Building Agentic Apps With Craft: Field Stories from Austin Vance, CEO, Co-Founder of Focused
Release Date: 05/01/2025
Convergence.fm
In this episode, Ashok sits down with , to explore key insights from Josh's latest book, "Who Does What by How Much." The conversation centers around using OKRs (Objectives and Key Results) to align teams and improve organizational outcomes. They examine the challenges many teams face when implementing frameworks like OKRs or Agile and emphasize the importance of understanding the "why" behind these systems. Josh also reflects on his early work, such as developing the Kensington Turbo Mouse and collaborating with Alan Cooper, widely known as the "Father of Visual Basic." Unlock the full...
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AI can make therapy more accessible—but only if it's done right. In this episode, ex-Google and Amazon product leader Seth shares his journey from panic attacks to building Volo Health, an AI-powered tool for anxiety, depression, and addiction. He breaks down how most therapy tools get it wrong, what makes human-centered AI actually safe, and how product teams can reconnect with the humans they serve—even at scale. Seth opens up about leaving Silicon Valley, his personal journey with emotional healing, and the limits of traditional therapy. Along the way, we explore the ethics of AI in...
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info_outlineWhat does it actually take to build agentic AI applications that hold up in the real world? In this episode, Ashok sits down with Austin, founder of Focused, to share field stories and hard-won lessons from building AI systems that go beyond flashy demos. From legal assistants to government transparency tools, Austin breaks down the concrete criteria for identifying where AI makes sense — and where it doesn’t.
They unpack how to find the right starting point for your first agentic app, why integration with legacy systems is the real hurdle, and the engineering must-haves that keep AI behavior safe and reliable. You’ll hear practical guidance on designing eval frameworks, using abstraction layers like LangChain, and how observability can shape your development roadmap just like in traditional software. Whether you’re a product leader or a CTO, this conversation will help you distinguish hype from real opportunity in AI.
Unlock the full potential of your product team with Integral's player coaches, experts in lean, human-centered design. Visit integral.io/convergence for a free Product Success Lab workshop to gain clarity and confidence in tackling any product design or engineering challenge.
Inside the episode...
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A practical checklist for identifying your first AI-powered app
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The hidden cost of "AI for AI’s sake" and where traditional software is better
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Why repetitive knowledge work is prime territory for automation
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How Focused helped Hamlet build an AI for parsing government meeting data
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Where read-only data access gives you a safe starting point
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Why integration is often more complex than the AI itself
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The importance of eval frameworks and test-driven LLM development
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How to use observability to continuously improve AI agent behavior
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Speed vs. believability: surprising lessons from Groq-powered inference
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Using multiple models in one system and LLMs to QA each other
Mentioned in this episode
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Hamlet (government transparency startup) - https://www.myhamlet.com/?convergence
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LangChain - https://www.langchain.com/?convergence
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Claude (Anthropic) - https://claud.ai/?convergence
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Dspy Prompting framework - https://dspy.ai/?convergence
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Shopify AI memo (referenced) - https://convergence.fm/episode/shopifys-leaked-ai-mandate-explained-6-takeaways-for-your-product-team?convergence
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Amazon Bedrock / SageMaker - https://aws.amazon.com/bedrock/?convergence
Unlock the full potential of your product team with Integral's player coaches, experts in lean, human-centered design. Visit integral.io/convergence for a free Product Success Lab workshop to gain clarity and confidence in tackling any product design or engineering challenge.
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