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Remember our livestream last week with Ben Cherry from LiveKit? We turned it into a full guide on how to build real-time AI voice agents that can listen, respond, interrupt, call tools, and work in production. | The jump from chatbot to voice agent is bigger than it sounds. A chatbot waits for you to type. A voice agent has to handle timing, interruptions, latency, and the very human habit of changing your mind mid-sentence. It has to survive Thanksgiving dinner with API access. | Read our full LiveKit voice agents guide here. | Hereās what happened in AI today: | šæ AI backlash became a fight over data centers. š° OpenRouter raised $113M as model routing exploded. š° Researchers said language models may need sleep. šŖ Alexa can now generate custom podcasts. š Map who gets AI's upside before pitching change.
| Hey: Want to reach 700,000+ AI-hungry readers? Advertise with us!Ā | P.S: Love robots? Weāre starting a new robotics newsletter! Sign up early here. | | šæĀ AI's backlash has a physical address now | DEEP DIVE:Ā The AI backlash is really a fight over who owns the future | Data centers have made AI a local issue: they involve local land, power, water, tax deals, zoning, and neighborhoods living near the hum. | Now, two institutions are finally reacting:Ā the U.S. government is preparing for anti-tech unrest, while the Catholic Church warns against techno-corporate Babel. | The Stateās response: | WIRED obtained 1,000+ unpublished DHS, FBI, and fusion-center pages showing law enforcement tracking āanti-technology extremistsā amid CEO attacks, data center protests, and job fears.Ā A New York report warned AI could fuel ālarge-scale protestsā and āanti-tech violent extremist activity,ā a phrase absent from existing public DHS or FBI reports. US President Trump planned to sign an AI Executive Order last week that would request AI companies share their models with the gov ahead up to 90 days in advance of release,, but it got scrapped at the last minute; read the full draft here.
| That elasticity is the risk. Anti-tech violence is very real (just look at what happened to Sam Altman), but critics of the term worry the label could widen to peaceful protesters, skeptics, and local residents who donāt want a datacenter in their backyard. WIRED even flagged a nonviolent More Perfect Union data center video as a threat vector.Ā | The Churchās response:Ā In Magnifica Humanitas, Pope Leo XIV frames AI as āBabelā versus āJerusalem.ā Babel is uniformity, domination, self-sufficiency, and efficiency that sacrifices human dignity. Jerusalem is a shared rebuilding, where everyone contributes. | The Pope says technology can heal, connect, educate, and protect creation, but can also divide, exclude, and create injustice. Technology is ānever neutral,ā he writes, because it takes on the traits of those who devise, finance, regulate, and use it. | His key warning:Ā AI systems touching jobs, credit, services, reputation, or opportunity can exclude people without understandable decisions or appeals. His answer: data should carry social obligations, and AI rollouts should include job protections, retraining, and worker participation. | Why this matters:Ā Data centers are AIās defining political fault line, where jobs, power, water, wealth, health, and geopolitical competitiveness converge. | Goldman Sachs projects annual AI infrastructure spending will reach $800B by the end of 2026, and lifted its 2026 capex growth forecast from 6.5% to 7.8%. So the same infrastructure that supports U.S. AI leadership, stocks, retirement accounts, tax bases, and productivity also raises fears about water, bills, noise, air quality, land use, job loss, and who gets paid. | Our take:Ā Data centers are becoming a referendum on the AI boom, and weād be shocked if it misses the ballot box. Datacenters are quite literally a Rorschach test for the future. The State sees security risk. The Church sees legitimacy risk. Both are responding to people who feel AI is being built around, near, and sometimes on top of them, without them. | That is where the Popeās Jerusalem metaphor lands: he argues the walls of Jerusalem are technology built through shared responsibility; everyone contributes to serve a common good. The test for AI is whether ordinary people believe the future is being built alongside them, and that they own a piece of it. | |
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| Plenty of companies can launch an AI pilot. Far fewer know how to make it stick. Explore this resource hub, sponsored by Dell AI Factory with NVIDIA, for strategies, decisions, and real-world lessons on turning AI into something scalable, useful, and worth the investment. | Learn More | |
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Before you pitch any AI change at work, map who gets the upside. This is the fastest way to find the person who will quietly block your āefficiencyā project because, to them, it looks like more work, more surveillance, or fewer jobs. | Use a stakeholder upside map: a simple scan of everyone affected by a change, what they gain, what they lose, and what would make the deal feel fair. It is especially useful for automation, new agents, data projects, and team-wide AI rollouts; things your colleagues, staff, or citizens might naturally be opposed to if they donāt see the benefit. | Copy this prompt and run it before you launch a project to help you gain perspective and better bargaining chips so you can gain buy-in from other stakeholders:Ā | Iām considering this AI project: [describe the project].
