Inside Apartment List’s AI-Powered Product Team | Sierra Hahn-Ventrell, Director of Product Management
AI isn’t a side project at Apartment List — it’s part of the daily workflow.
TL;DR:
Apartment List is empowering their teams to level up with AI, and in this episode of LaunchPod AI, Sierra Hahn-Ventrell, Director of Product Management, shares how her team is using AI to surface customer insights, proactively detect performance issues, and transform the way product marketing and sales teams stay in sync.
We break down how the team:
Analyzes customer interviews with ChatGPT and even uncovered an insight that led to a full product strategy reset (13:10)
Built an AI Slack bot to flag issues in a new customer-facing tool before they become big problems (2:47)
And transformed sales enablement and automated documentation using NotebookLM and Claude (10:19)
What do you want to learn about when it comes to incorporating AI into your team’s workflow?
1. Avoided a Bad Bet by Synthesizing Research with ChatGPT
The team used ChatGPT to analyze interviews and prototype feedback ahead of a new product launch and found a problem they had missed.
What they did:
Fed interview transcripts and notes into ChatGPT
Asked it to synthesize findings, compare to market, and evaluate product-market fit
Kept pushing it with follow-up prompts: competitor comparisons, sentiment analysis, fit assessments
What they found:
The product idea looked too similar to existing competitors
Feedback flagged a lack of differentiation in a saturated space
AI surfaced gaps that the team hadn’t fully acknowledged
“We’re completely changing our product strategy and we’ve kind of scrapped the entire original idea.”
2. Built a Slack Bot to Flag Issues in Real Time
Early pilots of their AI leasing agent are complex and often competitive. So the team built a system of internal AI agents to monitor deployments.
How it works:
Property-level agents review performance
Supervisor agents track overall metrics
A synthesis agent posts key alerts to Slack
What it flags:
Performance against benchmark KPIs
Issues with integrations, setup, or delivery
Anomalies compared to past performance
Why it works:
Built on existing data stack (BigQuery)
Delivered in Slack, where the team already operates
Avoids alert fatigue by layering three tiers of KPI review
“It allows us to move so much faster — without overwhelming the support team.”
3. Scaled Sales Enablement with NotebookLM and Claude
Sales needed an easier way to understand new features and positioning, so the product team used AI to shorten the process and make the positioning more engaging.
What they did:
Dropped docs and release notes into NotebookLM
Created pitch-style summaries and Q&A formats
Generated audio versions for reps to listen to on the go
When it worked best:
Launching new B2B platform positioning
Training sales on how to handle objections and talk about integrations
Rolling out enablement across distributed teams
“So much easier than reading a 10-page doc, especially when you’re on a plane heading to a client site.”
Links
Tools
Chapters
What does LogRocket do?
LogRocket's Galileo AI watches user sessions for you and surfaces the technical and usability issues holding back your web and mobile apps. Understand where your users are struggling by trying it for free at LogRocket.com.