Building Out Loud

PODCAST · business

Building Out Loud

We follow the journey of a Female Founder creating an AI native tech startup

  1. 16

    Episode 15: How product teams work in AI native tech businesses

    Building Out Loud: Beta testing feedback with Rags (Floto.ai) + How AI is changing product team practicesRandy Silver and Faith Forster welcome Rags, co-founder of Floto and a Discovery beta tester with a product background from Google, Meta, and startups. Rags says Discoveree feels like a “thinking partner” that deliberately slows him down by challenging assumptions, adding guardrails, and mapping practical steps (e.g., founder-led sales to a B2B motion) rather than just providing answers. He notes bugs and suggests faster onboarding by reusing captured business info, and praises “wow” moments like competitor updates and comparative product recommendations, requesting deeper agent-driven drill-down per recommendation. The group discusses shifting dev cycles to weekly releases, inverted build-design workflows, small-team scaling via agents, hiring AI-native juniors, and Faith’s beta expansion, PE-firm outreach, bug-fixing, and looming steps like production readiness and taking payments.00:00 Welcome and Guest Intro00:44 How They Met01:38 Why Rags Joined Beta02:33 Discovery as Thinking Partner04:21 Goals and Guardrails07:46 Bugs and Onboarding Friction09:11 Wow Moments Competitive Insights12:30 Opportunities Feature Explained13:15 Modern Dev Cycles Weekly Releases18:30 Scaling Teams with Agents22:32 Hiring AI Native Juniors24:54 Beta Progress and Next Steps26:36 Closing Thanks

  2. 15

    Episode 14: Rethinking the SaaS experience

    Building Out Loud: Rethinking the SaaS experience and the Discoveree ICP & value propositionRandy Silver and Faith Foster recap a pivotal week for Faith’s product, Discovery, as she ships access to a first beta tester. Faith describes a major mindset shift from building a classic structured B2B SaaS tool to a more flexible, document- and conversation-driven assistant that can adapt to different strategy contexts. She explains a new growth strategy workflow: users upload strategy docs, collaborate with a general strategy assistant, and trigger specialist agents for topics like new markets, acquisition, fundraising, or funnel optimisation, with commenting and iterative refinement. Faith also reports a breakthrough in agent reliability using Opus 4.6, which rapidly diagnosed and fixed issues that previously took weeks. Conversations with a customer success leader and an investor lead her to broaden positioning beyond product teams to tech business leaders, and she adds outputs like user manuals and website positioning. Next steps include more beta feedback and an external security-focused code review.00:00 Beta Shipped Update01:10 Mental Model Breakthrough02:01 Trusting AI Semantics02:57 Strategy Assistant Redesign04:47 Agents Finally Working06:14 Bigger Market Positioning10:03 Automating The Workflow11:49 Defining Growth Strategy12:53 New ICP And Next Steps14:36 Feedback And Security Wrap

  3. 14

    Episode 13: Discipline to stay focused

    Building Out Loud: Shipping vs. Feature Factory in an AI-Native WorldRandy Silver and Faith Foster discuss Faith’s week after attending Product Con’s AI Leadership Conference, where she learned how regulated companies like BT are transforming legacy stacks for an AI-agent world and met the founder of Jack and Jill, an AI-native recruitment business that has automated its customer feedback-to-fix loop using multiple agents. They debate whether this kind of automation creates a sustainable product strategy or an “infinite feature factory,” and what observability and review are needed. Faith reflects that she overbuilt her product, making it far more complex, and recognises she has lost clarity on her ICP amid investor conversations and the spectrum of AI maturity across businesses. With customers waiting, she commits to simplifying and shipping a beta, using real usage—and eventually asking for money—as the forcing function for learning.00:00 Welcome and weekly check-in00:30 ProductCon insights on AI transformation02:07 Automated feedback loops and feature factories03:52 Discovery focus and corporate expectations04:28 Overbuilding and losing the ICP06:20 Alpha learnings and investor pressure08:48 Back to hypotheses and real users09:38 Solo founder tension and accountability12:08 Poker lesson ask for money13:10 This week ship the beta13:57 Wrap-up and next week challenge

