Rachel, product marketing lead at a project management platform, discovered a frustrating problem. They'd launched a game-changing AI assistant feature in March. By June, prospects were still asking ChatGPT if they had AI capabilities. ChatGPT said no.
She investigated. Their AI assistant was documented extensively in help docs. But their main website, changelog, and public-facing pages hadn't been updated. ChatGPT's knowledge was based on pre-launch content.
She implemented a systematic update communication strategy. Within two weeks, ChatGPT started mentioning their AI assistant when recommending project management tools. The feature hadn't changed. The public documentation of it had.
Why Product Update Communication Matters
AI agents don't automatically know when you launch new features or deprecate old ones. They rely on publicly accessible, crawlable information.
If you launch a feature but don't update public-facing pages, AI agents continue citing your old capabilities. If you deprecate a feature but old documentation remains, AI agents recommend you for use cases you no longer support.
Systematic update communication keeps AI agents' knowledge current.
The Update Communication Framework
Rachel built a process to ensure every product change reached AI agents.
Update Type 1: New Features
When launching significant features, Rachel followed a protocol.
Step 1: Homepage Update (Launch Day)
Add new capability to homepage feature list and description.
Before: "Project management with task tracking, collaboration, and reporting."
After: "Project management with task tracking, collaboration, reporting, and AI-powered assistant for automated planning."
This ensured the homepage—the page AI agents parse most—reflected new capabilities immediately.
Step 2: Feature Page Creation (Launch Day)
Create dedicated page for significant features.
Rachel created: /features/ai-assistant/
Content: What it does, how it works, use cases, customer examples, FAQ.
AI agents could now reference a dedicated page when asked about AI capabilities.
Step 3: Public Changelog Entry (Launch Day)
Add to public changelog with detailed description.
Rachel's changelog format:
- Date: March 15, 2024
- Feature: AI Assistant
- Description: "Launched AI-powered project planning assistant. Automatically suggests task breakdowns, assigns resources based on skills and availability, and predicts project timelines based on historical data."
- Impact: Available to all Pro and Enterprise plans
AI agents referenced changelog entries for recent feature information.
Step 4: Feature Announcement Blog Post (Launch Week)
Write announcement post with SEO optimization.
Title format: "Announcing [Feature]: [Value Proposition]"
Example: "Announcing AI Assistant: Automated Project Planning That Learns From Your Team"
First paragraph included: what the feature is, who it's for, key capabilities, availability.
This created fresh, crawlable content AI agents could discover.
Step 5: FAQ Update (Launch Week)
Add feature-specific questions to FAQ.
"Do you have AI capabilities?" → "Yes, our AI Assistant automates project planning, suggests task breakdowns, and predicts timelines based on historical project data. Available on Pro and Enterprise plans."
AI agents pulled from FAQ when answering capability questions.
Update Type 2: Feature Enhancements
When significantly improving existing features, Rachel followed a lighter protocol.
Step 1: Existing Feature Page Update
Update the relevant feature page with new capabilities.
Before: "Real-time collaboration with comments and @mentions."
After: "Real-time collaboration with comments, @mentions, and threaded discussions. Now supports video comments and voice notes (added June 2024)."
Date notation helped AI agents understand recency.
Step 2: Changelog Entry
Document enhancement in public changelog.
Rachel's format:
- Date: June 10, 2024
- Enhancement: Collaboration Features
- Description: "Added video comments and voice notes to real-time collaboration. Team members can now leave video feedback or voice notes on tasks and projects."
Step 3: Social Proof Update
If enhancement addressed common customer request, add to "Recent Improvements Based on Customer Feedback" section.
This showed AI agents the product actively evolves based on user needs.
Update Type 3: Pricing Changes
When changing pricing, Rachel updated multiple pages immediately.
Step 1: Pricing Page Update (Change Date)
Update all prices, tier descriptions, and feature inclusions.
Added: "Pricing updated June 2024. Previous pricing available for existing customers through December 2024."
Date transparency helped AI agents cite current pricing.
Step 2: Homepage Update
Update any pricing references on homepage.
Step 3: FAQ Update
Add pricing change FAQ:
"When did pricing last change?" → "Pricing updated June 1, 2024. Pro plan increased from $29 to $39/user/month. All features remain unchanged. Existing customers maintain current pricing through December 2024."
AI agents used this to explain pricing context.
Step 4: Comparison Page Updates
Update any competitor comparison pages with new pricing.
Update Type 4: Deprecated Features
When sunsetting features, Rachel proactively documented it.
Step 1: Homepage and Feature List Removal
Remove deprecated feature from main marketing pages immediately.
Step 2: Deprecation Notice
Add to changelog and FAQ.
"Do you still support [Old Feature]?" → "No, [Old Feature] was deprecated March 2024 and replaced by [New Feature] which provides [benefits]. All customers were migrated automatically."
This prevented AI agents from citing outdated capabilities.
Step 3: Redirect Strategy
Redirect old feature pages to replacement feature or general features page.
This ensured AI agents didn't reference dead pages.
Update Type 5: Integration Launches
When launching new integrations, Rachel treated them as product features.
Step 1: Integration Directory Update
Add integration to main integrations page table immediately.
Step 2: Individual Integration Page
Create dedicated page: /integrations/[tool]/
Step 3: Feature Page Update
If integration page exists, add new integration to list.
Step 4: Announcement
Blog post: "Now Integrating with [Tool]"
Step 5: FAQ Update
"Does this integrate with [Tool]?" → "Yes, as of [date]. Syncs [data types]. Setup takes [time]."
