An artificial intelligence-enhanced setup will streamline Meta Pixel, while Conversions API gets a one-click option.
Bitcoin rallied to $76,000 on Tuesday as a bullish chart breakout and increasing onchain activity hint at an extended rally to $90,000.
World Liberty Financial allegedly used illiquid tokens to borrow $75 million, fueling bad debt fears and rattling confidence among traders.
One investor who has backed both companies told the FT that justifying OpenAI’s recent round required assuming an IPO valuation of $1.2 trillion or more — making Anthropic’s current $380 billion valuation look like the relative bargain.
Read more Fundraising is reportedly flowing for Fluidstack after it secured a $50 billion deal to build data centers for Anthropic.
Read more Dozens of WordPress plug-ins were allegedly hijacked to push malware after they were sold to a new corporate owner.
Read more In an interview at the Semafor World Economy summit this week, Anthropic co-founder Jack Clark explained why the company was still engaged with the U.S. government while simultaneously suing them.
Read more Waymo’s commercial service will eventually follow testing if the U.K. government approves.
Read more Software engineering has experienced two seismic shifts this century. First was the rise of the open source movement, which gradually made code accessible to developers and engineers everywhere. Second, the adoption of development operations (DevOps) and agile methodologies took software from siloed to collaborative development and from batch to continuous delivery. Now, a third such shift looks to be taking shape with the adoption of agentic AI in software engineering.
Thus far, engineering teams have mainly used AI to assist with coding, testing, and other individual tasks, within tightly designed parameters. But with agentic capabilities, AI agents become reasoning, self-directing entities that can manage not just discrete tasks but entire software projects—and do so largely autonomously. If adopted and fully embraced by engineering teams, agentic AI will usher in end-to-end software process automation and, ultimately, agent-managed development and product lifecycle automation.
This report, which is based on a survey of 300 engineering and technology executives, finds that software engineering teams are seeing the potential in agentic AI and are beginning to put it to use, but so far in a mainly limited fashion. Their ambitions for it are high, but most realize it will take time and effort to reduce the barriers to its full diffusion in software operations. As with DevOps and agile, reaping the full benefits of agentic AI in engineering will require sometimes difficult organizational and process change to accompany technology adoption. But the gains to be won in speed, efficiency, and quality promise to make any such pain well worthwhile.
Key findings include the following:
Adoption momentum is building. While half of organizations deem agentic AI a top investment priority for software engineering today, it will be a leading investment for over four-fifths in two years. That spending is driving accelerated adoption. Agentic AI is in (mostly limited) use by 51% of software teams today, and 45% have plans to adopt it within the next 12 months.
Early gains will be incremental. It will take time for software teams’ investments in agentic AI to start bearing fruit. Over the next two years, most expect the improvements from agent use to be slight (14%) or at best moderate (52%). But around one-third (32%) have higher expectations, and 9% think the improvements will be game changing.
Agents will accelerate time-to-market. The chief gains from agentic AI use over that two-year time frame will come from greater speed. Nearly all respondents (98%) expect their teams’ delivery of software projects from pilot to production to accelerate, with the anticipated increase in speed averaging 37% across the group.
The goal for most is full agentic lifecycle management. Teams’ ambitions for scaling agentic AI are high. Most aim for AI agents to be managing the product development and software development lifecycles (PDLC and SDLC) end to end relatively quickly. At 41% of organizations, teams aim to achieve this for most or all products in 18 months. That figure will rise to 72% two years from now, if expectations are met.
Compute costs and integration pose key early challenges. For all survey respondents—but especially in early-adopter verticals such as media and entertainment and technology hardware—integrating agents with existing applications and the cost of computing resources are the main challenges they face with agentic AI in software engineering. The experts we interviewed, meanwhile, emphasize the bigger change management difficulties teams will face in changing workflows.
This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff. It was researched, designed, and written by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.
Want to understand the current state of AI? Check out these charts.
If you’re following AI news, you’re probably getting whiplash. AI is a gold rush. AI is a bubble. AI is taking your job. AI can’t even read a clock. Stanford’s 2026 AI Index—the field’s annual report card—cuts through the noise.
The data reveals a technology evolving faster than we can manage. From the China-US rivalry and model breakthroughs to public sentiment and the impact on jobs, here are the index’s key findings on the state of AI today.