  4. 13

    Episode 12: Rethinking PRDs, Roadmaps & Product Teams for the AI Era

    Building Out Loud: Rethinking PRDs, Roadmaps, and Product Teams in an AI-Native WorldRandy Silver checks in with Faith Forster on her progress building Discovery after speaking with over 70 product leaders and using feedback to update the product, shifting it toward a “strategic advisor” and embedding agents to help shape and apply product strategy across decision-making. They discuss how AI changes product development fundamentals—what roadmaps, PRDs, epics, and tasks mean when building is faster and work may be defined for agents rather than engineers—highlighting a “product experience document” that emphasises behavior, tone, and guardrails. Faith explains Discovery’s approach: defining problems, generating and comparing solution ideas, then producing different scoping/design outputs depending on audience (engineer, AI agent, stakeholder), with customisable templates. They also cover collaboration, bias, diversity of viewpoints, the limits of artificial personas versus real users, prototyping trade-offs, and challenges for legacy and regulated stacks. Faith’s next priority is getting the beta ready around ProductCon.00:00 Weekly Build Update01:21 Future of Product Work03:50 Teams to Domains Shift04:01 Artifacts Not Outcomes06:30 Designing for Agents09:14 Collaboration and Bias12:35 Build Fast Risk Smart15:46 Prototypes and Legacy17:51 Beta Prep and Wrap

  5. 12

    Episode 11: Big week!

    Building Out Loud: Beta Prep, Investor Decks & Fixing AI Agents with LangfuseIn this episode of Building Out Loud, Randy Silver and Faith Forster recap a big week: Faith meets Anton, founder of Lovable, and reflects on where Lovable excels (websites and decks) but still falls short for production B2B apps. Buoyed by strong alpha sign-ups, she begins preparing to raise funding, sharing an investor deck and getting early feedback from investors who prefer post-revenue companies. On the product side, she finally improves her agent reliability by combining guidance from Claude with Replit and by adding Langfuse tracing and evals for clearer debugging than basic logs. Faith then previews rapid beta progress, including a revamped “Competitor Intelligence” area with dynamic profiles, strategic analysis, comparisons, and assignable product recommendations, and plans to have the beta ready for upcoming team onboarding calls.00:00 Welcome Back Update00:24 Meeting Lovable Founder01:09 Pitch Deck And Fundraising02:47 Agents Finally Working04:06 How Technical To Be07:19 Replit Logs Tour08:11 Langfuse Tracing And Evals12:40 Beta Build Sneak Peek13:17 Competitor Intelligence Features18:32 Roadmap And Wrap Up

  6. 11

    Episode 10: Evals with Ed Biden

    Building Out Loud: Debugging AI Agents, Evals, and When to Move Beyond Prototyping Tools (with Ed Biden of Hustle Badger)Randy Silver and Faith Forster are joined by Ed Biden, co-founder of Hustle Badger, to follow up on Faith’s progress building an AI-powered discovery product. Faith shares insights from roughly 20 interviews and survey feedback, noting strong resonance with the product’s commercial outcomes value proposition but a clear need to improve trust in the underlying data by getting her “army of agents” working reliably before polishing features. They discuss the temptation to immediately implement feedback versus waiting to prioritise patterns, and Faith details practical debugging issues including missing notifications (e.g., running out of Perplexity credits), JSON parsing problems, and OpenAI producing no output. Ed explains four categories of AI building tools (LLMs, workflow builders, prototyping tools, IDEs) plus an emerging fifth category, then introduces evals and observability via traces, clustering failure modes, and automated tests. Faith plans to try Langfuse, improve dashboards, rethink agent orchestration with planning agents, and continue toward beta users while balancing automation with team control.Check out Hustle Badgers Evals course: https://youtu.be/TA9LJJddlNEOr watch their introductory video on Evals: https://youtu.be/7OcrV7VSvW400:00 Welcome and Guest Intro00:49 Discovery Progress Update01:33 Resisting Quick Fixes02:57 Agent Debugging Woes03:43 Moving Beyond Replit05:03 AI Tooling Landscape08:30 Swarms and Subagents09:16 Evals and Observability15:05 Building Better Evals18:21 Faith Next Steps and Roadmap21:29 Replit vs IDE Comfort23:05 Wrap Up and Teaser

