Product Demise/Sunsetting AI Prompts for PMs

Quick Answer

We help Product Managers master the complex art of product sunsetting by leveraging AI to transform a risky, multi-week process into a data-driven, strategic workflow. This guide provides a comprehensive framework for decommissioning features, from establishing a defensible rationale to crafting empathetic user communications that preserve trust. Our goal is to turn a dreaded task into a hallmark of disciplined product leadership.

The Art of Product Goodbye

Every Product Manager remembers the thrill of a launch day. The metrics dashboard glowing green, the user feedback pouring in, the team celebrating a hard-won victory. But what about the day you decide to turn a feature off? That’s a different kind of adrenaline, isn’t it? It’s a conversation most of us would rather avoid. We pour our hearts into building, so the idea of dismantling feels like a step backward. Yet, in my years of managing products, I’ve learned that the ability to gracefully sunset a feature is not a sign of failure—it’s the hallmark of a mature, disciplined product leader.

The Hidden Challenge of Product Sunsetting

This is the unspoken challenge of our role: while new features get the spotlight, managing their end-of-life is equally vital for long-term product health and user trust. Think about it. A poorly managed sunsetting process can create a churn avalanche, damage your brand’s reputation, and leave a tangled mess of technical debt for your engineers. I once saw a company lose 15% of its user base in a single quarter because they announced a feature deprecation with a one-month notice and no clear migration path. The trust they had spent years building was shattered overnight. Sunsetting isn’t just a technical task; it’s a strategic exercise in user empathy and risk management.

Why AI is Your Strategic Partner in Decommissioning

This is where AI becomes your most valuable co-pilot. Let’s be clear: AI won’t make the final “kill” decision for you. That requires your strategic judgment. But it can transform a daunting, multi-week process into a manageable, data-driven workflow. AI can accelerate the tedious parts, allowing you to focus on the high-stakes strategy. It can sift through terabytes of user data to identify who will be most impacted, draft empathetic and clear communication templates for different user segments, and model the potential revenue or churn risk of the decision. It turns a gut-feel announcement into a calculated, strategic move.

What This Guide Will Cover

In this guide, we’ll walk through a comprehensive framework for decommissioning a feature, using AI prompts to augment every step. We’ll start by establishing the “why” behind the sunset, ensuring the decision is defensible. Then, we’ll move into identifying and assessing the impact on your user base. Finally, we’ll craft a flawless communication and migration plan that preserves user trust, even as you say goodbye. This isn’t about just removing code; it’s about strategically managing your product’s evolution.

The “Why” Before the “Wipe”: Defining the Sunset Rationale

Before you write a single line of deprecation code or draft a user-facing email, you need to build an ironclad case for why this feature needs to die. It’s the most critical step, and it’s where most sunsetting projects fail—not because the code is hard to remove, but because the justification is weak. A poorly reasoned sunset feels arbitrary to users and erodes trust, while a well-communicated, data-backed decision is seen as a sign of a healthy, focused product. You need to move from a gut feeling to a defensible business decision.

Identifying the Core Drivers for Decommissioning

The “why” isn’t a single reason; it’s a combination of factors that, when viewed together, point to an unavoidable conclusion. In my experience, these drivers usually fall into four key buckets. Your job is to identify which ones are at play and quantify their impact.

• The “Ghost Town” Problem (Low User Adoption): This is the most common driver. You launch a feature with high hopes, but over time, the data reveals a stark reality: almost nobody is using it. We’re not talking about a 10% drop-off; we’re talking about a feature that sees daily active users in the double digits out of a user base of thousands. It’s a “build it and they will come” scenario that never came.
• The “Resource Sink” (High Maintenance Costs): Some features are like old cars; they look fine but are constantly in the shop. This feature might be built on a legacy framework that requires specialized knowledge, or it might be so buggy that it consumes 20-30% of the engineering team’s capacity just to keep it running. That’s capacity that isn’t being spent on innovation or fixing core issues.
• The “Dinosaur” Effect (Technological Obsolescence): The world moves fast. A feature might have been a brilliant solution five years ago, but now it’s been replaced by a better, more modern alternative—either within your own product or in the broader market. Continuing to support it makes your product feel dated and can create security vulnerabilities.
• The “Strategic Shift” (Pivot or Refocus): Sometimes, the company’s strategy changes. You’re no longer trying to be the “everything” tool; you’re focusing on being the best tool for a specific niche. A feature, even a moderately successful one, might not align with that new, sharper focus. Sunsetting it is a declaration of strategic discipline.