Create a stakeholder upside map with these columns:
1. Stakeholder group
2. What they gain if this works
3. What they might fear or lose
4. What proof would make them trust it
5. What ownership, participation, or benefit-sharing mechanism would make the change feel fair
6. What are the downsides if this goes wrong (and how we can mitgate them through preparedness)
7. What's the first conversation I should have with each stakeholder.
Be concrete. Include employees, managers, customers, legal/compliance, IT/security, and any affected community or partner group. Consider both their legitimate upside and downside in order to help me see the full impact of this project and navigate it's challenges as well as communicate it's benefits.
| Resistance often shows up as āpeople hate change,ā but a lot of the time, people hate being handed someone elseās upside as their downside.Ā | Now, uno-reverse that! Before you pitch a new AI workflow, ask your chatbot to argue against it from the perspective of the person most likely to be affected. You will usually find the real blocker faster: extra review work, unclear accountability, job insecurity, data exposure, or the fear that āefficiencyā means fewer humans later. | Act as the person most likely to oppose this AI project: [describe it].
Write the strongest good-faith argument against it.
Focus on risks, incentives, hidden costs, trust issues, and what (if anything) would make you support it.
| Oh, and if you want to take this a step further to consider every ethical aspect of an initiative before you launch it, you could copy the above prompt along with the Popeās Magnifica Humanitas doc and ask the AI to āhelp me create a prompt like this one Iām sharing, using the Magnifica Humanitas doc, to ask questions that aim to address each of the ethical points the doc presents to build an āethical responsibility map" before launching a new initiative.āĀ Ā | You might not be able to answer every ethical question on every project you pursue, but hey, at least youāll have taken the step to think about itā¦ more than can be said about a lot of projects TBH. | Total AI beginner? Start here (goes with this video). | Have a specific skill you want to learn?Ā Request it here.Ā | | |
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| Join us live this Thursday for A Total Beginnerās Guide to AI Agents & Automation. Weāll break down what AI agents actually are, how automation workflows work, and how to start using tools like ChatGPT, Claude, Make, and ClickUp without getting buried in jargon. Bring your questions (seriously, anything) and leave with a clearer sense of how to get started using AI agents as soon (and as easily) as humanly possible. Oh, and check this out:Ā no coding required. | | š° Around the Horn | | OpenRouter raised $113M from CapitalG and others after weekly volume hit 25T tokens across 400+ models and 8M+ users. Elon Musk said xAI finished training Grok V9-Medium, a 1.5T-parameter model expected in 2-3 weeks. Qualcomm struck a deal to sell millions of AI chips to ByteDance for data centers (Reuters). China expanded overseas travel curbs to top AI talent at private firms, including Alibaba and DeepSeek. Anthropic grew revenue 5x in the first five months of 2026 to ~$45B annualized (roughly 35% higher than OpenAI's ~$33B) and is projecting a $559M Q2 operating profit while OpenAI lost at least $7B in Q1 on a -122% operating margin. Baseten, whose inference software helps developers run AI models (mostly open-source) faster and cheaper on Nvidia GPUs rented from AWS, Google, and other clouds, was in talks to raise $1B at an $11B valuation ā more than double the $5B valuation from its round just three months ago. Figure AI signed its first large-scale retail supply chain deal, deploying Figure 03 humanoids at JCPenneyās parent company Reno, Nevada based distribution center.
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šĀ Midweek Wisdom | Agent researchers argued the next AI bottleneck is the system around the model: memory, tools, context, routing, and verification. Researchers proposed giving language models āsleep,ā where they consolidate recent context into memory before clearing their cache. KIDBench tested child-facing chatbot safety and found multi-turn conversations can degrade response quality by 6-24%. MiniMax teased M3ās sparse-attention system, claiming 9.7x faster prefill and 15.6x faster decode at 1M tokens. The Verge traced how AI weapons, Project Maven, and military procurement are pushing AI warfare from theory into deployment.
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