SAIL Conference

Andrew White






FutureHouse
Nov 3, 2026

AI Progress

Model intelligence doubles every ~4 months

METR Task Completion Benchmark metr.org

Effect is Visible in Economy

AI models are superhuman in math

Millennium Prize

OpenAI reports a solution to Navier–Stokes in September 2026.

Only 1 other Millennium Prize problem solved in 25 years.

ARC-AGI

2025: o3 scores 87.5% for ~$500,000.

2026: Astra scores higher for ~$20.

Math Olympiad

OAI, Ant, and many start-ups got perfect scores 42/42 on IMO 2026.

1 Millennium Prize / NYT  2 ARC-AGI / Noam Brown  3 IMO / China Daily

1 NASA OIG Report oig.nasa.gov  2 US FHWA fhwa.dot.gov  3 US Telecom Capex Report ustelecom.org  4 Morgan Stanley AI Market Trends 2026

What about in science?

Labbench 2

1,912 questions across accessing data, reading patents, reading figures, protocol understanding, etc.

Example: Deletion of which residues from C. elegans protein COSA-1 would most likely affect the ability of COSA-1 to recruit MSH5 and ZHP3?

Residues 31–40

Labbench 2 Accuracy

FutureHouse

  • FutureHouse founded in 2023
  • Cofounded by Andrew White, Sam Rodriques
  • Based in San Francisco with Wetlab
  • Funded primarily by Eric Schmidt

FutureHouse Timeline

Introduction to AI Agents

Agent: trained, makes decisions

Environment: untrained, has tools, state

How are agents trained?

  1. Pre-training — broad knowledge via next-token prediction
  2. Supervised Fine-Tuning (SFT) — learn from expert instruction–response pairs
  3. Reinforcement Learning (RL) — optimize through environment interaction with verifiable rewards

RL expands capabilities beyond what supervised data can teach

Verifiable Rewards

Computational checks (code execution, tool outputs) produce objective reward signals — no human feedback needed

LabBench2: verifiable tasks as RL training signal

Laurent et al., LabBench2, 2026; Narayanan et al., Aviary, 2024; 2025 NVIDIA Technical Blog

Behavior Changes

Training Curve

FutureHouse Agents

Name Environment Key Tools
PaperQA Literature Research Search, Citation Traversal
ProteinCrow Designing novel proteins AlphaFold2, Molecular Dynamics
ChemCrow/Phoenix Designing new molecules Retrosynthesis, self-driving robotic lab
Data analysis crow Generating discoveries from data bioinformatics tools, code, file system

Complete cycle of disease to target to drug

ROBIN: A Multi-Agent System for Automating Scientific Discovery Nature, 19 May 2026

Ali Essam Ghareeb*, Benjamin Chang*, Ludovico Mitchener, Angela Yiu, Caralyn J. Szostkiewicz, Jon M. Laurent, Muhammed T. Razzak, Andrew D. White†, Michaela M. Hinks‡, Samuel G. Rodriques

Robin proposes follow-up experiments

Robin optimizes the therapeutic candidates

Edison Scientific

  • Spinout from FutureHouse formed in 2025
  • AIxBio Research Lab that partners with biotech and pharma
  • 80 employees
  • $70M in seed financing
  • offices in New York, Boston, San Francisco
  • Announced major deal with Pfizer last week.

State of Agents in 2026

3 Generations of Agents

ReAct

Original chain of thought + tools agents

2022

Tool Calling

Tool calling schema and MCP

2023

Code-writing

Code writing agents in a persistent sandboxed computer.

2025

Tool-State Paradox

$T_1=$ alphafold2
$T_2=$ $\beta$-sheet percentage

$T_2\rightarrow$ error, no pdb
$T_1,T_2\rightarrow$ success
$T_1,T_1,T_2\rightarrow$ need to treat multiple structures

Engineers must consider $O(2^{N})$ interactions between tools: will not scale past ~10 tools

Code-writing agents

LLMs manage state, you must only write good code

Challenges:

  1. Must create persistent sandboxed computers for agents
  2. Must solve security and authentication for agents

Kosmos Agent

A persistent always-on colleague that has access to 80% of public data, our chemistry and literature agents, and world models of biology

Security Models for Code-Writing Agents

User is the boundary

Claude Code · Codex

Code runs on the user's machine with user authentication.

Isolation is the boundary

OpenClaw · Hermes Agent · NemoClaw

Code runs on a separate machine with agent authentication.

Zero-trust

Edison

Separate machine and container, supervised actions, network interception, secrets isolation, ephemeral authentication, cost governance, and supply-chain protection.

questions