The Data-Driven Decision: Metrics That Matter

A strong rationale is built on a foundation of cold, hard data. You need to present a clear picture of the feature’s impact—or lack thereof. This isn’t about emotion; it’s about evidence. I once had to sunset a reporting feature that a senior executive was personally attached to. The conversation changed completely when I presented a dashboard showing it was responsible for 40% of our production support tickets while being used by less than 2% of our customers.

Here is a mini-framework for the data you should gather to build your case:

1. Usage & Engagement Analytics:

   • DAU/MAU Ratio: Is this feature used daily by the same people, or is it a once-a-month curiosity? A low ratio indicates poor stickiness.
   • Adoption Funnel: How many users even find the feature? Of those who do, how many complete the primary action? A massive drop-off at any stage points to a usability or value problem.
   • Time-to-Value: How long does it take a new user to get value from this feature? If it’s weeks, it’s likely too complex for the modern user.

2. Cost & Efficiency Metrics:

   • Support Ticket Volume: Tag and quantify every ticket related to this feature. What’s the cost per ticket in terms of support agent time?
   • Engineering Allocation: Ask your tech lead for a rough estimate. “How many hours per sprint are spent on bugs, minor updates, or just thinking about this feature?” This number is often shocking.
   • Infrastructure Costs: Can you isolate the server or database costs associated with this feature? Even a small AWS bill is wasted on a ghost feature.

3. Qualitative Feedback:

   • Customer Sentiment: Analyze support tickets, NPS comments, and social media mentions for phrases like “confusing,” “doesn’t work,” or “I wish it did X instead.”
   • Sales & CS Feedback: Your frontline teams are a goldmine. Ask them: “Do you ever have to apologize for this feature? Do you avoid showing it in demos?”

Golden Nugget: Don’t just present the raw numbers. Frame them as an opportunity cost. For example: “By sunsetting this feature, we can reallocate two full-time engineers, which is the exact resource we need to build the [new, high-demand feature] that our enterprise clients have been requesting for six months.” This shifts the conversation from loss to gain.

The Stakeholder Alignment Imperative

Once your data is solid, the next hurdle is internal. A product decision is never made in a vacuum. If you surprise another department with a feature sunset, you’re not just changing a product; you’re disrupting their entire workflow. This is where trust and authoritativeness are built or broken.

You must secure buy-in from the key teams before the final decision is locked in. Here’s who to talk to and why:

• Engineering: They need to know the “why” to plan the technical work. More importantly, they are your best allies in identifying hidden complexities and resource drains. Involve them early to understand the true cost of the feature.
• Sales: A salesperson might be using that feature as a key selling point to close a deal, even if it’s rarely used post-purchase. You need to understand its impact on the sales cycle and give them a new, better story to tell.
• Marketing: They’ve likely built campaigns, landing pages, and help-doc content around this feature. They need a heads-up to plan their own transition, update messaging, and prepare for any potential PR backlash.
• Customer Support: This is non-negotiable. Your support team will be on the front lines, fielding angry emails and confused users. They need to be armed with a clear timeline, a migration plan, pre-written responses, and training before the first user complains.

A lack of alignment doesn’t just risk a messy rollout; it creates deep internal resentment. It makes the product team look out of touch and can damage your credibility for future initiatives. A successful sunset is a cross-functional project, not a product decree.

The AI-Powered Sunset Strategy Blueprint

Decommissioning a feature feels like a product failure, but it’s actually a sign of a mature, disciplined product team. The real failure isn’t in sunsetting a feature; it’s in letting a low-impact, high-cost feature languish, draining resources and confusing your user base. The challenge is that the emotional and logistical complexity of a sunset can be paralyzing. You’re not just removing a button; you’re managing user expectations, technical dependencies, and internal politics. This is where a strategic AI co-pilot becomes invaluable, helping you move from a reactive, panic-driven process to a proactive, strategic one.

Crafting the Perfect Sunset Prompt

The quality of your AI output is a direct reflection of the quality of your input. A vague prompt will give you generic, unusable fluff. A precise, structured prompt, however, can generate a comprehensive project plan. Think of it as briefing a junior strategist; you need to give them the full context, the objective, the audience, and the exact deliverables you expect.

