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AI agents are science fiction not yet ready for primetime

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AI agents are science fiction not yet ready for primetime

This is The Stepback, a weekly newsletter breaking down one essential story from the tech world. For more on all things AI, follow Hayden Field. The Stepback arrives in our subscribers’ inboxes at 8AM ET. Opt in for The Stepback here.

It all started with J.A.R.V.I.S. Yes, that J.A.R.V.I.S. The one from the Marvel movies.

Well, maybe it didn’t start with Iron Man’s AI assistant, but the fictional system definitely helped the concept of an AI agent along. Whenever I’ve interviewed AI industry folks about agentic AI, they often point to J.A.R.V.I.S. as an example of the ideal AI tool in many ways — one that knows what you need done before you even ask, can analyze and find insights in large swaths of data, and can offer strategic advice or run point on certain aspects of your business. People sometimes disagree on the exact definition of an AI agent, but at its core, it’s a step beyond chatbots in that it’s a system that can perform multistep, complex tasks on your behalf without constantly needing back-and-forth communication with you. It essentially makes its own to-do list of subtasks it needs to complete in order to get to your preferred end goal. That fantasy is closer to being a reality in many ways, but when it comes to actual usefulness for the everyday user, there are a lot of things that don’t work — and maybe will never work.

The term “AI agent” has been around for a long time, but it especially started trending in the tech industry in 2023. That was the year of the concept of AI agents; the term was on everyone’s lips as people tried to suss out the idea and how to make it a reality, but you didn’t see many successful use cases. The next year, 2024, was the year of deployment — people were really putting the code out into the field and seeing what it could do. (The answer, at the time, was… not much. And filled with a bunch of error messages.)

I can pinpoint the hype around AI agents becoming widespread to one specific announcement: In February 2024, Klarna, a fintech company, said that after one month, its AI assistant (powered by OpenAI’s tech) had successfully done the work of 700 full-time customer service agents and automated two-thirds of the company’s customer service chats. For months, those statistics came up in almost every AI industry conversation I had.

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The hype never died down, and in the following months, every Big Tech CEO seemed to harp on the term in every earnings call. Executives at Amazon, Meta, Google, Microsoft, and a whole host of other companies began to talk about their commitment to building useful and successful AI agents — and tried to put their money where their mouths are to make it happen.

The vision was that one day, an AI agent could do everything from book your travel to generate visuals for your business presentations. The ideal tool could even, say, find a good time and place to hang out with a bunch of your friends that works with all of your calendars, food preferences, and dietary restrictions — and then book the dinner reservation and create a calendar event for everyone.

Now let’s talk about the “AI coding” of it all: For years, AI coding has been carrying the agentic AI industry. If you asked anyone about real-life, successful, not-annoying use cases for AI agents happening right now and not conceptually in a not-too-distant future, they’d point to AI coding — and that was pretty much the only concrete thing they could point to. Many engineers use AI agents for coding, and they’re seen as objectively pretty good. Good enough, in fact, that at Microsoft and Google, up to 30 percent of the code is now being written by AI agents. And for startups like OpenAI and Anthropic, which burn through cash at high rates, one of their biggest revenue generators is AI coding tools for enterprise clients.

So until recently, AI coding has been the main real-life use case of AI agents, but obviously, that’s not pandering to the everyday consumer. The vision, remember, was always a jack-of-all-trades sort of AI agent for the “everyman.” And we’re not quite there yet — but in 2025, we’ve gotten closer than we’ve ever been before.

Last October, Anthropic kicked things off by introducing “Computer Use,” a tool that allowed Claude to use a computer like a human might — browsing, searching, accessing different platforms, and completing complex tasks on a user’s behalf. The general consensus was that the tool was a step forward for technology, but reviews said that in practice, it left a lot to be desired. Fast-forward to January 2025, and OpenAI released Operator, its version of the same thing, and billed it as a tool for filling out forms, ordering groceries, booking travel, and creating memes. Once again, in practice, many users agreed that the tool was buggy, slow, and not always efficient. But again, it was a significant step. The next month, OpenAI released Deep Research, an agentic AI tool that could compile long research reports on any topic for a user, and that spun things forward, too. Some people said the research reports were more impressive in length than content, but others were seriously impressed. And then in July, OpenAI combined Deep Research and Operator into one AI agent product: ChatGPT Agent. Was it better than most consumer-facing agentic AI tools that came before? Absolutely. Was it still tough to make work successfully in practice? Absolutely.