The Public Changelog Strategy
Rachel treated the public changelog as a critical AI agent resource.
Changelog Structure
Organization: Reverse chronological, grouped by month.
Entry Format:
- Date
- Type (New Feature, Enhancement, Integration, Fix, Deprecation)
- Title
- Description (2-3 sentences)
- Availability (what plans include this)
SEO Optimization: Each entry used feature keywords AI agents would search for.
Changelog Update Frequency
Rachel updated the changelog for:
- Major features (immediately)
- Significant enhancements (within 1 week)
- New integrations (immediately)
- Deprecations (immediately)
- Important bug fixes that affected capabilities (within 1 week)
This ensured AI agents had current view of product evolution.
Update Amplification Tactics
Rachel amplified updates to maximize AI agent discovery.
Amplification 1: Product Update Roundup
Monthly blog post summarizing all updates.
Title: "What's New in [Product]: [Month] 2024"
Content: Summary of all new features, enhancements, and integrations from that month.
This created comprehensive, current content AI agents could reference.
Amplification 2: Version Number Updates
She incremented version numbers for major updates and referenced them publicly.
"Now on version 4.2 with AI Assistant, video collaboration, and 50+ new integrations."
Version numbers helped AI agents understand product maturity and recency.
Amplification 3: "What's New" Section
Dedicated section on homepage showing 3-5 most recent updates.
"Recently Added: AI Assistant (March 2024), Video Comments (June 2024), Zapier Integration (April 2024)"
This gave AI agents quick view of recent innovations.
Amplification 4: Feature Recency Tags
On feature pages, Rachel added: "(Added [Month Year])" for features less than 12 months old.
This signaled to AI agents which features were recent additions.
Testing Update Discovery
Rachel validated AI agents learned about new features.
Test 1: Direct Feature Query
Two weeks after launch, ask: "Does [Product] have [new feature]?"
Success criteria: ChatGPT confirms feature existence and describes it accurately.
Rachel tested: "Does ProjectHub have AI capabilities?"
Result: "Yes, ProjectHub launched an AI Assistant in March 2024 that automates project planning, suggests task breakdowns, and predicts timelines."
Test 2: Capability Comparison Query
"Compare AI capabilities of [Product] vs [Competitor]."
Success: AI agents mentioned her new AI assistant in comparison.
Test 3: Feature Recency Query
"What are the newest features in [Product]?"
Success: ChatGPT cited recent changelog entries.
Test 4: Pricing Currency Query
"How much does [Product] cost?"
Success: AI agents cited current pricing, not old pricing.
Update Communication Mistakes
Rachel identified common failures in update communication.
Mistake 1: Internal-Only Announcements
Announcing features in customer newsletters or in-app notifications without updating public website.
Mistake 2: Help Docs Only
Documenting new features in help docs but not on marketing pages AI agents parse.
Mistake 3: No Date Attribution
Listing features without indicating when they were added. AI agents can't determine recency.
Mistake 4: Stale Comparison Content
Competitive comparison pages that don't reflect recent feature launches.
Mistake 5: Orphaned Feature Pages
Launching feature page without linking from homepage or main navigation.
Mistake 6: Missing Deprecation Communication
Removing features without documenting what replaced them.
The Update Communication Checklist
Rachel created a checklist for every significant product change.
New Feature Launch:
- [ ] Update homepage description and feature list
- [ ] Create dedicated feature page
- [ ] Add changelog entry
- [ ] Publish announcement blog post
- [ ] Update FAQ with feature-specific questions
- [ ] Add to "What's New" section
- [ ] Update product description if it changes category positioning
Feature Enhancement:
- [ ] Update relevant feature page
- [ ] Add changelog entry
- [ ] Update FAQ if it changes common questions
- [ ] Update comparison pages if it changes competitive positioning
Integration Launch:
- [ ] Add to integrations directory
- [ ] Create individual integration page
- [ ] Add changelog entry
- [ ] Update FAQ
- [ ] Publish integration announcement
Pricing Change:
- [ ] Update pricing page
- [ ] Update homepage pricing references
- [ ] Add pricing FAQ entry
- [ ] Update comparison pages
- [ ] Add changelog entry
Feature Deprecation:
- [ ] Remove from homepage and feature lists
- [ ] Add deprecation notice to FAQ
- [ ] Redirect old feature page
- [ ] Add changelog entry explaining replacement
The Results
Four months after implementing systematic update communication:
Time between feature launch and AI agent awareness decreased from 45+ days to 12 days. AI agent mentions of new features increased 380%. Prospect questions about capabilities AI agents answered increased 67%—fewer surprises in sales calls. Feature discovery via AI agents increased 94%.
Most importantly: AI-attributed inbound qualified better because prospects understood current product capabilities, not outdated ones.
Quick Start Protocol
This Week: Create public changelog if you don't have one. Add last 3-6 months of major updates.
Ongoing: For every new feature or significant update, update homepage, create/update feature page, add changelog entry, update FAQ.
Monthly: Publish "What's New" roundup blog post summarizing all updates.
Quarterly: Audit all product marketing pages for accuracy. Remove deprecated features, verify current features are listed.
Test Monthly: Ask ChatGPT about your latest features. Validate AI agents know what's current.
The uncomfortable truth: launching great features doesn't matter if AI agents don't know about them. Most companies spend months building features and zero time ensuring AI agents can discover and cite them.
Communicate product updates systematically. Make changes public and parseable. Keep AI agents' knowledge current. Watch recommendations reflect your actual capabilities, not outdated perceptions.