To get a truly actionable sunset plan, you must deconstruct the request into four core components. This “prompt architecture” ensures the AI understands the nuance of your situation and provides a tailored, strategic response.

• Define the Feature & Rationale: Clearly state the feature name and, crucially, the why behind the sunset. Is it due to low adoption, high maintenance costs, or a strategic pivot? This context is vital for the AI to generate appropriate communication and risk-mitigation strategies.
• State the Primary Objective: Be explicit about the goal. Don’t just say “plan a sunset.” Instead, specify the desired outcome, such as “Create a 6-month sunset plan that minimizes customer churn and maintains a positive brand reputation.”
• Identify the Audience: Who is this plan for? The AI’s tone, complexity, and focus will change dramatically based on the audience. Is this an internal document for your engineering team, a high-level summary for the C-suite, or a communication strategy for your customer success team?
• Request Specific Outputs: Don’t leave the deliverables to chance. List the exact artifacts you need. This forces the AI to structure the information in a practical, usable format.

Here is a masterclass prompt structure you can adapt:

Prompt: “Act as an experienced Product Manager. Develop a comprehensive 6-month sunset plan for the ‘Legacy Reporting Dashboard’ feature. The rationale for sunsetting is that it has less than 2% monthly active usage and its data infrastructure is being replaced by our new Analytics Hub.

The primary objective is to migrate 80% of active users to the new Analytics Hub with less than 5% churn.

The primary audience for this plan is our internal Customer Success and Engineering teams.

Please provide the following specific outputs:

1. A detailed timeline with monthly milestones (Months 1-6).
2. A risk assessment matrix (technical and business risks).
3. A stakeholder communication plan (internal and external).
4. A user migration checklist for the Customer Success team.”

This prompt provides the AI with all the necessary ingredients to cook up a strategic blueprint, not just a list of tasks.

Scenario Planning and Risk Mitigation with AI

One of the most valuable, yet time-consuming, parts of planning a sunset is anticipating everything that could go wrong. Your engineering team is worried about breaking core app dependencies. Your sales team fears it will upset a key account. Your support team is bracing for a deluge of tickets. AI excels at rapid, comprehensive brainstorming, allowing you to build a robust risk matrix in minutes instead of hours.

The key is to prompt the AI to think from multiple perspectives—technical, business, and user—to uncover hidden risks. You want to force it to consider the second and third-order consequences of the decision.

Prompt: “Brainstorm a comprehensive risk matrix for sunsetting the ‘Legacy Reporting Dashboard’. Categorize risks into ‘Technical’, ‘Business’, and ‘User Experience’. For each risk, identify the potential impact (High, Medium, Low), the likelihood of occurrence, and propose a specific mitigation strategy. Include risks related to data integrity, third-party integrations, internal team dependencies, and potential customer backlash.”

The AI might generate a list like this, giving you a powerful tool for pre-emptive problem-solving:

Risk Category	Potential Risk	Impact	Likelihood	Mitigation Strategy
Technical	Breaking a critical internal dashboard that pulls from the legacy API.	High	Medium	Conduct a full dependency audit in Month 1. Create a deprecation API endpoint with a 6-month warning.
Business	A key enterprise customer churns because they relied on a custom report from the old dashboard.	High	Low	Proactively identify all enterprise users of the feature in Month 1. Have the Customer Success team personally manage their migration.
User Experience	Users feel blindsided and post negative reviews, damaging trust.	Medium	High	Execute a multi-touch communication plan (in-app banners, emails, support articles) starting 90 days before deprecation.

Pro-Tip: Don’t just accept the first output. Ask the AI to “Act as a skeptical engineering lead” or “Act as a concerned enterprise customer” and have it critique its own risk matrix. This adversarial prompting often uncovers even more nuanced vulnerabilities.

Developing the Migration & Transition Plan

A sunset without a clear path forward is an act of user abandonment. The goal is not just to remove a feature but to successfully guide users to a better alternative, preserving goodwill and demonstrating that you’re still solving their core problem. This is where you shift from a defensive posture (managing risk) to an offensive one (delivering value).

Your AI co-pilot can help you design user-centric offboarding paths that feel like an upgrade, not a downgrade. The prompts should focus on identifying alternatives and creating frictionless transition processes.

