Building Out Loud

https://discoveree.com/
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We follow the journey of Faith Forster as she creates an AI native tech startup & product.

  1. Episode 1

    Episode 1: Introducing Building Out Loud

    Building Out Loud: Faith Forster's AI Startup Journey Welcome to 'Building Out Loud,' a new podcast where Randy Silver and Faith Forster document the weekly progress of Faith's journey in building a new AI startup. Faith, a Chief Product Officer, explores how AI can transform the product management space by making processes more efficient. The series delves into the challenges of startup building, her experiences, and the evolving landscape of AI and product management. In the first episode, they discuss the rationale behind the startup, initial challenges, and the importance of redefining the playbook for building products in today's AI-driven environment. 00:00 Introduction to Building Out Loud 00:37 Faith's Journey into AI 01:20 Challenges in Product Management 02:43 Faith's Startup Experience 04:10 Identifying the Problem and Customer 06:04 Prototyping and Feedback 09:24 Looking Ahead Learn more about Discoveree: https://discoveree.com/

    10 min

  2. Episode 2

    Episode 2: Problem we're solving & first steps

    Building Out Loud: Faith's Journey into AI startup for "Product Intelligence" Welcome to the latest episode of 'Building Out Loud,' a weekly check-in hosted by Randy and Faith as they delve into the development of Faith's new AI project, 'Product Intelligence.' This episode covers the initial ideation, challenges in gathering and analyzing data for product management, and the potential of AI agents to streamline these processes. Faith walks us through her architectural approach, lessons learned, and interactions with various tools, while also exploring the broader implications and desirability of the project. Stay tuned for an in-depth look at how the idea evolved and what's next in their development journey. 00:00 Introduction to Building Out Loud 00:36 Identifying the Problem 01:40 Leveraging AI for Product Management 03:41 Architectural Challenges and Solutions 05:30 Prototyping and Feedback 06:20 Exploring AI Tools 09:08 Lessons Learned and Next Steps 11:05 Conclusion and Next Episode Teaser Learn more about Discoveree: https://discoveree.com/

    11 min

  3. Episode 3

    Episode 3: Demo of Loveable prototype

    Building Out Loud: Faith's AI-Driven Product Management Prototype In this episode of 'Building Out Loud,' hosts Randy and Faith dive into the development of Faith's new AI project designed for product monitoring and management.  Faith showcases her progress, highlighting the journey from a simple clickable prototype in Lovable to a more advanced version being built in Replit. The episode covers the project's core functionalities, including AI agents for data collection, sentiment analysis, and dashboard metrics for product teams. Discussions also touch on the challenges of sentiment scoring, the relevance of OKRs in an AI-driven environment, and the importance of setting constraints for productive development.  Tune in to learn more about the project's evolution and upcoming features. 00:00 Introduction and Episode Overview00:29 Initial Product Development01:18 Lovable Prototype Demonstration03:10 Replit Development Insights04:02 Sentiment Scoring Challenges04:21 Organizing Feedback and Goals04:57 OKRs and Leadership Insights07:30 User Engagement and Roadmapping08:12 North Star Metric and Future Plans09:04 Conclusion and Next Episode Teaser Learn more about Discoveree: https://discoveree.com/

    10 min

  4. Episode 4

    Episode 4: Demo of Replit product design

    Building Out Loud: Faith's Path to Discoveree - Naming, Prototyping, and Feedback In this episode of 'Building Out Loud,' hosts Randy and Faith discuss her latest progress on the newly named app, Discoveree. Faith explains her decision to move development from Lovable to Replit for better functionality and reliability. She highlights Discoveree's new features, including onboarding flows, AI-generated opportunities, and sentiment scoring. Faith also shares her learnings from feedback sessions with product leaders and explores the delicate balance between adding features and validating the MVP. Tune in to hear about the next steps and challenges in bringing this AI-driven product management tool to life. 00:00 Introduction and Recap00:32 Revealing the App Name01:11 Choosing the Right Development Platform02:09 Building the App: Features and Challenges02:58 AI-Generated Opportunities and Feedback04:01 Sentiment Scoring and API Integration05:46 Validation and Future Plans09:18 Conclusion and Next Steps Learn more about Discoveree: https://discoveree.com/

    10 min

  5. Episode 5

    Episode 5: Naming & value prop with Chad Butz

    Building Out Loud: Naming and Branding with Chad Butz In this episode of 'Building Out Loud,' host Randy Silver and guest Chad discuss the journey of Faith's new startup, focusing on the challenges and processes involved in naming and branding the product 'Discoveree.'  They explore the importance of a strong brand, product messaging, and the difficulties of naming a new product. The conversation delves into the iterative process of testing and refining the name and message, the role of AI in product development, and the overall strategy for launching a new product. Chad and Faith share insights from their previous experiences and emphasize the significance of early customer feedback and confidence-building for founders. 00:00 Introduction and Special Guest00:41 The Importance of Branding01:19 Naming the Product05:00 Crafting the Messaging07:55 Building the Website10:03 Testing and Feedback12:18 Comparing Past and Present Startups13:30 Conclusion and Next Episode Teaser Learn more about Discoveree: https://discoveree.com/

    15 min

  6. Episode 6

    Episode 6: A live MVP!

