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⚡️Using RFT to Build Clinical Superintelligence

Jul 29, 2025 · 26:58

Brendan Fortuner, Head of Eng at Ambience AI, explains how the healthcare startup uses OpenAI's reinforcement fine-tuning (RFT) to build clinical AI assistants that help doctors automate note-taking and ICD-10 coding, saving up to two hours per day. Ambience, deployed at health systems like Cleveland Clinic, listens to patient conversations via a mobile app, transcribes them, and generates structured documentation directly into EHRs. Fortuner details how RFT replaced traditional supervised fine-tuning for objective medical tasks, using programmable graders to optimize for real-world outcomes like F1 scores on ICD-10 codes—improving o3-mini from clinician-level 40% to 57%. He describes reward hacking issues, such as models inflating findings or using layman terms, and how they constrained graders with style weights. The episode also covers domain expert vs. ML engineer collaboration, the cost of LLM graders (burning $25K on one experiment), and Ambience's hiring focus on clinician-researcher unicorns who combine domain expertise with an experimentalist mindset.

Cline: The Collaborative AI Coder

Jul 16, 2025 · 1:15:44

Saoud Rizwan and Pash from Cline join to explain why their open-source coding agent uses a Plan + Act paradigm — having models explore and plan before executing — pioneered before competitors like Claude Code. They argue that "RAG is a mind virus" and "Fast Apply got bitter lesson'd" as frontier models now achieve sub-5% diff edit failure rates, making layered workarounds obsolete. Cline's bring-your-own-API-key model avoids inference markups, with enterprise features driven by Fortune 5 companies asking for security and ROI insights. The MCP ecosystem grew via Cline's marketplace (150+ servers, top ones with hundreds of thousands of downloads), though monetization and security remain open questions. They detail how Plan mode extracts user intent and Act mode auto-approves, how context engineering prioritizes agentic file exploration over retrieval, and why they stayed a VS Code extension rather than fork — to focus solely on the agentic loop.

[AIEWF Preview] Containing Agent Chaos — Solomon Hykes

Jun 3, 2025 · 27:14

Solomon Hykes, creator of Docker and founder of Dagger, argues that the industry needs an open standard for AI coding agent environments to avoid repeating the fragmentation seen before Docker. Dagger, a workflow engine originally built for post-development automation (CI/CD), is now being pulled by its community into the agentic space to solve environment isolation, portability, and observability for concurrent agent teams. Hykes insists containers are the right base layer but require a new, agent-native UX—unlike legacy Dockerfile or Compose—that is decoupled from any IDE, model, or cloud provider. He critiques current vertical monoliths (e.g., proprietary IDE-hosted agent environments) and advocates for a Lego-like modular approach where the environment is the standard linchpin. Dagger integrates with existing stacks rather than replacing them, and Hykes previews fresh, unreleased content for his upcoming keynote at AI Engineer World's Fair.