Prompt: “The ‘Legacy Reporting Dashboard’ is being sunset. Its primary user jobs are 1) generating weekly sales performance summaries and 2) exporting raw lead data. The replacement is the ‘Analytics Hub’. Generate a user-centric migration plan. Suggest 3 alternative workflows within the new Analytics Hub that achieve the same user jobs. Outline a step-by-step data export procedure for users who want to keep their old data. Propose a ‘Goodwill Package’ to offer migrating users, such as a temporary discount or access to a premium feature.”

The AI’s output will give you the building blocks for a smooth transition. It might suggest:

• Alternative Workflows: “For weekly sales summaries, users can now ‘Save’ a pre-configured dashboard view in Analytics Hub and have it emailed to them every Monday automatically. For raw lead data export, they can use the new ‘Scheduled Exports’ feature.”
• Data Export: “Create a one-click ‘Export All My Legacy Data’ button in the old dashboard settings, available until the final shutdown date. Provide a clear support article with screenshots showing how to interpret the CSV file.”
• Goodwill Package: “Offer all active users of the legacy dashboard a free 3-month trial of our new ‘Advanced Analytics’ add-on, which includes the functionality they’re losing and more. Frame this as an exclusive ‘early adopter’ offer for being a long-time user.”

By focusing the AI on solutions and alternatives, you transform the sunset from a negative event into a positive product evolution, strengthening your relationship with your most dedicated users.

The Communication Cascade: Internal and External Messaging

A product feature sunset is a delicate operation where the right words are as critical as the right code. A poorly handled announcement can fracture team morale and alienate your user base, while a well-executed communication cascade can turn a potentially negative event into a demonstration of your company’s integrity and customer commitment. This is where you manage the human element of the decommissioning process, ensuring your message is received with understanding, not outrage.

The Internal Announcement: Getting Your House in Order

Before a single customer sees a notification, your entire organization must be aligned. The internal announcement isn’t just a courtesy; it’s your first line of defense against confusion and misinformation. If your support team is blindsided by a customer’s question about the sunset, your credibility takes an immediate hit. The goal is to equip every department with the context, timeline, and talking points they need to operate confidently.

Your internal memo should be a single source of truth. It must transparently explain the “why” (the rationale you established earlier), the “what” (exactly what is being sunset), and the “when” (a clear timeline with key milestones). Most importantly, it must detail the “who”—the impact on different teams and their specific responsibilities.

Here is a powerful prompt to draft a comprehensive internal announcement:

“Act as an internal communications lead for a product team. Draft a clear and concise internal memo announcing the sunset of the ‘[Feature Name]’ feature. The memo should be addressed to all departments (Sales, Support, Marketing, Engineering).

Context:

• Feature Name: [e.g., ‘Legacy Project Importer’]
• Primary Rationale: [e.g., ‘Low adoption (<5% of active users) and high maintenance costs, preventing resources from being allocated to our new AI-powered workflow builder’]
• Sunset Timeline:
  • [Date]: Sunset announcement sent to customers; feature marked as ‘deprecated’ in UI.
  • [Date + 60 days]: Feature becomes read-only; no new imports possible.
  • [Date + 90 days]: Feature is fully removed from the platform.

Departmental Impact & Actions:

• Support: Will handle an influx of tickets. Provide them with the attached FAQ document. All agents must be trained on the migration path by [Date].
• Sales: Stop selling this feature as a benefit. New talking points should focus on the superior new alternative, [New Feature Name].
• Marketing: Draft the external blog post and email sequence. Coordinate with Product on the exact timing.
• Engineering: No new work on the feature. Allocate 20% of sprint capacity for the next two sprints to handle bug fixes only. Begin archival process after [Date + 90 days].

The memo’s tone should be professional, transparent, and reassuring. It should acknowledge that this is a significant change but frame it as a necessary step for product evolution. End with a clear call to action for department heads to confirm their teams are prepared.”

Golden Nugget: A common mistake is creating information silos. To avoid this, create a dedicated, temporary Slack or Teams channel (e.g., #sunset-feature-name) that includes leads from Support, Sales, and Marketing. This allows for real-time Q&A and ensures everyone is working from the same playbook as the external launch date approaches.

The Customer Communication Plan: Empathy and Clarity

This is the most critical part of the cascade. Your customers don’t care about your maintenance costs; they care about how this change affects their workflow. A purely transactional announcement (“We’re removing X, here’s a link to Y”) feels cold and breeds resentment. Your communication must lead with empathy, acknowledge the inconvenience, and relentlessly focus on the user’s benefit and the support you’re providing.

