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 NextLearn more about Discoveree: https://discoveree.com/