Eiso Kant
Co-Founder & CTO, Poolside · 1 appearance on the record.
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founderexecutiveengineerinvestor@eisokant ↗LinkedIn ↗poolside.ai ↗
Eiso Kant is the co-founder and CTO of Poolside, an AI foundation model company focused on software engineering. He previously founded Athenian and source{d}, applying artificial intelligence to code analysis and developer tools.
43statements → 13claims → 5claims resolved → 80%fully supported → 3.81/5average certainty → 2.35/5average debate potential → 3said about them ↓
4 supported 1 partly supported 0 contradicted 1 not yet assessed 7 not checkable as stated how the 13 claims stand · each chip opens the sources
4 predictions · 9 assertions · 7 opinions · 11 insights · 11 disclosures · 1 what if · every statement was checked. The predictions and assertions are the 13 claims: statements the public record can support or contradict. 5 are resolved, 1 is not yet assessed, and 7 name no date, number or outcome precise enough to check. Everything else (opinions, insights, what ifs, disclosures) can never be settled by the record, so it carries no assessment.
The record, in short
What the tape says about how Eiso argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.
Their most notable supported claim
Kant: Major AI labs did not prioritize RL for LLMs three years ago
“And the second was that reinforcement learning was going to be the biggest driver for LLM capabilities. Today, very obvious three years ago was not an opinion held or direction held at either OpenAI or Google or Anthropic or others.”
Everything Eiso Kant said on Latent Space that made the record, most notable first. Filter by type, assessment or year in the ledger →
Kant: Solving knowledge work does not require 2-3 orders of magnitude scaling
“I'm no longer thinking that we need two or three orders of magnitude on the largest models to be able to You know, solve knowledge work the accounting, the legal, the code that we write.”
Kant: Anthropic's MCP and explicit tool calling abstractions are stupid
“I think MCP and tools are stupid.”
Kant: Restricting open-weight AI models at current capability levels will hurt innovation
“We are not at a level of capability right now. That we should start restricting, you know, open models in any way, shape or form. I think it will hurt innovation if we do so.”
Kant: Major AI labs did not prioritize RL for LLMs three years ago
“And the second was that reinforcement learning was going to be the biggest driver for LLM capabilities. Today, very obvious three years ago was not an opinion held or direction held at either OpenAI or Google or Anthropic or others.”
Kant: Open weights alone do not allow developers to recreate AI models
“Weights are a binary. Let's call them what they are. Yes, we can modify it and we can change them, but like, Giving someone the weights does not allow them ultimately to recreate what you're doing.”
Kant: Labs benefiting from Chinese open research have an obligation to give back
“The incredible Chinese lab has done an amazing job at sharing their research, and we have definitely take, like, been on the receiving end of taking advantage of that. So When you're on the receiving end of something coming to you, I think you also have kind o…”
Kant: Catching up to frontier AI labs will soon become unfeasible
“We've got a small window before models are Really impacting recursive self-improvement to a level where catching up otherwise might become unfeasible.”
Kant: Industry will squeeze far more capability from smaller models via behavior
“We are going to be able to squeeze so much more out of smaller models than I think we had imagined in the industry. Because yes, there's intelligence and larger models are more intelligent. Like no doubt about it. We should continue to scale up. But the behavi…”
Kant: Focusing solely on small open-source models is a cop out
“I think we ultimately only succeed if we scale our models as large as our competition. I do not, like, I think we should not put our head in the sand and say we're going to be king of open source small models. I think that's Frankly, it's a cop out.”
Kant: Reinforcement learning will move earlier into LLM pre-training
“I have I would say a not commonly held opinion that reinforcement learning will move earlier and earlier into pre-training.”
Kant: Laguna S outperforms models two to three times its size
“When you look at the benchmarks and start using it, you'll realize that we are outperforming models two or three times their size.”
Kant: Prompts stuffed with dozens of tools will vanish in 12 months
“I think we will in 12 months not see a single system prompt that is stuffed with 20 or 30 or 40 tools anymore.”
Kant: Pre-training compute runs are not the expensive part of AI
“The training run is not the expensive part. The training run is a very anticlimactic event, right?”
Kant: AI will become the world's most demanded commodity with commoditizing margins
“Intelligence is the most in life. You're going to be the world's most demanded commodity. It will more commoditize in margin and price.”
Kant: RL compute cannot scale like pre-training due to task batch constraints
“And RL is batch size constraint, right? So like you are ultimately in your batch size constraint because you don't have infinite tasks, right? When you've got the entire web, you can be much more flexible in scaling up your batch size because you've got the en…”
Kant: Poolside is releasing open weights to prevent five-company AI concentration
“I think it all just came down to one thing and I'll stop the monologue is the fact that I rather live in a world that has a hundred foundation model companies than a world that has five. Even if I was one of the five. And the smallest and most meaningful contr…”
Kant: Foundation model building is 90% engineering rather than research
“Model building is ultimately 90% engineering. And I think we all know it in the industry, because if you look at words, every researcher spending their time, they're spending their time writing code, right? Looking at data and writing code.”
Kant: Poolside trains and launches models in five to eight weeks
“Laguna access two that we launched. It was five weeks from the beginning of pre-training to launch. The model that we're going to talk about today was eight weeks from start to pre-training to launch.”
Kant: 95% of foundation model building is data and compute efficiency
“I actually think you can sum down. So I saw 90. Five percent of model building to just doing, you're just doing two things. You're improving data or you're improving compute efficiency.”
Kant: Poolside's 8B-active Laguna S solved Erdős 397 on DGX Spark
“A 118,000,000,008 B active model, which is not that large. It fits on a DGX spark and still runs at, you know, 3040 tokens a second on a spark is able to solve. Erdos three 97 independently. It's able to do complex programming tasks.”
Kant: Mid-training stages exist due to organizational silos, not necessity
“Mid-training exists because there's a mid-training team now, right? There's people or like people decide to focus on like a mid-training effort. But what you really want is engineering. And skill of experiments that allows for a much more continuous spectrum t…”
Kant: Base model pre-training is required to unlock major capabilities
“You can't fine tune your way to success, right? Major capabilities emerge from training a base model made accurate and useful during fine tuning.”
The other half of the tape: Eiso Kant's own voice is left out of every number here. Other people bring the name up 3 times in 2 episodes on Latent Space. every mention, with the transcript →
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Appearances (1)
| Episode | Date | Speaking time |
|---|---|---|
| The AI Frontier: from open weights to open research — Eiso Kant, Poolside AI | Jul 22, 2026 | 1h 26m |