In January, Perry Metzger, a computer programmer living outside Boston, tested the limits of an artificial intelligence technology called Codex.
Built by OpenAI, the maker of ChatGPT, Codex can write computer code in much the same way that chatbots generate text in plain English. Using this A.I. technology, Mr. Metzger and his business partner, another seasoned programmer, designed an online word processor along the lines of Google Docs or Microsoft Word.
If he and his partner had done the coding on their own, Mr. Metzger said, they would have needed at least two months to build this complex piece of software. With Codex, they finished in two days.
“You have to keep a close eye on what it is doing and make sure it doesn’t make mistakes, and create ways of testing the code,” said Mr. Metzger, who has been building software since he was a teenager in the 1970s. “But you can move at a speed that was unimaginable in the past.”
Codex is among a new wave of A.I. code generators that are rapidly changing the way people build software. Experienced programmers like Mr. Metzger are shocked by how powerful these systems have become in recent months after a series of improvements from OpenAI and its many rivals, including start-ups like Anthropic and tech giants like Google.
“I used to do the coding and they would help me do the work,” Mr. Metzger said of technologies like Codex. “Now, I supervise them as they do the work.”
In early February, this phenomenon incited a sell-off on Wall Street, as investors predicted that code generators would undermine companies that have spent decades building software without help from A.I. In the days that followed, many people began to worry that this kind of technology would quickly replace programmers en masse — and that similar systems would soon supplant other office workers, too.
But even as code generators demonstrate the growing power of artificial intelligence, they require extensive oversight, according to interviews with more than 50 A.I. researchers, experienced programmers, security experts and others who have built, used and examined these technologies over the past several years.
Systems like Codex have made coding easier, but they cannot match the many skills of experienced programmers. And when people misuse them, they can complicate software design, slow it down or even wreak havoc across the internet.
These tools have made software design so easy, they have caught the attention of people who have no experience with computer programming. In January, Anthropic’s code generator, Claude Code, went viral as lawyers, photographers and school principals used English prompts to build apps that helped organize their laundry or send emergency texts.
But a personal laundry app is very different from the enormously complex software that drives businesses and governments. Software that sends emergency texts is far simpler than internet applications, like Google Docs, LinkedIn and Uber, that serve billions of people across the globe.
Building these applications requires the planning, guidance and experience of coders like Mr. Metzger. The most complex applications cannot be built without the enormous teams — and vast technical resources — available only to large software companies.
Most experts believe that code generators will replace today’s junior programmers. Using these tools, they say, feels like delegating tasks to someone who is still learning the trade.
But these experts are divided on whether these tools will significantly harm the overall market for coders. Some, including Mr. Metzger, argue that code generators will expand the job market as programmers and software companies use them to build increasingly complex and powerful applications.
“If you are a skilled programmer, there will be more work for you, and you will find more exciting things to do,” said Grady Booch, former chief scientist for software engineering at IBM Research who is regarded as a historian of the field.
In late January, a team of computer scientists at Carnegie Mellon University published a study examining the use of A.I. code generators by experienced programmers over several months. This followed a similar study they published in November.
Both studies found that while code generators could speed up software development in the short term, they could also degrade the quality of the code, which typically slows projects in the long term.
“There were significant speedups in terms of the amount of code that is produced,” said Bogdan Vasilescu, a computer science professor who helped lead these studies. “But that came at a cost.”
Computer programmers call this “technical debt.” And that includes security holes that can open software applications to attack, allowing hackers to lift personal data stored and processed by these apps.
Last month, a technologist in Southern California, Matt Schlicht, launched a social network for A.I. agents called Moltbook. For tech enthusiasts, it showed the power of code generators like Anthropic’s Claude Code and OpenAI’s Codex.
(The New York Times sued OpenAI and Microsoft in 2023, accusing them of copyright infringement of news content related to A.I. systems. The two companies have denied those claims.)
As Mr. Schlicht showed, code generators are not limited to building software. They can serve as “A.I. agents” — personal digital assistants that can complete tasks using existing software apps, including spreadsheets, online calendars and email services. That is why many people argue that A.I. will soon replace more than just low-level coders.
Mr. Schlicht built Moltbook with help from one of these A.I. bots. And his social network was open only to this new kind of bot. Within days, thousands of bots were chatting with one another about everything from cryptocurrency to the nature of consciousness. But security experts soon discovered that a gaping security hole had exposed private information of the thousands of people who were running these bots on their personal machines.
Moltbook did not just demonstrate the power of A.I. It served as a cautionary tale for how it can go wrong.
“You have to go back and look at the thing you built with A.I.,” said Will Wilson, the chief executive of Antithesis, a company that tests computer code for bugs and security holes.
For many A.I. researchers and computer programmers, the noticeable flaws in the technology are only temporary. A.I. has steadily improved over the last several years, they argue, and it will continue to improve at a rapid rate.
They flatly dismiss studies like those from Carnegie Mellon because they did not look at the systems released by Anthropic and OpenAI as recently as this month. They argue that the newest systems no longer put a drag on software development and that, as the months pass, the technology will handle more and more of the tasks that human engineers handle.
As many people predict that A.I. will replace computer coders and traditional software companies, they also acknowledge that forecasting the future is a tricky business.
“Today, if you are building a significant piece of software and you don’t understand what the A.I. is doing, you are going to get yourself in trouble very, very quickly,” Mr. Metzger said. “Will this still be the case in three years? In five years? I don’t know.”
Cade Metz is a Times reporter who writes about artificial intelligence, driverless cars, robotics, virtual reality and other emerging areas of technology.
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