—Michelle Kim
Why opinion on AI is so divided
Stanford’s 2026 AI Index is full of striking stats. It also reveals a field riddled with inconsistencies, most notably in the gap between experts and non-experts.
On jobs, 73% of US experts view AI’s impact positively, compared to just 23% of the public. Similar divides emerged on the economy and healthcare. What’s driving this disconnect?
Part of the answer may lie in their diverging experiences. Those using AI for coding and technical work see it at its best, while everyone else gets a more mixed bag. The result is two very different realities. Read the full story on what they are—and why they matter.
This story is from The Algorithm, our weekly newsletter on AI. Sign up to receive it in your inbox every Monday.
—Will Douglas Heaven
Job titles of the future: Wildlife first responder
Grizzly bears have made such a comeback across eastern Montana that in 2017, the state hired its first-ever prairie-based grizzly manager: wildlife biologist Wesley Sarmento.
For seven years, Sarmento worked to keep both bears and humans out of trouble. He acted like a first responder, trying to defuse potentially dangerous situations. He even got caught in some himself, which led him to a new wildlife safety tool: drones. Find out the results of his experiments in digital ecology.
—Emily Senkosky
This article is from the next issue of our print magazine, which is all about nature. Subscribe now to read it when it lands on Wednesday, April 22.
The must-reads
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 Human scientists still trounce the top AI agents at complex tasks
The best agents perform only half as well as experts with PhDs. (Nature)
+ Can AI really help us discover new materials? (MIT Technology Review)
2 OpenAI is escalating its fight with Anthropic while pulling away from Microsoft
A leaked memo exposes plans to attack Anthropic. (Axios)
+ And says Microsoft “limited our ability” to reach clients. (The Information $)
+ While touting a budding alliance with Amazon. (CNBC)
3 Carbon removal technology is stalling—and that may be good news
Better solutions could now emerge. (New Scientist)
+ Here are three that are set to break through. (MIT Technology Review)
4 AI is finding bugs faster than we can fix them—and hackers will benefit
Welcome to the bug armageddon. (WSJ $)
+ AI may soon be capable of fully automated attacks. (MIT Technology Review)
5 A Texas man has been charged with the attempted murder of Sam Altman
He allegedly threw a Molotov cocktail at the OpenAI CEO’s home last Friday. (NPR)
+ The suspect reportedly had a list of other AI leaders. (NYT $)
6 AI is beginning to transform mathematics
It’s proving new results at a rapid pace. (Quanta)
+ One AI startup plans to unearth new mathematical patterns. (MIT Technology Review)
7 Students are turning away from computer science
It’s had a massive drop in enrollments. (WP $)
+ AI coding tools have diminished the degree’s value. (NYT $)
8 India’s bid to become a data center hub is sparking a fierce backlash
Farmers are protesting Delhi’s courtship of hyperscalers. (Rest of World)
9 Meta is set to overtake Google in advertising revenue this year
And become the world’s largest digital ad platform for the first time. (WSJ)
10 AI influencers are taking over Coachella
Synthetic content creators are “everywhere” at the festival. (The Verge)
Quote of the day
“These people are almost nothing like you. They are most likely sociopathic/psychopathic and, in the case of Altman, consistently reported to be a pathological liar.”
—The alleged firebomber of Sam Altman’s home shares his distrust of AI leaders in a blog post.
One More Thing
FRANCESCO FRANCAVILLA
We’ve never understood how hunger works. That might be about to change.
A few years ago, Brad Lowell, a Harvard University neuroscientist, figured out how to crank the food drive to the maximum. He did it by stimulating neurons in mice. Now, he’s following known parts of the neural hunger circuits into uncharted parts of the brain.
The work could have important implications for public health. More than 1.9 billion adults worldwide are overweight, and more than 650 million are obese. Understanding the circuits involved could shed new light on why these numbers are skyrocketing.
—Adam Piore
We can still have nice things
A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line.)
Top image credit: Stephanie Arnett/MIT Technology Review | Getty Images
+ Someone built a mechanical version of Tony Hawk’s Pro Skater from Lego.
+ Enjoy this wholesome clip of toddlers discovering the existence of hugs.
+ This interactive body map shows exactly which exercises you need.
+ Jon McCormack’s photos of nature’s patterns are breathtaking.