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Trump’s AI framework targets state laws, shifts child safety burden to parents

The Trump administration on Friday laid out a legislative framework for a singular policy for AI in the United States. The framework would centralize power in Washington by preempting state AI laws, potentially undercutting the recent surge of efforts from states to regulate the use and development of the technology.

“This framework can only succeed if it is applied uniformly across the United States,” reads a White House statement on the framework. “A patchwork of conflicting state laws would undermine American innovation and our ability to lead in the global AI race.”

The framework outlines seven key objectives that prioritize innovation and scaling AI, and proposes a centralized federal approach that would override stricter state-level regulations. It places significant responsibility on parents for issues like child safety, and lays out relatively soft, nonbinding expectations for platform accountability. 

For example, it says Congress should require AI companies to implement features that “reduce the risks of sexual exploitation and harm to minors,” but does not lay out any clear, enforceable requirements.

Trump’s framework comes three months after he signed an executive order directing federal agencies to challenge state AI laws. The order gave the Commerce Department 90 days to compile a list of “onerous” state AI laws, potentially risking states’ eligibility for federal funds like broadband grants. The agency has yet to publish that list.

The order also directed the administration to work with Congress on a uniform AI law. That vision is coming into focus, and it mirrors Trump’s earlier AI strategy, which focused less on guardrails and more on promoting companies’ growth.

The new framework proposes a “minimally burdensome national standard,” echoing the administration’s broader push to “remove outdated or unnecessary barriers to innovation” and accelerate AI adoptions across industries. This is a pro-growth, light-touch regulatory approach championed by “accelerationists,” one of whom is White House AI czar and venture capitalist David Sacks. 

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While the framework nods to federalism, the carve-outs for states are relatively narrow, preserving only their authority over general laws like fraud and child protection, zoning, and state use of AI. It draws a hard line against states regulating AI development itself, which it says is an “inherently interstate” issue tied to national security and foreign policy. 

The framework also seeks to prevent states from “penaliz[ing] AI developers for a third party’s unlawful conduct involving their models” — a key liability shield for developers.

Missing from that framework are any gestures toward liability frameworks, independent oversight, or enforcement mechanisms for potential novel harms caused by AI. In effect, the framework would centralize AI policymaking in Washington while narrowing the space for states to act as early regulators of emerging risks.

Critics say states are the sandboxes of democracy and have been quicker to pass laws around emerging risks. Notably, New York’s RAISE Act and California’s SB-53 seek to ensure large AI companies have and adhere to safety protocols that are publicly documented. 

“White House AI czar David Sacks continues to do the bidding of Big Tech at the expense of regular, hardworking Americans,” said Brendan Steinhauser, CEO of The Alliance for Secure AI. “This federal AI framework seeks to prevent states from legislating on AI and provides no path to accountability for AI developers for the harms caused by their products.” 

Many in the AI industry are celebrating this direction because it gives them broader liberties to “innovate” without the threat of regulation.

“This framework is exactly what startups have been asking for: a clear national standard so they can build fast and scale,” Teresa Carlson, president of General Catalyst Institute, told TechCrunch. “Founders shouldn’t have to navigate a patchwork of conflicting state AI laws that impede innovation.”

The framework was issued at a moment when child safety has emerged as a central flashpoint in the debate over AI. Certain states have moved aggressively to pass laws aimed at protecting minors and placing more responsibility on tech companies. The administration’s proposal points in a different direction, placing greater emphasis on parental control than platform accountability. 

“Parents are best equipped to manage their children’s digital environment and upbringing,” the framework reads. “The Administration is calling on Congress to give parents tools to effectively do that, such as account controls to protect their children’s privacy and manage their device use.”

The framework also says the administration “believes” that AI platforms should “implement features to reduce potential sexual exploitation of children and encouragement of self-harm.” While it calls on Congress to require such safeguards and affirms that existing laws, including those banning child sexual abuse materials, should apply to AI systems, the proposal employs qualifiers like “commercially reasonable” and stops short of laying out clear prerequisites.

