Most AI agents are built backwards, starting with models instead of system architecture.

Aishwarya Srinivasan, Head of AI Developer Relations at Fireworks AI, joins host Conor Bronsdon to explain the shift required to build reliable agents: stop treating them as model problems and start architecting them as complete software systems. Benchmarks alone won't save you.

Aish breaks down the evolution from prompt engineering to context engineering, revealing how production agents demand careful orchestration of multiple models, memory systems, and tool calls. She shares battle-tested insights on evaluation-driven development, the rise of open source models like DeepSeek v3, and practical strategies for managing autonomy with human-in-the-loop systems. The conversation addresses critical production challenges, ranging from LLM-as-judge techniques to navigating compliance in regulated environments.

Connect with Aishwarya Srinivasan:

LinkedIn: https://www.linkedin.com/in/aishwarya-srinivasan/

Instagram: https://www.instagram.com/the.datascience.gal/

Connect with Conor: https://www.linkedin.com/in/conorbronsdon/

00:00 Intro — Welcome to Chain of Thought

00:22 Guest Intro — Ash Srinivasan of Fireworks AI

02:37 The Challenge of Responsible AI

05:44 The Hidden Risks of Reward Hacking

07:22 From Prompt to Context Engineering

10:14 Data Quality and Human Feedback

14:43 Quantifying Trust and Observability

20:27 Evaluation-Driven Development

30:10 Open Source Models vs. Proprietary Systems

34:56 Gaps in the Open-Source AI Stack

38:45 When to Use Different Models

45:36 Governance and Compliance in AI Systems

50:11 The Future of AI Builders

56:00 Closing Thoughts & Follow Ash Online

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This week, we're doing something special and sharing an episode from another podcast we love: The Humans of AI by our friends at Writer. We're huge fans of their work, and you might remember Writer's CEO, May Habib, from the inaugural episode of our own show.

From The Humans of AI:

Learn how Melisa Russak, lead research scientist at WRITER, stumbled upon fundamental machine learning algorithms, completely unaware of existing research — twice. Her story reveals the power of approaching problems with fresh eyes and the innovative breakthroughs that can occur when constraints become catalysts for creativity.

Melisa explores the intersection of curiosity-driven research, accidental discovery, and systematic innovation, offering valuable insights into how WRITER is pushing the boundaries of enterprise AI. Tune in to learn how her journey from a math teacher in China to a pioneer in AI research illuminates the future of technological advancement.

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Check out Writer’s YouTube channel to watch the full interviews.

Learn more about WRITER at writer.com.

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The incredible velocity of AI coding tools has shifted the critical bottleneck in software development from code generation to code reviews.

Greg Foster, Co-Founder & CTO of Graphite, joins the conversation to explore this new reality, outlining the three waves of AI that are leading to autonomous agents spawning pull requests in the background. He argues that as AI automates the "inner loop" of writing code, the human-centric "outer loop"—reviewing, merging, and deploying—is now under immense pressure, demanding a complete rethinking of our tools and processes.

The conversation then gets tactical, with Greg detailing how a technique called "stacking" can break down large code changes into manageable units for both humans and AI. He also identifies an emerging hiring gap where experienced engineers with strong architectural context are becoming "lethal" with AI tools. This episode is an essential guide to navigating the new bottlenecks in software development and understanding the skills that will define the next generation of high-impact engineers.

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Graphite Website: graphite.dev

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