A multi-channel approach is non-negotiable. You need to meet users where they are:

• In-App Notifications: For active users of the feature. This is your most direct and immediate channel.
• Email: For all users, but especially those who have used the feature in the past. This provides a detailed record they can refer back to.
• Blog Post/Help Center: A public-facing article that details the change, the rationale, and the migration path. This becomes the canonical resource you link to from all other communications.

Here is a prompt designed to generate empathetic and helpful customer-facing copy:

“Act as a senior product manager responsible for communicating a feature sunset to our customers. Your primary goal is to maintain user trust while delivering difficult news. Draft the copy for an in-app notification banner and a follow-up email.

Feature Details:

• Feature Being Sunset: [e.g., ‘Legacy Project Importer’]
• Effective Date of Removal: [e.g., ‘October 31, 2025’]
• Reason Framed for Customers: [e.g., ‘To invest in a faster, more reliable way to bring your projects into our platform, we are retiring our older importer. The new AI-powered importer, which we are launching today, reduces import time by 90%.’]
• What Users Get Instead: [e.g., ‘Access to the new AI-powered importer, a step-by-step migration guide, and a dedicated support team to help with any transition issues.’]

Requirements for the Copy:

1. Acknowledge & Empathize: Start by acknowledging their reliance on the feature.
2. Explain the ‘Why’ from Their Perspective: Focus on the benefit to them (e.g., ‘better performance,’ ‘more features,’ ‘improved security’), not our internal reasons.
3. Be Crystal Clear on Dates: Provide the exact timeline (read-only date, removal date).
4. Provide a Clear Path Forward: Link directly to the new feature and the migration guide.
5. Offer Proactive Help: Explicitly tell them how to get help if they need it (e.g., ‘Our support team is ready to assist…’).”

Handling Pushback and Managing Difficult Conversations

No matter how well you communicate, some users will be upset. They may have built critical workflows around the feature, and your announcement represents a significant disruption. Your job is not to win the argument but to de-escalate the situation and guide them toward a solution. The key is to have pre-written, empathetic response templates ready for your support team. This ensures a consistent, professional, and supportive tone, even under pressure.

Your strategy should anticipate common objections and have clear, helpful answers. This isn’t about being defensive; it’s about being a reliable guide.

Use this prompt to generate a robust set of response templates for your support team:

“Act as a customer support enablement specialist. Your task is to create a set of response templates for handling pushback on the ‘[Feature Name]’ sunset announcement.

Common User Objections to Address:

1. ‘I use this feature daily for a critical business process. Your new solution doesn’t work for my use case.’
2. ‘I’m on a legacy plan and this was a core feature I paid for. This feels like a bait-and-switch.’
3. ‘Why are you removing a feature that works instead of just fixing bugs?’
4. ‘I need more time. The [Date + 90 days] deadline is not enough.’

For each objection, generate a response template that includes the following components:

• Acknowledge their frustration: Start with a phrase like, ‘I completely understand your frustration…’ or ‘Thank you for sharing this; I can see why this change is disruptive…’
• Validate their concern: Show you’ve heard them specifically. ‘It sounds like the [specific workflow] is essential to your operations.’
• Reiterate the core benefit (briefly): ‘We’re making this change to ensure long-term stability and performance, which is why we’re focused on the new importer.’
• Offer a specific, actionable solution or path: ‘Let’s schedule a 1-on-1 call to review your workflow and see how we can replicate it with the new tool.’ or ‘While the deadline is firm, I can escalate your feedback to our product team for consideration in future updates.’
• Provide a clear escalation path: ‘If you’d like to discuss this further with a manager, I can connect you.’” The tone for all templates must be supportive, patient, and professional. Avoid corporate jargon and focus on finding a path forward for the user.”

Execution and Monitoring: The Sunset in Motion

A product sunset plan is only as good as its execution. This is where your strategy meets reality, and the margin for error shrinks dramatically. The transition period is a high-stakes balancing act: you must drive users toward the new solution while actively managing the risk of churn and reputational damage. It’s not a “set it and forget it” announcement; it’s a dynamic process that requires constant vigilance and a willingness to adapt. Getting this phase right is what separates a graceful evolution from a messy, brand-damaging failure.