On the topic of copyright, the framework attempts to find a middle ground between protecting creators and allowing AI systems to be trained on existing works, citing the need for “fair use.” That kind of language mirrors arguments AI companies have made as they face a growing number of copyright lawsuits over their training data. 

The main guardrails Trump’s AI framework seem to outline involve ensuring “AI can pursue truth and accuracy without limitation.” Specifically, it focuses on preventing government-driven censorship, rather than platform moderation itself. 

“Congress should prevent the United States government from coercing technology providers, including AI providers, to ban, compel, or alter content based on partisan or ideological agendas,” the framework reads. It also instructs Congress to provide a way for Americans to pursue legal redress against government agencies that seek to censor expression on AI platforms or dictate information provided by an AI platform.

The framework comes as Anthropic is suing the government for allegedly infringing on its First Amendment rights after the Department of Defense (DOD) labeled it a supply-chain risk. Anthropic argues that the DOD is designating it as such in retaliation for not allowing the military to use its AI products for mass surveillance of Americans or for making targeting and firing decisions in autonomous lethal weapons. Trump has referred to Anthropic and its CEO Dario Amodei as “woke” and a “radical leftist.”

The framework’s language, which emphasizes protecting “lawful political expression or dissent,” seems to build on Trump’s earlier executive order targeting “woke AI,” which pushed federal agencies to adopt systems deemed ideologically neutral. 

It’s unclear what qualifies as censorship versus standard content moderation, so such language could make it difficult for regulators to coordinate with platforms on issues like misinformation, election interference, or public safety risks. 

Samir Jain, vice president of policy at the Center for Democracy and Technology, pointed out: “[The framework] rightly says that the government should not coerce AI companies to ban or alter content based on ‘partisan or ideological agendas,’ yet the Administration’s ‘woke AI’ Executive Order this summer does exactly that.”

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Glean’s top line crosses $300M as AI budget cutting becomes its major selling point

Glean, a company often described as the Google for enterprise, said it has reached $300 million in annual recurring revenue (ARR), a three-fold increase from the $100 million milestone it reached just 15 months ago.

While many AI startups are growing at a blistering pace, Glean’s progress is particularly remarkable. After years of essentially being the only player in the category, the seven-year-old startup is accelerating its growth as tech giants enter the enterprise AI search market with rival products.

“The first four or five years of our existence, we had no competition,” Glean CEO Arvind Jain told TechCrunch. “Given how important search is to make AI work in the enterprise, every single company in the world wants to be in this space.”

Tech heavyweights building Glean-like tools include Google, Microsoft, OpenAI, Anthropic, Salesforce, and Atlassian.

Jain maintains there’s value in being a first mover in the space, but that it’s also equally important to offer a better product.

What Glean does better than its competition, according to Jain, comes down to the deep understanding that its AI tools have of customers’ business needs. Glean’s AI achieves this knowledge — a concept captured by the new, popular term “context graph” — by connecting to and learning from enterprises’ internal software systems.

Jain claims that Glean’s context graph also helps enterprises cut AI computing costs.

“If you connect your AI to Glean, it gives you all the information that you need to do your work, and that results in AI consuming far fewer tokens compared to if you unleash AI onto your systems directly,” Jain said. That’s because with Glean, AI ends up performing fewer operations, he added.

At a time when many companies are blowing through their AI budgets, those token cost savings have become a major selling point for the company.

“One of the things you know our customers really like about Glean is the fact that we can reduce your AI bill significantly,” he said.

The company, which was last valued at $7.2 billion when it raised a $150 million Series F last June, offers various pricing structures to its customers, which include Databricks, Reddit, Pinterest, and Samsung.

According to Jain, Glean offers both a consumption-based model, where clients pay per use, and a hybrid model that combines a fixed monthly fee for active users with separate usage fees for model consumption.

Glean is definitely not the first company to do this, but it’s worth pointing out that the company’s $300 million milestone cannot be fully described as traditional ARR, because a consumption model by definition doesn’t have a strictly recurring component.

