Goodfire

Goodfire AI’s Bet: Interpretability as the Next Frontier of Model Design — Myra Deng & Mark Bissell

Feb 5, 2026 · 1:08:41

Goodfire AI's Mark Bissell and Myra Deng argue that interpretability is the next frontier for model design, using their recent $150M Series B at $1.25B valuation to scale surgical edits of model internals beyond post-hoc poking. They explain how their platform detects behaviors like sycophancy and reward hacking, enabling targeted unlearning without wrecking capabilities. The episode covers real-world deployments from Rakuten's PII guardrails to life science partnerships with Mayo Clinic finding Alzheimer's biomarkers. Mark demonstrates real-time steering of a trillion-parameter Kimi K2 model, while Myra details how SAEs sometimes underperform probes for detection tasks. They envision a future where interpretability guides training so customization isn't brute-force guesswork.

[State of MechInterp] SAEs in Production, Circuit Tracing, AI4Science, "Pragmatic" Interp — Goodfire

Dec 31, 2025 · 21:48

Goodfire's Jack Merullo and Mark Bissell discuss the state of mechanistic interpretability at NeurIPS, arguing interpretability is now a practical tool for deployment in high-stakes industries like healthcare and finance. They introduce paint.goodfire.ai, which lets users paint directly into Stable Diffusion's internal concept map via unsupervised feature discovery. At Rakuten, Goodfire's interpretability-based PII detection proved 500x cheaper than GPT-5 as a judge with higher recall. Merullo presents a memorization vs. reasoning spectrum, showing factual recall sits between rote memorization and logical reasoning. They highlight cross-layer transcoders and circuit tracing for scaling interpretability across all layers. Neil Nanda's pivot to 'pragmatic interpretability' is seen as validation, not retreat, and Goodfire's Pasteur's Quadrant philosophy balances foundational research with applied use cases like novel biomarker discovery in genomics.

Anthropic, Glean & OpenRouter: How AI Moats Are Built with Deedy Das of Menlo Ventures

Nov 14, 2025 · 1:26:59

Deedy Das of Menlo Ventures returns to explain how Anthropic became the fastest-growing software company ever (zero to billions in revenue) and why Glean’s boring enterprise search moat of hard integrations and ranking problems is harder than competitors think. He reveals the $100M Anthology Fund’s strategy: backing OpenRouter, Goodfire, Prime Intellect, and Whisper—companies that solve thorny infrastructure or research problems rather than chasing apps. Das argues that model-layer companies will capture most value because building great models is harder than building apps, and that Anthropic’s product innovations like Claude Code emerge from a culture that lets researchers experiment freely. He also warns that vibe coding is becoming a cognitive crutch for engineers, eroding deep problem-solving skills, and discusses how enterprise AI market share has shifted dramatically: OpenAI went from 50% to 20%, while Anthropic rose from 12% to 32% of enterprise LLM API spend.

⚡️Automating Scientific Discovery - Jessica Rumbelow, Leap Labs

Nov 2, 2025 · 27:32

Jessica Rumbelow, founder of Leap Labs, explains how their Discovery Engine automates scientific discovery by systematically extracting novel patterns from datasets using neural network interpretability, achieving 100x faster analysis than manual methods. The tool has uncovered unexpected findings: novel T-cell receptor markers for tumor reactivity, a synergistic effect between manganese and genotype on root architecture for drought-resistant crops, and a 20% violation of the foundational surface layer assumption in meteorological modeling, worth billions if improved. Rumbelow contrasts Claude 4.1 Opus alone (which hallucinated and overgeneralized) vs. Claude with Discovery Engine (which became powerful at synthesis), arguing that language models need specialized tools for unbiased, hypothesis-free discovery. The platform is domain-agnostic, free for academics publishing their data, and expanding to multimodal datasets and industry pilots.