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So there’s a long way to go to reach that vision of an ideal AI agent, but at the same time, we’re technically closer than we’ve ever been before. That’s why tech companies are putting more and more money into agentic AI, by way of investing in additional compute, research and development, or talent. Google recently hired Windsurf’s CEO, cofounder, and some R&D team members, specifically to help Google push its AI agent projects forward. And companies like Anthropic and OpenAI are racing each other up the ladder, rung by rung, to introduce incremental features to put these agents in the hands of consumers. (Anthropic, for instance, just announced a Chrome extension for Claude that allows it to work in your browser.)

So really, what happens next is that we’ll see AI coding continue to improve (and, unfortunately, potentially replace the jobs of many entry-level software engineers). We’ll also see the consumer-facing agent products improve, likely slowly but surely. And we’ll see agents used increasingly for enterprise and government applications, especially since Anthropic, OpenAI, and xAI have all debuted government-specific AI platforms in recent months.

Overall, expect to see more false starts, starts and stops, and mergers and acquisitions as the AI agent competition picks up (and the hype bubble continues to balloon). One question we’ll all have to ask ourselves as the months go on: What do we actually want a conceptual “AI agent” to be able to do for us? Do we want them to replace just the logistics or also the more personal, human aspects of life (i.e., helping write a wedding toast or a note for a flower delivery)? And how good are they at helping with the logistics vs. the personal stuff? (Answer for that last one: not very good at the moment.)

  • Besides the astronomical environmental cost of AI — especially for large models, which are the ones powering AI agent efforts — there’s an elephant in the room. And that’s the idea that “smarter AI that can do anything for you” isn’t always good, especially when people want to use it to do… bad things. Things like creating chemical, biological, radiological, and nuclear (CBRN) weapons. Top AI companies say they’re increasingly worried about the risks of that. (Of course, they’re not worried enough to stop building.)
  • Let’s talk about the regulation of it all. A lot of people have fears about the implications of AI, but many aren’t fully aware of the potential dangers posed by uber-helpful, aiming-to-please AI agents in the hands of bad actors, both stateside and abroad (think: “vibe-hacking,” romance scams, and more). AI companies say they’re ahead of the risk with the voluntary safeguards they’ve implemented. But many others say this may be a case for an external gut-check.

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Valve is so behind on Steam Controller orders that some won’t ship until 2027

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Valve is so behind on Steam Controller orders that some won’t ship until 2027

Valve has some good news and bad news about Steam Controllers. The good news: if you make a reservation for a Steam Controller, the company will now show you one of three estimates of when you’ll be able to actually order your gamepad: by September 2026, by December 2026, or sometime in 2027. The bad news: any reservations made today “indicate a 2027 date for shipping,” Valve says.

“We have no plans to stop making Steam Controller,” according to Valve. “But as we look at the current demand compared to how many we know we can make by the end of the year, we want to manage expectations as much as we can with regards to when folks can expect to receive their order.”

Valve’s very good new Steam Controller went on sale in early May, and the initial rush led some people to run into frustrating problems with trying to check out ahead of the controllers eventually going out of stock. A few days later, the company announced that it would be implementing a reservations queue for interested buyers so they could get on a waitlist. If you’re on the waitlist, when you get notified that a Steam Controller is ready for you to buy, you have 72 hours to actually make the order.

“When we launched Steam Controller last month, we quickly saw that initial demand exceeded our expectations,” Valve says. “Switching to a reservation queue has (hopefully) cut down on the headaches on the customer side, and for us it’s also been helpful as we plan ahead and try to get as many out as quickly as we are able.”

All three of Valve’s big hardware products were delayed from a planned early 2026 launch because of the component crisis, Valve still hasn’t announced when the Steam Machine PC or Steam Frame VR headset might go on sale. However, just yesterday, Valve officially launched its big SteamOS 3.8 update with support for the Steam Machine. It’s also been importing a lot of hardware into the US as of late.

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McDonald’s AI drive-thru may take your next order

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McDonald’s AI drive-thru may take your next order

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The next time you pull up to a McDonald’s drive-thru, the voice taking your order may not be human. McDonald’s is testing a new AI-powered system called ArchIQ at five U.S. locations. The company has not said where those restaurants are located. The voice assistant, nicknamed Archy, can take drive-thru orders and has shown it can handle both English and Spanish.