Pure consumption pricing models depend on fluctuating user activity rather than predictable subscription renewals, therefore a portion of Glean’s top line is more accurately described as an annualized revenue run rate.

Glean did not immediately respond to a request for comment; this post will be updated if the company replies.

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Final 24 hours to save up to $410 on your TechCrunch Disrupt 2026 ticket

This is it. The countdown is almost over. You now have until tonight at 11:59 p.m. PT to lock in Early Bird savings of up to $410 for TechCrunch Disrupt 2026 before prices increase.

If Disrupt has been on your must-attend list, this is your final chance to secure the lowest available rates before the next price jump hits. Once the deadline passes, so do the savings.

Register now and join 10,000+ founders, investors, operators, and innovators at Moscone West in San Francisco from October 13–15 for three days packed with networking, startup discovery, and conversations shaping the future of tech. Bring a plus-one at 50%, or bring a group to get an up to 30% discount.

TechCrunch Disrupt 2026 24 hours left

What makes Disrupt worth attending year after year

TechCrunch Disrupt is where startup momentum accelerates. The event brings together the people actively building, funding, and scaling what’s next across AI, fintech, SaaS, climate, cybersecurity, consumer tech, and beyond.

Attendees come to Disrupt for:

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With 300+ exhibiting startupsStartup Battlefield 200, curated networking experiences, and multiple stages of programming, Disrupt is built to help attendees make meaningful connections and real business progress.

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Built for the people shaping what’s next

Disrupt is designed for founders raising capital, investors sourcing opportunities, operators scaling companies, and innovators looking for an edge. Whether you’re launching your next startup, growing your network, or tracking the future of technology, Disrupt puts you in the room with the people driving the industry forward.

Hear directly from tech leaders shaping the industry

Every year, Disrupt brings together hundreds of influential voices across startups and venture capital. Past speakers have included leaders from the companies and firms shaping the future of AI, enterprise software, fintech, consumer tech, and more.

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This year will deliver the same high-caliber experience, with 200+ sessions across six industry-focused stages, plus roundtables and breakouts covering scaling, AI, fintech, infrastructure, robotics, and emerging technologies. Explore the growing agenda to see the latest sessions and speaker announcements.

Speakers include:

Savings of up to $410 end tonight at 11:59 p.m. PT

Early Bird savings of up to $410 end tonight at 11:59 p.m. PT. After that, ticket prices increase.

Register now to secure your TechCrunch Disrupt 2026 pass at a low rate before the deadline expires. Bringing more than just you? Save 50% on a second ticket, or up to 30% on community passes.

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Today is the last day to apply to speak at TechCrunch Disrupt 2026

TechCrunch Disrupt 2026 returns October 13–15 to Moscone West in San Francisco — and applications to speak are open for just a few more hours.

We’re inviting founders, investors, operators, and technology experts to apply for a chance to take the stage at one of the most influential tech events of the year.

More than 10,000 startup and VC leaders will gather at Disrupt 2026 to explore what’s next in AI, scaling, fintech, infrastructure, robotics, and the future of innovation.

Applications close tonight at 11:59 p.m. PT. Apply now to share your expertise and help shape the conversations defining the tech industry.

Pick your session format

We’re looking for high-impact speakers to lead one of two session types:

Breakout Sessions: A 30-minute talk (up to 4 speakers, including a moderator) with a 20-minute audience Q&A. Capacity: 100 attendees.

Roundtables: A 30-minute speaker-led group discussion, designed for up to 40 participants. No slides or AV — just insight and conversation.

TechCrunch Disrupt 2024 Breakout Session
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How the application process works

Each application will be carefully reviewed by our editorial team. Finalists will be selected for the Audience Choice vote — where TechCrunch readers choose which sessions make it to the Disrupt Stage. Learn more about speaking on Disrupt’s Call for Content page.

Lead the conversation at Disrupt 2026

If you have actionable insights, real-world experience, and a desire to contribute meaningfully to the tech ecosystem, we want to hear from you. Submit your application before today’s deadline.

TechCrunch Disrupt 2026, October 13-15

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