Artificial Intelligence

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How to AI

Illustration: Brendan Lynch/Axios

The No. 1 pushback we get from AI skeptics or newbies is: "It's overhyped. I asked it something and it spit out an unimpressive answer!" Truth bomb: It's not the AI. It's you, Jim VandeHei and Dan Cox write. Why it matters: Ask top large language models like ChatGPT something simple or generic, and you will get a simple or generic answer. Ask the right questions the right way, and you will often get magic. Jim asked Dan Cox, our CTO and AI leader, to help him craft six ways for ordinary users to get more extraordinary answers. It starts with prompts — the very questions you pose to ChatGPT, Claude, Gemini, Grok or Perplexity. Just in time for performance-review season, here are six tips (for both reviewers & reviewees): 1. 🔁 It's a conversation, not a search engine. The biggest mistake newbies make is treating AI like Google — one question, one answer, done. The magic happens in the back-and-forth. Ask a question. Read the answer. Then push: "Make it shorter ... Give me three alternatives ... That's too formal ... What am I missing?" The best outputs come from the fifth or sixth exchange. Example: You ask for help requesting a raise. The first draft is generic. You say: "Too corporate. I've been here six years and my boss is informal — make it sound like a real conversation." Now it's useful. 2. 👤 Nail the Who. Start by explaining who you are — your role, experience, anything relevant — and who you want the AI to think like when answering. Be specific. Example: "I'm a senior account manager at a midsized software company. I've been here six years, consistently hit my numbers, and just took on two new direct reports. I want you to think like a brutally honest executive coach who has helped hundreds of people negotiate compensation." 3. 🧩 Context matters most. Give detailed, real-world framing upfront. The AI doesn't know your situation, your audience, or what you're trying to avoid unless you tell it. Specificity is everything. Example (building on the Who😞 "My annual review is in two weeks. I haven't had a raise in 18 months despite a promotion in title. I know the company had a rough Q3, but my division exceeded targets. My boss is supportive, but not the final decision-maker — he has to pitch it to the VP. What's the smartest approach?" 4. 🚫 Just say no. Tell it what not to do. This sharpens output dramatically. Example (adding constraints): "Don't give me generic advice like 'know your worth.' Don't suggest ultimatums — I'm not bluffing. And don't make it sound like a script I'd read verbatim." 5. 🪜 Say: "Think step by step." When you're dealing with anything complex — a negotiation, a decision with trade-offs, a strategy with multiple variables — ask the AI to reason through it explicitly. This simple phrase dramatically improves output quality. Example: "Think step by step about how my boss will react and what objections he might raise when pitching this to the VP." 6. 👀 Just dump the image in. The models are extraordinary at instantly understanding screenshots, documents or files. Stop wasting time explaining what you're looking at — the AI can just see it. Example: Screenshot your company's salary bands from the internal HR portal. Paste it into ChatGPT alongside your title and tenure. Ask: "Based on this, where should I be? What's a reasonable ask?" ⚠️ Trust but verify. AI can hallucinate confidently — inventing facts, statistics, even citations that don't exist. The more specific the claim, the more you should double-check. Use it to think, draft and strategize. But if it spits out a number or a name, verify it before you repeat it. The bottom line: AI is a power tool. It rewards users who treat it like a sharp colleague rather than a magic box. Be specific. Be demanding. Keep pushing. 📱 How'd you do? How'd we do? What's your power prompt? Let us know: finishline@axios.com. Go deeper: Jim's video, "Blunt AI advice."

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Building AI brains

Illustration: Allie Carl/Axios

AI startups are raising billions to develop "brains" for robots that could work everywhere from oil rigs to construction sites, Axios Pro Rata author Dan Primack writes. Why it matters: Blue-collar workers may have as much to fear from AI disruption as white-collar workers. These software "brains" would understand physics and real-world conditions — helping the robots adapt to changing environments. Some of these AI-powered robots may be humanoids, others may not — form matters less than functionality. Plumbing, electrical, welding, roofing, fixing cars, making meals — there really isn't much of a limit. Think about it a bit like C-3PO and R2-D2, but without the snarky personalities. 🔬 Zoom in: There isn't yet agreement on the smartest way to apply AI to robotics. Big Tech giants and startups are gathering gobs of real-world data to train their AI models. Others employ "world models," which are trained on simulated physical world data. They're cheaper — relying on an understanding of things like gravity — and have been championed by Yann LeCun, the former chief AI scientist at Meta who recently formed a new company called AMI Labs. Follow the money: Toronto-based Waabi last week raised up to $1 billion in what could be the largest funding ever for a Canadian startup, with an initial focus on robotaxis and self-driving trucks. Pittsburgh-based Skild AI just raised $1.4 billion at a $14 billion valuation. Its motto: "Any robot. Any task. One brain." FieldAI last month raised nearly $400 million to focus on "dirty, dull, or dangerous" industries like energy and logistics. Its software could help robots build data centers — AI enabling AI, leaving humans on the sidelines. 🥊 Reality check: It's impossible to know how many blue-collar jobs could be rendered irrelevant, or over what time frame, as AI expands from the virtual to the physical. Even if an AI-powered robot can outperform a human, the added hardware and switching costs may outweigh the added efficiency. At least for now.

