A practical look at the SDLC mechanics that separate teams getting real output from agents from teams generating a lot of code that doesn’t hold up. This talk covers spec-driven development as a way to give agents better constraints, large language model (LLM) gateway and routing strategies for managing which model handles which task, test-driven development adapted for an agent-first workflow, and verification practices built for the volume and pace of AI-generated code. This session is a deep dive on the actual mechanics of building software well with agents in the loop.
Summary
Speakers
Ameya Kanitkar
Co-founder and CTO @ Larridin
Ameya is the co-founder and CTO of Larridin, an AI value measurement platform backed by a16z, Gradient, and Bloomberg Beta. He was previously Head of Engineering for Coinbase's retail trading business, and before that, he led Developer Productivity engineering at LinkedIn. He speaks and writes about measuring AI's real impact on how engineering organizations actually work. Today he runs a fully AI-native engineering team where all production code is written with Coding agents - building Larridin - a platform that measures ROI on every dollar of AI spend.
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