  7. 10

    Episode 9: Alpha feedback & getting production ready

    Building Out Loud: 70 Alpha Signups, Early Validation & Getting to a Production-Ready StackRandy Silver and Faith Foster check in on Faith’s weekly progress building her AI product discovery tool. Faith has grown her alpha group to 70 people, with about half of the original 60 logging in and nine completing the feedback form; 55% rated it extremely valuable or valuable, and about 80% saw value overall. Feedback highlights that adoption is a multi-stakeholder, team-wide decision and that onboarding and implementation need to be seamless, including importing existing product documentation and expanding the AI assistant to create roadmap items. Faith updated messaging and a new website to position it as a strategic CPO purchase focused on CEO/board decision-making and commercial alignment, prioritising UK/EU B2B SaaS (especially PE-backed). Polarised reactions informed a two-tier pricing model (tactical feedback/roadmapping vs outcome and goal alignment). Next she’ll chase testers, prepare four beta users, improve agent reliability, data security, and integrations, and move to a more robust stack with evals tooling; a future episode will feature Ed Biden on evals and production readiness.00:00 Weekly Check In01:09 Early User Signals02:20 Onboarding And AI Assistant03:06 Messaging And Jobs To Be Done04:30 Ideal Customer Profile05:45 Maturity And Pricing Tiers07:32 Next Week Execution Plan08:20 Stack Upgrade And Evals09:05 Confidence And Hiring Help11:19 Next Episode Preview

  8. 9

    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 Setup00:20 Trial Update Tease00:56 Agent Dev Frustrations01:48 Competitor Agent Breakdown04:14 Pricing And Reviews Wins06:32 Hardcoding And Trust07:46 Logging Error Rates09:58 Prompts Triggers LLM Switch13:01 Time Estimates Rabbit Holes14:18 Next Week Plans Wrap

  9. 8

    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

  10. 7

    Episode 6: A live MVP!

    Building Out Loud: Faith’s MVP Is Live — Debugging, Gemini Integration, and What Comes NextIn 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

  11. 6

    Episode 5: Naming & value prop with Chad Butz

    Building Out Loud: Naming and Branding with Chad ButzIn 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

  12. 5

    Episode 4: Demo of Replit product design

    Building Out Loud: Faith's Path to Discoveree - Naming, Prototyping, and FeedbackIn 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

  13. 4

    Episode 3: Demo of Loveable prototype

    Building Out Loud: Faith's AI-Driven Product Management PrototypeIn 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

  14. 3

    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 Loud00:36 Identifying the Problem01:40 Leveraging AI for Product Management03:41 Architectural Challenges and Solutions05:30 Prototyping and Feedback06:20 Exploring AI Tools09:08 Lessons Learned and Next Steps11:05 Conclusion and Next Episode TeaserWhere to find us:• Discoveree: Discoveree.app• Faith: faithforster.com or https://www.linkedin.com/in/faithforster• Randy Silver: outofowls.com or https://www.linkedin.com/in/randysilver 

  15. 2

    Episode 1: Introducing Building Out Loud

    Building Out Loud: Faith Forster's AI Startup JourneyWelcome 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 Loud00:37 Faith's Journey into AI01:20 Challenges in Product Management02:43 Faith's Startup Experience04:10 Identifying the Problem and Customer06:04 Prototyping and Feedback09:24 Looking AheadWhere to find us:• Discoveree: Discoveree.app• Faith: faithforster.com or https://www.linkedin.com/in/faithforster• Randy Silver: outofowls.com or https://www.linkedin.com/in/randysilver 

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ABOUT THIS SHOW

We follow the journey of a Female Founder creating an AI native tech startup

HOSTED BY

Discoveree.app

Produced by Faith Forster

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