Joe Jenkins
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ZDNET’s key takeaways
- AI Dev, DeepLearning.ai’s AI conference, made its NYC debut.
- We sat down with Andrew Ng at the event to talk AI and developers.
- Ng recommends that everyone learn to code.
The second annual AI Dev, a summit on all things AI and software hosted by Andrew Ng’s DeepLearning.ai, came to New York on Friday. In several panels and an interview with ZDNET, the Google Brain founder had advice to give about the future of the field.
AI has rapidly become a reliable coding assistant for many developers — so much so that many are wondering about the future of the entire profession. Entry-level coding jobs are dwindling for recent grads as teams offload junior tasks to AI assistants; at the same time, experts cite the real limitations of these tools as proof that engineers will never actually become obsolete.
Also: Why AI coding tools like Cursor and Replit are doomed – and what comes next
Here’s what Ng had to say about how to navigate this uncertain future, why everyone should learn to code, and how governance should really be done.
Coding still matters – sort of
“Because AI coding has lowered the bar to entry so much, I hope we can encourage everyone to learn to code — not just software engineers,” Ng said during his keynote.
How AI will impact jobs and the future of work is still unfolding. Regardless, Ng told ZDNET in an interview that he thinks everyone should know the basics of how to use AI to code, equivalent to knowing “a little bit of math,” — still a hard skill, but applied more generally to many careers for whatever you may need.
“One of the most important skills of the future is the ability to tell a computer exactly what you want it to do for you,” he said, noting that everyone should know enough to speak a computer’s language, without needing to write code yourself. “Syntax, the arcane incantations we use, that’s less important.”
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He added that he wants to welcome vibecoders in as community members, even if they aren’t technically developers themselves. But he doesn’t expect it to be easy, either. Despite noting that “it’s really obvious that code should be written with AI assistants,” Ng admitted that vibecoding — which he prefers to call “AI coding” — leaves him “mentally exhausted.”
Becoming generalists
In his keynote, Ng noted that because AI has made software development so fast, product management — not prototyping — is the new slowing point for launching new products. To maintain the pace AI makes possible, he recommended that engineers learn some product management skills to circumvent that stall.
“Engineers that learn some product work can frankly be a team of one,” he said.
Also: What Bill Gates really said about AI replacing coding jobs
That theme of all professionals — not just developers — becoming generalists recurred throughout the summit. During a panel on development in the AI age, Fabian Hedin, CTO at coding platform Lovable — one of the underdog startups on a16z’s recent list — noted that vibecoding can enable people with deep knowledge in a non-software topic to “iterate a lot faster than before” using coding skills. Moderator Laurence Moroney, director of AI at Arm, said that this can make the most of an otherwise siloed expert, a shift in how niche skills function in the workplace.
The new challenge for developers, Ng said during the panel, will be coming up with the concept of what they want. Hedin agreed, adding that if AI is doing the coding in the future, developers should focus on their intuition when building a product or tool.
“The thing that AI will be worst at is understanding humans,” he said.
Why CS degrees aren’t serving students
The realities of coding in the AI age have started to hit post-grads struggling to find jobs. Computer science, once thought of as a foolproof major that guaranteed a lucrative career, is letting students down, Ng told ZDNET.
He cited the overhiring sprees tech companies went on — and then ultimately reversed — during the COVID-19 pandemic as the primary reason entry-level coding jobs are hard to come by. Beyond that, though, it’s a question of grads having the right kind of coding skills.
“AI has transformed how code should be written, but candidly, many universities have been slow to adapt the curriculum,” he said. “So if a university has not significantly changed its curricula since 2022, then they are not readying grads for the jobs of the market today.”
Also: AI will cause ‘jobs chaos’ within the next few years, says Gartner – what that means
Ng said he considers it “malpractice” for universities to grant CS degrees without teaching those students how to optimize working with AI assistants.
“I actually feel bad that there’s still people today receiving a bachelor’s degree in computer science that have not made a single API call to a single AI model,” he said. For him, reorienting CS degrees around that reality will bridge the gap between underprepared grads and a need for AI-experienced coders. “For the fresh college grads that do know those skills, we can’t find enough of them,” Ng said, a concern he also noted earlier this fall in an X post.
Public fear of AI
In his keynote, Ng recognized that “AI has not yet won America’s hearts and minds,” referring to the often-circulated public perception of what AI could become in its worst-case scenario. Several panelists called on the hundreds of developers in the audience to shift that perception.
Joe Jenkins
“You have this unique insight into what AI is not,” said Miriam Vogel, president and CEO of Equal AI. She urged developers not to ignore people’s fears about the tech, but to actively participate in AI literacy, adding that “we will fail” if that sentiment doesn’t improve.
Ng thinks third parties have intentionally sown AI fear thus far.
“I think a lot of fear of AI was driven by a handful of businesses that ran almost, frankly, PR campaigns to get people to be fearful of AI, often for lobbying,” he told ZDNET during our interview. “I think that’s done a lot of damage to the field of AI and to American leadership for developers.”
When asked how developers can impact that, he said he wants them to engage in candid conversation about what’s working and what isn’t. “If the public understands it better, then we can all arrive at more rational conclusions about technology,” he said.
Many of those fears stem from AGI, the somewhat ill-defined equivalent of human-level intelligence that OpenAI and Microsoft, among other labs, have set their sights on with increasing intensity. Ng has long maintained that those projections are overblown.
“If you look at the incredibly messy training recipes that go into training these AI models, there’s no way this is AGI — if, by AGI, you mean any intellectual task that a human does,” Ng told ZDNET. “So much of that knowledge is still, frankly, engineered into these systems, with very clever people, with a lot of data.”
Safety and governance
In a panel conversation, Ng acknowledged that the public doesn’t really know what AI labs are doing, which can create panic, but urged people not to “take a red teaming exercise and turn it into a media sensation.” Ng added that he’s less in favor of Anthropic’s brand of safety and governance, which he finds somewhat limiting. Rather than bearing down on governance efforts, he emphasized sandboxed environments “that are guaranteed safe” as a path toward responsible AI that doesn’t hamper speed.
Vogel defined governance as “breaking down principles into actionable workflows,” not creating bureaucracy. Her concern was less about the hyperscalers like OpenAI and Meta, and more about the smaller AI companies that blaze ahead before they’ve developed any governance structure.
Regulating AI
“You don’t get to lead in AI by passing regulations,” Ng said during a panel, speaking on the EU’s approach to legislating AI. He credited the Trump administration’s AI Action Plan, released this past summer, for keeping federal regulations loose.
Many AI experts are alarmed at the lack of US AI regulation. Some see the federal government’s failure to regulate social media platforms when they proliferated as an example of what could happen if AI continues to outpace legislation. Ng told ZDNET he thinks that’s a false equivalency.
Also: 8 ways to make responsible AI part of your company’s DNA
“I’m seeing way more bad regulatory proposals than good ones,” Ng said in the interview, adding that he sees the nonconsensual deepfake ban and the FTC’s actions against companies using AI to scale “deceptive or unfair conduct” as examples of good AI policy.
When asked if there are any other regulations he’d make at the federal level, he said he wants more transparency requirements for large AI companies off the bat.
“When a lot of bad things happened with social media, none of us knew about it. Even people inside the business did not really know about it,” Ng told ZDNET. “If we have regulations to require that the largest companies — only the large ones, so we don’t put unreasonable compliance burdens of small startups — but if we demand some level of transparency from the businesses with a very large number of users, that could give us better signals to spot the actual problems, rather than count on the luck of there being a whistleblower.”