For anyone who has repeated “no pickles” into a speaker box more than once, this could sound helpful. However, if you remember McDonald’s last AI drive-thru experiment, you may also wonder whether your burger order could somehow turn into a bag full of surprise McNuggets.

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WOULD YOU EAT AT A RESTAURANT RUN BY AI? 

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McDonald’s is testing an AI drive-thru system called ArchIQ at five U.S. restaurants. (Kurt “CyberGuy” Knutsson)

 

What is McDonald’s AI drive-thru?

ArchIQ is McDonald’s new AI system for restaurants. It can take drive-thru orders and also help with operations behind the scenes.

In a post on X, McFranchisee, an anonymous McDonald’s franchisee account, said the system is currently in five test stores and has processed more than one million transactions. The account also said about 90% of orders were completed without a human stepping in. That number sounds promising. Still, McDonald’s has not confirmed a nationwide launch date. For now, this remains a limited test.

The system also appears to connect with a bigger McDonald’s plan called “McDonald’s > NEXT.” CEO Chris Kempczinski described the strategy as a way to bring in more customers and improve restaurant productivity. The plan also includes menu changes, restaurant redesigns, technology upgrades and more focus on hospitality.

 

Why McDonald’s is testing AI ordering

Drive-thrus can get chaotic fast. Someone changes an order after the total appears. A child calls out from the back seat. Road noise makes the speaker hard to hear. Then the driver remembers the extra sauce after everything has already gone through. That is the type of pressure McDonald’s wants AI to handle.

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If ArchIQ works well, it could help restaurants move cars through the line faster. It may also reduce mistakes during busy hours. Workers could then focus more on preparing food, handling payments and helping customers who need a real person.

ArchIQ also appears to have a management role. In the same X post, McFranchisee described Archy as a tool that could alert managers to bottlenecks or other issues before they slow down operations. 

STARBUCKS USES CHATGPT TO SUGGEST DRINKS BASED ON MOOD AS EXPERT WARNS OF HIDDEN DOWNSIDES

The AI assistant, nicknamed Archy, can take drive-thru orders and may also help managers spot restaurant slowdowns. (McFranchisee)

 

McDonald’s tried AI drive-thru ordering before

This new test follows McDonald’s earlier AI drive-thru experiment with IBM. That program involved more than 100 restaurants. McDonald’s ended the test in 2024 after customers complained about order accuracy. Some mistakes also went viral, creating an embarrassing moment for McDonald’s and raising questions about whether the technology was ready for the drive-thru. Customers reported wrong items, strange quantities and other order mix-ups. That history is why this new test will get extra attention.

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This time, McDonald’s is working with Google technology. McFranchisee also claimed every McDonald’s in the U.S. is getting Google Edge Cloud hardware in anticipation of the rollout. McDonald’s seems to believe the newer system can perform better than the last one. The real test will come when regular customers use it during real drive-thru rushes.

 

How McDonald’s AI drive-thru could help customers

If McDonald’s gets this right, the most obvious benefit is speed. An AI ordering system does not get tired during a long shift. It may also help more customers order in the language they prefer. That could make a busy drive-thru feel less frustrating, especially during breakfast or late-night hours.

The system may also ask clearer follow-up questions and catch missing details before the order reaches the kitchen. That would be a win for customers who want to get in, get their food and get on with the day.

 

The biggest problem with AI drive-thru orders

The biggest concern is accuracy. AI can still misunderstand people. That gets frustrating fast when you are trying to grab lunch between errands or get your kids fed from the back seat. A wrong order wastes time. It also puts workers in the position of fixing a mistake the machine made.

There is also the customer service side. Some people like hearing a real person at the speaker. Others may find an AI voice cold or annoying, especially if the system gets confused.

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Then there is the privacy question. If an AI system takes your order, customers may wonder what gets collected, how long it is kept and who can access it. McDonald’s has not publicly explained those specifics for this current ArchIQ test.

ALEXA+ LETS YOU ORDER FOOD LIKE A REAL CONVERSATION

A drive-thru menu board stands outside a McDonald’s restaurant in Hercules, Calif., on Oct. 23, 2024, amid an E. coli outbreak linked to onions in Quarter Pounder sandwiches that has sickened dozens and killed one person across the U.S. (David Paul Morris/Bloomberg via Getty Images)

 

How to avoid AI drive-thru mistakes

Before you leave the drive-thru, take a moment to check the order screen. Make sure the items match what you said. Listen when the system repeats your order. Keep your receipt until you confirm the food is right.

