#podcast

News · 2026-08-22

The evolution of agent frameworks: the interface no longer guards the model, but our attention

Latent Space analyzes the shift in agent architectures. What used to be done by external software wrappers is being absorbed directly into the model weights. The remaining infrastructure is changing its purpose – it no longer controls AI, but filters our interaction with it.

News · 2026-07-21

Xaira bets on X-Atlas because bigger models hit a wall without causal data

Latent Space profiles Xaira Therapeutics and its X-Cell model for drug discovery. The sober point is that cell models cannot be rescued by more parameters if the data lacks causal interventions.

News · 2026-07-24

FLUX 3 Video pushes Black Forest Labs into multimodal production

Latent Space describes FLUX 3 as a multimodal flow model for video, audio, keyframes and longer sequences. If the performance claims and the open Dev version hold, Black Forest Labs is no longer just an image lab, but a supplier of a generative production layer.

News · 2026-07-23

Poolside frames the model factory as the product, not just one model

Latent Space’s interview with Eiso Kant presents Poolside as a model factory: fewer than 70 researchers, 10000 to 20000 experiments per month and Laguna S 2.1 with 118B parameters. The story is about industrializing training, not just another coding model.

News · 2026-06-15

Microsoft used Build to act like a model lab, not just a distributor

Latent Space frames Microsoft Build as the moment Microsoft showed its own MAI models alongside Copilot, Windows and Web IQ. The key ambition is to control data, inference and developer workflow at once, rather than leaving that leverage to partners.

News · 2026-06-15

Andon Labs tests agents where benchmarks stop: money, people and shelves

Latent Space's interview with Andon Labs shows evals that look less like exams and more like running a small business. The key ingredients are long horizons and real consequences.

News · 2026-06-15

Bad RL environments do not train agents, they teach them to trust a broken world

Latent Space published Auriel W's piece on why low-quality RL environments damage agent training. The point is simple: in reinforcement learning, the environment is the data generator, so a harness bug becomes training material.

News · 2026-06-09

Agent cost is no longer a footnote. It is an engineering expense

Simon Willison shows how he manually added pricing for Claude Fable 5 in AgentsView and immediately saw the cost of local coding agents by project. The small trick points to a bigger shift: AI coding is starting to look like infrastructure consumption, not an app subscription.

News · 2026-06-02

GitHub is preparing for a world where agents write commits at scale

The Latent Space interview with Kyle Daigle frames GitHub as a platform under pressure from agentic coding. The point is not another Copilot feature, but whether infrastructure built for human pace can absorb software produced by machines.

News · 2026-06-01

Video generation is moving from clip output to canvas agent

Latent Space frames xAI Grok Imagine, through an interview with Ethan He, as a move from one shot video generation toward video agents. The thesis will be proven less by demo quality than by whether the system can iterate through a whole creative task.

News · 2026-05-01

Coding agents leave the IDE: Codex and Claude show what comes after programming

Latent Space AINews observes a shift they call "breaking containment": coding agents like Codex and Claude are no longer just tools for writing code but are expanding into knowledge work and creative workflows broadly.

News · 2025-09-16

Latent Space: Greg Brockman on GPT-5 and Codex as the agentic layer of software development

Latent Space published a belated episode with Greg Brockman on GPT-5 and Codex, plus editorial takes on the GPT-5-Codex model combination. This is a podcast episode and pointer, not a standalone analytical essay.

News · 2025-07-02

Jack Morris goes against the current: information theory, not agents or benchmarks

Latent Space profiles Jack Morris, a PhD student who deliberately is not working on agents, benchmarks or VS Code forks. He studies the information-theoretic foundations of language models: embeddings, latent space and compression. This is a podcast interview and pointer.