    Building Out Loud: Faith’s MVP Is Live — Debugging, Gemini Integration, and What Comes Next In this episode of Building Out Loud, Randy Silver checks in with Faith after a gap in updates and she reveals big news: her MVP is now live in production.  Faith shares that launching triggered a major debugging and security push, including ensuring a secure multi-tenant setup and correct data handling.   Faith walks through the MVP. She demonstrates the setup for product teams, business goals, and team goals, enabling planned value realization tracking. At the team level, the app collects competitor and own-product feedback from review and comparison sites, groups insights by themes or shows raw feedback with source links, and supports creating opportunities manually or automatically. The roadmap emphasizes value realization through planned start dates and time investment, will sync with Jira in the future, and can generate PRDs or user stories from collected context.  Randy challenges whether this is truly an MVP given how much is built and the fact that no users have tested it yet. Faith explains how AI drastically shortened build time, but agrees the next step is validating usability and fit. She plans to reach out to product leaders and senior product managers for hands-on feedback, focusing on whether the goal setup matches varied organisational realities and whether the core workflow—from feedback to opportunities to solutions to roadmap—fits real operating and governance cycles.  After another revision round, she hopes to onboard teams for a beta. She expects feedback in a couple of weeks, will continue tidying up, start building integration capabilities, and use early feedback to revise the website, polish and publish the podcast episodes, and build a drumbeat about how AI is changing product decision-making. 00:00 Live MVP Launch: What’s Working (and What Broke in Production)00:42 The Confidence Turning Point: Replit Support, Gemini Integration, and Reliability02:03 MVP Tour: Dashboard, Competitors, and Roadmap Views03:22 Goals & Metrics Setup: Connecting Team Work to Business Outcomes04:22 Core Workflow Demo: Feedback Agents → Opportunities → Solutions05:59 Roadmap Execution: Value Realization, Jira Sync, and AI-Generated PRDs06:39 Is This Really an MVP? How AI Changes the Definition of “Minimum”07:53 Testing Plan: Hypotheses, Open Questions, and What to Validate10:56 What Success Looks Like: From Solo Testing to Team Alpha12:10 Next Steps & Wrap-Up: Integrations, Website Messaging, and Next Check-In Learn more about Discoveree: https://discoveree.com/

    13 min

  7. Episode 7

    Episode 7: Training agents & initial alpha feedback

    Building Out Loud: Initial MVP Feedback & wrestling with Agents  Randy Silver and Faith Forster catch up after Faith reaches a key milestone: a working MVP that covers the full workflow.  After walking a few “friendly” product leaders through the tool, Faith uses early feedback to sharpen the purpose of each element. She shares strong early demand signals and early indications of willingness to pay. Faith explains recent work on AI agents and why it has been harder than expected. Based on user conversations, Faith talks about some of the updates she has already made to deliver even more value.  00:00 MVP Update: Full Workflow Working & Early Friendly Feedback00:50 Sharpening Features: Rethinking the Roadmap Around Impact01:38 Demand Signal: 53 Product Leaders Raise Their Hands02:19 Will They Use It and Pay? Early Buyer Validation04:12 Building with AI Agents: The Pain of Training Web Search & Pricing Scrapes05:37 Refactoring the Agent Stack: Router + Choosing Perplexity/OpenAI/Gemini06:36 Cadence & Cost: Scheduling Agents and Avoiding Market Noise08:01 Competitor Intelligence: Threat Levels, Refreshes, and Instant Battle Cards09:06 Assistant vs Autonomous Agents: What’s Hard, What Learns Over Time09:39 Evals, Corrections, and Learning Loops in the Product11:26 Next Week: Sending 60 Invites, Collecting Beta Feedback, and Messaging Prep12:07 Wrap-Up and What’s Coming Next Learn more about Discoveree: https://discoveree.com/

    12 min

  8. Episode 8

    Episode 8: Building agents

    Building Out Loud: Under the Hood of AI Agents (Logging, LLM Routing & Competitor Tracking) Randy and Faith catch up on Faith’s startup progress after sending a trial to 60 people and getting useful feedback on product, selling, implementation, and how it fits into customers’ tool stacks.  This episode goes under the hood on why shipping took longer: building reliable AI agents was frustrating and required re-architecting the platform. Faith demos a competitor-monitoring workflow that evolved from one failing “competitor agent” into 8–9 narrow agents covering sources, product summary, segments, news/updates, pricing, features, integrations, and review summaries.  They discuss the need for rigorous logging, avoiding hard-coded behavior, and treating AI like a “lazy developer” that must be audited. Faith added editable prompts, scheduled/manual refresh, cost tracking, and an LLM router with fallback and bring-your-own-keys support, reducing Gemini errors from 48% to 19%, and plans a new website and product direction updates next week. 00:00 Welcome Back Setup 00:20 Trial Update Tease 00:56 Agent Dev Frustrations 01:48 Competitor Agent Breakdown 04:14 Pricing And Reviews Wins 06:32 Hardcoding And Trust 07:46 Logging Error Rates 09:58 Prompts Triggers LLM Switch 13:01 Time Estimates Rabbit Holes 14:18 Next Week Plans Wrap Learn more about Discoveree: https://discoveree.com/

    15 min
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We follow the journey of Faith Forster as she creates an AI native tech startup & product.

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  • Creator
    https://discoveree.com/
  • Years Active
    2K
  • Episodes
    20
  • Rating
    Clean
  • Copyright
    © 2026 https://discoveree.com/
  • Show Website
    Building Out Loud