Also, avoid sharing extra personal details at the speaker box. Your order should only require your food choices and payment.

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If the AI gets confused, ask for a crew member. You do not need to keep going back and forth with a machine over fries.

 

What this means for you

For now, you probably will not notice a change at your local McDonald’s. The ArchIQ test appears limited to five U.S. restaurants, and the company has not said when it could expand.

Still, this gives customers a preview of where fast food may be heading. AI could soon play a bigger role in how restaurants take orders and manage the kitchen. That may speed up the line, though it could also make the experience feel less personal.

 

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Kurt’s key takeaways

McDonald’s clearly wants AI to play a bigger role in its restaurants. From a business point of view, the idea makes sense. Shorter drive-thru lines could help franchisees and customers. Better restaurant data could also help managers fix problems faster. But I still want the human backup. Food orders can be messy because people are messy. We change our minds. We talk over each other. We forget the extra ketchup until the last second. AI may handle much of that one day. For now, I would treat it like any busy drive-thru interaction. Speak clearly. Check the order. Do not pull away until you know your food is right.

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Would you trust an AI voice to take your McDonald’s order, or do you still want a real person on the other end of the speaker? Let us know by writing to us at Cyberguy.com

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Midjourney goes from generating cat images to full-body ultrasound scans

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Midjourney goes from generating cat images to full-body ultrasound scans

Midjourney CEO David Holz just showed off the company’s first hardware product and plans to build a San Francisco spa, which he admitted is a bit different from the “cat pictures” produced by its AI image generator. Dubbed The Midjourney Scanner, it’s an ultrasound-based full-body scanner that uses a ring of sensors to capture vertical slices of the inside of your body, looking at the composition of your muscle, fat, bone, and organs to start. Holz said ideally, you could do this once a year or every single day, as it “aims for image quality comparable to MRI in many ways.”

He mentioned that one way he’d like to use it would be to see how his body changes in response to diet and workout changes, saying, “I’m not the most measured man on Earth yet, you know, but maybe I want to have that daily [measurable information].” A set of job listings advertises the company’s goal as trying to “build and launch the world’s first full-body ultrasound CT scanner, ultimately bringing safe, fast, and high fidelity preventative scanning to billions via a magical spa experience.”

The Midjourney Scanner was developed in a partnership with ultrasound tech company Butterfly Network, which said it uses “40 Butterfly Ultrasound-on-Chip imaging modules per system.”

The scanning process starts with stepping onto a platform that drops down into the water on rails through a ring of thousands of transducers that create ultrasonic waves. It then records the ripples passing through your body to analyze them and create detailed 3D images. The scan takes about 60 seconds. Holz said about a dozen people have been scanned so far.

It starts by stepping into a shallow pool of golden light. You then begin to descend into the water. Your body passes through a ring of underwater sensors, each acting like a dolphin, using its echolocation. The sensors send ultrasonic sound waves through your body from every angle. With enough waves, and enough angles, we form an image of what’s happening inside your body.

It combines those sensors with two petaflops of processing power. But after watching the livestreamed reveal, I’m still unclear on what Midjourney’s AI image generation tech exactly has to do with the Midjourney Medical effort, beyond an alternative business for otherwise-unused AI compute.

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Holz hopes to put 10 of the scanners into a Midjourney Spa location in San Francisco’s Union Square that will open before the end of 2027 and offered to scan the hands of attendees at its launch event. The Midjourney Spa will have a gym, saunas, and cold plunges to go along with the hot tub–equipped scanning rooms where visitors will get into the water to be scanned.

He did mention that various medical applications would require FDA clearances, but for now, Midjourney Medical says it’s working on “body composition maps” that don’t require the same level of clearance as diagnostic imaging. It also says the “library of scans” users create can be shared with doctors, AI health tools, or others, and that, “We take data privacy seriously — more details on our data policies will come as we get closer to launch.”

Holz suggested that eventually these scans could become better than an MRI, without radiation, powerful magnets, or other complicating factors, to get a look at what’s going on inside people’s bodies “real fast.” In response to a question, he imagined a future where the FDA had a class of devices to look at “weird” things and allowed people to “just try to get as much data as we can.”

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