The Phased Rollout: A Step-by-Step Timeline

A sudden shutdown is the fastest way to alienate your user base. A phased approach gives your users the predictability and support they need to adapt, while giving you critical data points to adjust your strategy. Think of this as a controlled descent, not a crash landing. The goal is to systematically reduce the feature’s footprint while increasing support for the migration path.

Here’s a practical timeline you can adapt for your own sunsets:

Phase	Duration	Key Activities	Primary Goal
Phase 1: Announcement & Education	30-60 Days	- In-app banners and modals announcing the sunset date. - Direct email communication to all affected users. - Publish a detailed help center article with FAQs. - Host a live webinar demonstrating the migration path.	Awareness & Preparation: Ensure 100% of active users are aware of the change and have clear instructions on what to do next.
Phase 2: Read-Only / Degraded Mode	30 Days	- Disable critical actions (e.g., creating new items, editing core data). - The feature remains visible for data export and reference. - Aggressively promote the alternative feature within the UI. - Offer dedicated 1:1 migration support calls for high-value accounts.	Migration & Data Integrity: Push the vast majority of users to the new solution while allowing a final window for data retrieval.
Phase 3: Final Shutdown	1 Day	- Feature access is fully revoked. - A final “This feature is no longer available” static page is shown. - A final email is sent confirming the shutdown and providing links to support resources for the new feature.	Clean Break: Officially retire the codebase and infrastructure.
Phase 4: Post-Sunset Support	14-30 Days	- A dedicated support queue for users struggling with the new feature. - A grace period for users who missed the deadline to request a one-time data export.	Trust & Goodwill: Mitigate lingering frustration and demonstrate a commitment to customer success even after the change is complete.

Golden Nugget: During the “Read-Only” phase, use your product analytics to identify the “last holdouts”—users who are still heavily interacting with the deprecated feature. Proactively reach out to them with a personal email or call. This single action can save your most valuable customers and provide you with invaluable qualitative feedback on why your migration path isn’t working for them.

Monitoring Key Health Indicators During the Transition

Once the plan is in motion, your job shifts from planner to air traffic controller. You need a dashboard of real-time signals to know if your plan is working or if it’s about to go off the rails. Relying solely on support tickets is a lagging indicator; by the time you see a spike, the damage is already being done. Modern PMs leverage AI tools to create a proactive monitoring system.

Here’s what you should be watching and how AI can amplify your efforts:

• Support Ticket Trends: Don’t just count tickets; analyze their sentiment and intent. An AI-powered text analysis tool can scan your support tickets and automatically categorize them into themes like “Can’t find the alternative,” “Data export issue,” or “Bug in new feature.” This allows you to spot a rising trend (e.g., a 300% increase in “data export” tickets) within hours, not days, and deploy resources to fix the underlying problem immediately.
• User Behavior on Migration Pages: Your help center article on “How to Migrate from X to Y” is a critical asset. Use tools like Hotjar or FullStory, which now include AI-driven behavior analysis, to see where users are getting stuck. Are they rage-clicking on a specific step? Are 80% of users dropping off after reading the first paragraph? This data tells you your instructions are unclear and allows you to A/B test a new video tutorial or simpler text to improve the completion rate.
• Social Media and Community Sentiment: The conversation will happen with or without you. Use AI social listening tools (like Brand24 or Sprinklr) to monitor mentions of your brand alongside keywords like “[Feature Name] sunset,” “hate the new update,” or “how to migrate.” The AI can perform sentiment analysis to differentiate between mild annoyance (“ugh, have to learn a new thing”) and a churn risk (“this is it, I’m switching to [Competitor]”). This gives you an early warning system to engage with frustrated users publicly and demonstrate you’re on top of the issue.

The Golden Nugget: The most critical metric during a sunset is the Migration Funnel Conversion Rate. Define the key steps a user must take to successfully migrate (e.g., 1. View migration page -> 2. Click “Start Migration” -> 3. Complete import). Track this funnel just like you would a sign-up funnel. If step 2 has a 90% drop-off, your call-to-action is weak or users don’t understand the value. This is the single most important health indicator for a successful sunset.

The Post-Mortem: Learning from the Experience

When the feature is finally gone and the support tickets die down, it’s tempting to declare victory and move on. This is a mistake. The period immediately following a sunset is a goldmine of strategic insights that can inform every major decision you make in the future. A disciplined post-mortem process ensures you’re not just closing a chapter, but writing a playbook for the next one.

