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