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Goodfire

Understand and debug your AI model

Using interpretability to understand, learn from, and design AI.
San Francisco24K followers
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The video animations could be cleaner and more polished.

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About

Silico is Goodfire's new platform for inspecting, debugging, and intentionally designing AI models, aimed at researchers and engineers who train foundation models and want to understand what is happening inside them rather than treat them as black boxes. The company says its mission is to make building AI models less like alchemy and more like a science, addressing the fact that LLMs like ChatGPT and Gemini can do amazing things but nobody knows exactly how or why they work, which can make it hard to fix their flaws or block unwanted behaviors. The product lets users decompose a model into interpretable features and see when predictions are driven by real understanding of biology, reasoning, or the physical world, or by spurious correlations and dataset artifacts , then run comprehensive diagnostics on internal representations to identify problems like undertraining, information bottlenecks, feature collapse, and other pathologies before they impact downstream performance . The launch matters now because mechanistic interpretability has moved from research curiosity to practical tooling, with mechanistic interpretability named one of MIT Technology Review's 10 Breakthrough Technologies of 2026 . Silico extends Goodfire's earlier work on Ember, a hosted API for steering model features, into a full design environment that spans life sciences, robotics and vision, and LLMs , with early partners including Arc Institute, Mayo Clinic, Microsoft, Prima Mente, and Rakuten . The pitch to model builders is concrete: find where a model is actually failing, fix the underlying features, and generalize from less data. Goodfire is led by CEO Eric Ho, who previously founded RippleMatch, a Series B AI recruiting startup backed by Goldman Sachs , alongside cofounder Daniel Balsam and a team focused on mechanistic interpretability research. The company has raised funding to support its work to rethink training and build a "model design environment," a platform for understanding, debugging, and intentionally designing AI models at scale. Early access to Silico is open now through the Goodfire website.
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Comments (13)
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Priya Venkataraman5/1/2026

Calling it Silico is a flex but the thread better deliver more than vibes by tweet 5. Pacing on this launch feels suspiciously polished, who edited it?

Tomasz Kowalczyk5/1/2026

Interpretability as a build-time tool instead of a post-hoc autopsy is the right framing. Curious how much of the SAE work from the last two years made it into the actual platform.

Adaobi Nwankwo5/1/2026

The pitch sounds like what folks were promising about ML observability circa 2021 with better internals. What does retention look like once a research team finishes their initial debugging sprint?

Dilnoza Karimova5/1/2026

Cool demo but every interpretability tool I've touched looks magical until you point it at a model that wasn't in the marketing deck. Show me a failure case you didn't cherry-pick.

Magnus Olafsson5/1/2026

I'll be honest, I still don't really get why anyone needs to look inside the model. Can't you just run more tests on the outputs and call it a day?

Rohan B.5/1/2026

Polite ping: any chance of a briefing before the rest of the thread drops? Happy to hold until you're ready to talk customers.

Marisol Quintero5/1/2026

Early access is fun but how are you actually onboarding teams, self-serve or white-glove? The gap between 'platform' and 'six engineers in a Slack channel' is where most of these die.

Felipe Aguirre5/1/2026

Hot take: the interpretability TAM is smaller than this thread implies. Most teams ship broken models and call it a feature.

kenji5/1/2026

Tweet 1 of 10 is brave in 2024. Half of us are gone by tweet 4.

Lukas Bergström5/1/2026

Are the primitives open or is this another 'open ecosystem' that means a sample notebook on GitHub? Docs link should be in tweet 2, not tweet 9.

Sanaa El-Khoury5/1/2026

If Silico is reading model internals, where do those activations live and for how long? Asking because procurement will, loudly.

Yuna Park5/1/2026

Third interpretability platform launch I've seen this quarter and the only one with a video that didn't open with a synth pad. Small win, taking it.

Harveen Sodhi5/1/2026

Reminds me of the early pitch from one of my portfolio companies in the eval space, except aimed at the model itself. The wedge feels right if the workflow is actually sticky.