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🤠 AI's first rodeo

Image: TWG AI/Teton Ridge/Palantir AI is moving into rodeo arenas and bringing analytics to one of America's most tradition-bound sports, Axios' Russell Contreras writes. Why it matters: Rodeo has long defined itself as the last major American sport untouched by analytics. If AI takes hold in training and broadcasting, it won't just change how riders compete but redefine the cowboy's identity. Cowboys are one of America's most enduring symbols of independence and tradition. Their embrace of AI could serve as a bridge between high-tech innovation and communities that often see it as threatening. 🐎 Zoom in: Palantir, TWG AI, and Nvidia announced last month they are teaming up with Texas-based Teton Ridge to bring real-time AI and computer vision into rodeo arenas. Keep reading.

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🏎️ The other AI race

Illustration: Brendan Lynch/Axios Anthropic has signed a multiyear deal with racing's Atlassian Williams F1 Team, Axios' Eleanor Hawkins reports. 🧠 Anthropic's Claude will be the team's "Official Thinking Partner." The team's cars will get new Anthropic branding. 🌎 Lots of AI companies are trying to tap into F1's huge global fandom. Oracle has teamed up with Red Bull Racing since 2021. Google is the official partner of McLaren's F1 team. IBM locked in a partnership with Scuderia Ferrari, and Perplexity signed driver Lewis Hamilton as a brand ambassador. Microsoft recently announced a multiyear deal with Mercedes-AMG Petronas F1 Team. Go deeper.

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AI's software disruption is here

Illustration: Brendan Lynch/Axios

Software stocks are getting dumped as investors price in a world where AI could replace software services, with the selloff dragging down the broader market yesterday. Why it matters: The wipeout shows how the market can respond when facing fresh evidence that AI could replace an entire industry, Axios Markets' Madison Mills reports. 📉 Software stocks slid after Anthropic rolled out new AI automation capabilities for several different sectors of enterprises. Selling started in legal software/data-adjacent names, including Experian, the London Stock Exchange Group, Thomson Reuters and LegalZoom, then broadened across the sector. The iShares Expanded Tech-Software Sector ETF (IGV) is down more than 14% over the past six sessions, following a 15% drop in January (its worst month since 2008). Software sentiment is the "worst ever," investment firm Jefferies says in a blunt note. The category is "radioactive," Anurag Rana of Bloomberg Intelligence tells Axios. 🦾 The backstory: Anthropic sees itself as a complement rather than as a competitor to software providers. Anthropic can securely connect with other tools and applications, becoming your "home page" of sorts while software services run through the back end. Claude can "render interfaces directly within it," potentially driving "even more engagement and interactivity … with all these other business systems," Scott White, head of product for enterprise at Anthropic, tells Axios. Reality check: It's not the first time Wall Street has turned sour on software. Mobile was once expected to threaten Microsoft's software business, since everyone was going to be spending time on phones, not desktops. Microsoft's stock is up 789% over the last decade. 🤖 Nvidia CEO Jensen Huang, speaking in San Francisco at an AI conference hosted by Cisco, called the idea of AI replacing software "the most illogical thing in the world." "If you were a robot," Huang said, "would you use tools or reinvent tools? The answer, obviously, is to use tools ... That's why the latest breakthroughs in AI are about tool use."

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• 💻 OpenAI today released a new enterprise platform, Frontier, designed to let large companies build, deploy and manage fleets of AI agents that plug into their existing systems. Go deeper.

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Real or AI? 7 Clues to Spot Fake Images Right Away

AI-generated images are getting scarily realistic, but there are still clear signs to help you spot the fakes.

https://www.pcmag.com/explainers/real-or-ai-7-clues-to-spot-fake-images-right-away?

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⚖️ Legal world enters AI era

Illustration: Brendan Lynch/Axios

AI promises to make lawyers more productive, but there's a problem: Their clients are using it, too, Axios' Emily Peck writes. Why it matters: AI is creating new headaches for attorneys. They're worried about the fate of the billable hour — a reliable profit center for eons — and are perturbed by clients getting bad legal advice from chatbots. Dave Jochnowitz, a partner at the law firm Outten & Golden, says it's "like the WebMD effect on steroids," referring to how medical websites can give people a misguided impression. "ChatGPT is telling them: 'You got a killer case,'" Jochnowitz said. But the models don't always understand the full context, applicable laws or case history. 👓 Between the lines: The potential impact of AI on the industry was evident when shares of legal software companies, like LegalZoom and Thomson Reuters, fell sharply after Anthropic released a legal plug-in.

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🔌 AI fuels massive power demand surge

Data: International Energy Agency. ("Other" includes cooling, heat pumps and other building needs.) Chart: Kavya Beheraj/Axios Data centers are slated to account for 50% or so of U.S. power-demand growth for the rest of the decade, Axios' Ben Geman reports from a new International Energy Agency analysis. The AI-driven rise of huge data centers is a big reason IEA sees overall U.S. demand rising 2% annually on average from 2026–30. That's twice the pace from 2016–25. Keep reading ...