A product discussed on Latent Space.

Dreamer: the Agent OS for Everyone — David Singleton
Mar 20, 2026 · 1:04:23
David Singleton, former Stripe CTO, introduces Dreamer, a consumer platform for discovering, building, and using AI agents and agentic apps centered on a personal Sidekick that acts as both companion and kernel-like traffic cop. He demonstrates building a conference schedule app in 25 minutes via natural language, a ski trip app that splits expenses, and tools like Gmail, Google Search, and live sports data feeds. Dreamer features an open tool ecosystem where builders get paid, a private waitlist skip at dreamer.com/latentspace, and a Builder-in-Residence program with a $10,000 prize for the best tool by mid-April. Singleton explains the OS model with Sidekick as kernel and agents as users enforcing data isolation and cross-agent coordination only through Sidekick. He shares insights on tiny-team building (six-person core, 17 total), hiring engineers who collaborate with coding agents, and LLMs' current lack of taste and creativity.

Captaining IMO Gold, Deep Think, On-Policy RL, Feeling the AGI in Singapore — Yi Tay
Jan 23, 2026 · 1:32:05
Yi Tay, who leads Google DeepMind's Reasoning and AGI team in Singapore, explains how Gemini Deep Think achieved IMO Gold by abandoning symbolic AlphaProof for an end-to-end RL-trained model. He details the on-policy RL philosophy—models learn from their own generated outputs rather than imitating others—and the critical role of self-consistency through parallel sampling and internal verification. Tay describes the IMO effort: four co-captains in different time zones, a one-week training sprint, a live competition in Australia where researchers punched in problems as they were released, and the tension of waiting for human scores to determine the gold threshold. He discusses why the team believes one model must subsume everything for AGI, the data efficiency gap compared to humans, and his hiring focus on raw talent and research taste. Tay also shares his personal fitness transformation—losing 23 kilos and improving HRV—as integral to research productivity.
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