainstorming and ideation
Enhanced meetings (pre- and post-meeting)
Organization
Let’s break these down further.
1. Brainstorming and ideation
If you have shared enough context with the AI agent and copilot that you are collaborating with, you can quickly brainstorm and ideate on many topics.
This can range from how to handle a particular situation you are dealing with, such as how to communicate with a specific stakeholder on a topic. Also, you can work with your AI agent to act as a sounding board for some visionary ideas you might have for the product you are responsible for.
You would be surprised at some of the detailed input you can get.
2. Enhance meetings
Taking hand-written or typed-out notes during meetings is a great way to stay engaged. But do you really want to have to write down every single takeaway?
This is where AI copilots can give you a major advantage in helping you ensure that important actions and takeaways are captured from a virtual video meeting.
By sharing a transcript with an AI tool, you can quickly create a summary and key takeaways.
What if you are not in a virtual meeting? The notes you take, no matter how messy, can be cleaned up quickly with an AI agent’s assistance. You can share the notes and ask for a cleaned-up version.
This is perfect for situations where you want to share the notes with the audience but didn’t want to or have the time to clean the notes up yourself.
3. Organization
Do you feel like you have a million projects and things you are working on all at once? I feel your pain. Most people work more hours to get more done. This isn’t sustainable over the long term and could have an impact on your productivity and well-being.
By working with an AI agent, you can organize your projects, tasks, and to-dos into meaningful action plans and strategies.
How can you do this?
Create separate ‘Projects’ or chats for different initiatives
Prioritize projects by impact
Let AI help you with the mind-numbing work
Voice integration is a powerful way to communicate with AI
The major AI tools have voice integration built in. This can be one of the most powerful ways to communicate a large amount of context in a short amount of time to your AI copilot.
You can absolutely type out all the details, but experiment with them, and try the voice integration feature.
The key to remember - the more context the better. Voice to text is one of the easiest ways to share a lot of contexts in a short amount of time.
Mac and Windows both have built in voice to text features that you can leverage as well. You can use those in any window that allows for text input, so it can also be used within AI if you prefer not to use the voice integration, or if for some reason, it doesn’t offer it yet.
Some use cases for voice integration with AI:
Quick brainstorming session
Meeting note dictation
Writing and improving an email or message
Task list creation
Some best practices and considerations
The possibilities of leveraging AI to boost your productivity as a product manager are exciting. There are some things you may want to consider as you dive deeper.
Recap of the data security implications
Remember to review company AI usage policies.
Understand data usage and retention policies for AI tools.
Check the training opt-out settings.
For sensitive topics, consider using generic examples instead of live data.
Sanitize sensitive information. Don’t put sensitive data into an AI tool.
Set yourself up for success, with some simple steps
When working with an AI copilot, remember the principles:
Share enough context to help the AI understand what you are trying to solve. The projects feature of AI tools can help organize this.
Experiment with your own workflows and where it helps you best. While the tools and models of AI can work across many aspects of our lives, find your best flow.
Never neglect or forget the important human aspect of doing business. Engaging with other team members cross-functionally is important. Human intuition is an amazing thing.
Don’t over-rely on AI suggestions. You can rely on your own intuition. AI is an enabling technology to help increase your capacity.
Implementing AI: Putting it all together
One of the best parts about where we are leveraging AI tools in our roles in product management is that we are still early.
Yes, advancements happen weekly, and automation with AI is becoming increasingly better.
But at the same time, ChatGPT was only released publicly 2 years ago.

Imagine where we will be in another 2 years from now.
What are the next steps?
Set up your AI tools by sharing context on what you are working on
Create some basic templates you can use - leverage AI to help you build them
Work with your AI copilot as needed
Experiment with different ways of working with AI agents.
Integration AI tools into product management workflows is a great way to be more productive while still driving desired business outcomes for the business and driving a positive outcome for the customer of your product.
I’d love to hear more about how you leverage AI into your daily workflows. We can all learn from each other.