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Instinct founder on an app-less personal Agent: How a 14-person team supports a $10 billion valuation

Instinct, an AI personal agent company founded a year ago with 14 employees, has reached a $10 billion valuation. Founder Noah Shinn discussed its product and business model on the podcast "Invest Like The Best." Instinct has no standalone app; users book flights and cancel subscriptions through text messages, phone calls, and emails, and its annualized transaction volume has reached the $1 billion scale, about half of which comes from business travel. It is free for users, and the company charges commissions to merchants that profit from transactions; Noah explicitly rejects the advertising model. About 40% of users link a credit card after roughly three weeks of use, and this group has a retention rate of about 80%.

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English translation is being prepared.

TechCrunch rounds up AI agents that live in text messages

TechCrunch reviewed more than ten AI agents that require no app download and interact directly via text message, covering general-purpose assistants as well as specialized products for home, travel, content creation, and work. These agents can remember context, connect to existing apps, and complete tasks on users' behalf, such as scheduling appointments, booking restaurants, sending emails, and shopping online. The article also lists each product's launch date, funding situation, and subscription price, such as Instinct raising $1 billion at a $10 billion valuation in September 2026, Fambot securing $3.5 million in pre-seed funding, and Town completing a $55 million Series A round.

OpenAI Team Responds to Computer Use Progress Doubts, Recaps One-Week Sprint on Decisions API

In a podcast after OpenAI DevDay, Ari Weinstein, who is in charge of the Computer Use agent, responded to Dwarkesh's doubts about Computer Use progressing slowly, saying it is now completely different from a few months ago because the model has become better at debugging and retrying, and can write JavaScript to execute multiple steps at once while combining screenshots, accessibility, DOM, and Playwright. He also mentioned that Dots provides each Dot with a cloud Linux virtual computer, and that Computer Use has entered the Agents API. Nikunj Handa, head of the OpenAI API team, introduced updates to GPT-6 such as asynchronous tool calling, mid-turn steering, WebSockets, UltraFast inference, prompt caching and pre-warming, and compaction, and said the Decisions API is based on Luna weights, with no new model trained, and took only about a week from the emergence of the idea to a prototype.

OpenAI and Meta Bet on AI Agents First, Hardware Later

The Verge reports that OpenAI and Meta plan to use cute software agents in the coming year to pave the way for physical AI hardware. OpenAI unveiled its agent platform Dots at DevDay and is partnering with former Apple designer Jony Ive; public documents show the hardware could ship as early as February 2027. Meta, meanwhile, has tied its recently released Muse agent directly to a pendant-style device called Muse Charm, which it plans to launch before this year's holiday shopping season. Both companies hope to first get users accustomed to and dependent on agents, then guide them toward accepting physical forms.

Frequent rear-end crashes involving assisted driving: system disengages at the last second, but liability still falls on the driver

On the Anshun section of the Shanghai-Kunming Expressway, a vehicle with assisted driving enabled rear-ended a large truck at night; when the system signaled disengagement, it was less than 10 meters from the vehicle ahead, leaving the driver no time to take over. The article reviews similar cases in Binzhou, Shandong, and on the Jiqing Expressway, noting that all mass-produced vehicles on the market are legally L2-level assisted driving, that the Supreme People's Court has made clear the driver remains the responsible party after activating the system, and that automakers need only prove they issued a warning and disengaged to be exempt from liability. Two mandatory national standards for intelligent connected vehicles taking effect in 2027 require L3 systems to give drivers at least 10 seconds to respond after issuing a takeover request, otherwise triggering a deceleration and pull-over to a stop.

Anthropic's Thariq on the Next Phase of Claude Code: Claude Mods, Projects, and Agent Security

Anthropic's Thariq Shihipar introduced the next phase of Claude Code on the Latent Space podcast, including Claude Mods for customizable harnesses, Projects, Claude Tag, and recent releases such as Opus 5.5 and Sonnet 5.5. He calls prompting the core skill for using Claude Code, recommending that users first spend time filling in context and allocate effort by task—for example, high or maximum for code review and security, and low or medium for UI-type tasks. He also discussed agent security, including sandboxing, prompt injection, Auto Mode, and Anthropic's "Pacing the Frontier" position.

TypeSafe CEO Diogo Almeida on Jev: Building a System One Model for Production, Not for God

InstructGPT paper author and TypeSafe CEO Diogo Almeida detailed his new model Jev on the Latent Space podcast, describing it as a System One large programmatic model oriented toward code consumption, with its core innovation being an unpublished RLCD (reinforcement learning for calibrated decision-making), optimized for "intelligence per dollar" rather than human preference feedback. He criticized RLHF for causing mode collapse, sycophancy, and hallucinations, arguing that safety alignment suits products like ChatGPT but fragments intelligence at the API layer, and said TypeSafe would rather be seen as a data lab, refusing to publish benchmark tests. He revealed that Jev's daily token consumption has exceeded one trillion since launch, and previewed follow-up models such as ReasoningJev.

Nathan Lambert: AI Safety Is Underprepared, as Seen from the Frontier Model Hacking Incident

Nathan Lambert published an article in Interconnects reviewing the OpenAI-HuggingFace hacking incident, arguing that the AI industry as a whole is severely underprepared for the risks of the next 12-24 months. He noted that OpenAI's models are stronger than Claude in inference persistence, possibly because OpenAI has bet more heavily on inference-time scaling, and that such models that continuously pursue goals deserve more safety attention. He also argued that public models and open research are irreplaceable for understanding frontier risks; currently open models lag by only 3-9 months, and restricting open models would instead weaken society's ability to respond.

Open models have only 6 months left? Nathan Lambert on tightening regulation and the distillation dispute

Nathan Lambert believes that the most severe feasibility test for open-weight models is now unfolding: the White House is discussing managing open models through a new executive order, which may affect only Chinese-origin models and government uses. He judges that the most likely action is to ban, or indefinitely postpone, within the next 6 months open-weight models whose capabilities clearly exceed the GPT 5.5, Claude Opus 4.8, or GLM-5.2 range, and such models are currently most likely to come from Chinese companies. He criticizes the distillation issue led by Anthropic as having evolved into regulatory capture, and believes that if the United States alone bans imports of the relevant models, the global open-source ecosystem will continue, and instead make the United States itself harder to predict.