Your goal is to create a “Sunset Playbook” that documents what happened, why it happened, and how you’ll do it better next time. This document is invaluable for onboarding new PMs and for justifying future resource decisions. Use these AI prompts to structure and facilitate a brutally honest and productive post-mortem session with your team:

“Act as a seasoned Product Operations Manager. Your task is to generate a comprehensive post-mortem framework for the sunset of the ‘[insert feature name]’ feature. Create a series of prompts for our team meeting that will help us uncover the key learnings. Structure the output into three main sections:

1. Quantitative Impact Analysis:

• Prompt: ‘Calculate the total cost savings from decommissioning this feature. Include engineering hours saved on maintenance, infrastructure costs (servers, databases), and third-party licensing fees.’
• Prompt: ‘Analyze the user churn data. What percentage of active users on the deprecated feature churned within 30 days of the final shutdown? How does this compare to our baseline churn rate?’
• Prompt: ‘What was the actual resource reallocation? Quantify the engineering and design hours saved and specify which new initiatives they were redirected to.’

2. Qualitative Process Review:

• Prompt: ‘What were our biggest communication failures? Where did users get confused or frustrated? Let’s review the top 10 support tickets and social media complaints.’
• Prompt: ‘What went surprisingly well? Identify any part of the migration process that had a higher-than-expected success rate and explain why it worked.’
• Prompt: ‘What were the internal blind spots? What did we assume would be easy that turned out to be hard? What dependencies did we miss?’

3. The Sunset Playbook:

• Prompt: ‘Based on our experience, create a 1-page checklist for the next product sunset. What are the 5 essential, non-negotiable steps we must take?’
• Prompt: ‘Draft a template for our future sunset announcement emails, incorporating the language and tone that we found most effective.’
• Prompt: ‘What early warning signals will we monitor in the future to predict if a feature is a candidate for sunsetting before it becomes a resource drain?’”

This structured approach transforms a potentially negative experience into a strategic asset, building institutional knowledge and making your entire product organization more mature and resilient.

Conclusion: Sunsetting as a Sign of Product Maturity

A well-executed sunset is one of the most underrated skills in product management. It’s a strategic lever that, when handled with care, reinforces user trust and protects your brand’s long-term health. Think of it not as a failure, but as a necessary pruning that allows the rest of your product to thrive. By managing the end-of-life process transparently and empathetically, you demonstrate a mature product strategy that respects your users’ investment in your platform. This builds a reputation for integrity that pays dividends far beyond the specific feature being retired.

Beyond the Prompts: The Irreplaceable PM

While the AI prompts in this guide provide a powerful framework for structure and efficiency, they are not a substitute for your leadership. The most critical elements of a sunset are deeply human: navigating a long-time user’s frustration, negotiating timelines with your engineering team, and making the final call on a resource trade-off. Your strategic judgment, empathy, and communication skills are what turn a well-structured plan into a successful execution. AI can draft the email, but only you can ensure it lands with the right tone and conviction. It can build the timeline, but only you can rally the team behind it.

Your Actionable Next Steps: From Theory to Practice

The best way to master this process is to apply it in a low-stakes environment. This builds your confidence and creates a repeatable playbook for more significant sunsets in the future.

1. Identify a Low-Impact Target: Find a minor feature in your product with low usage and minimal business impact. This could be an old report format, a legacy integration, or a redundant UI element.
2. Apply a Prompt Framework: Choose one of the prompt frameworks from this article—perhaps the “Communication Cascade” or the “Stakeholder Impact Analysis”—and run it for your chosen feature.
3. Draft Your Strategic Sunset Plan: Use the AI-generated output as your starting point. Refine it with your product knowledge, add specific timelines, and outline the human-centric communication steps you’ll take.

By taking this small, concrete step, you transform theory into practice and begin building the institutional muscle for graceful product evolution.

Performance Data

Frequently Asked Questions

Q: Why is product sunsetting considered a critical PM skill

Gracefully sunsetting features prevents technical debt, focuses engineering resources on innovation, and maintains user trust by showing disciplined product management

Q: How can AI specifically help with decommissioning

AI can analyze user data to identify impacted segments, draft empathetic communication templates, and model churn risk, turning a daunting process into a manageable, data-driven workflow

Q: What is the most common reason for sunsetting a feature

The most common driver is low user adoption, often called the ‘Ghost Town’ problem, where a feature’s daily active users are negligible compared to the total user base