PRODUCTS

AI coding tools rake in funding

AI coding companies had a good week. 

Sweden-based Lovable, a startup that offers vibe-coding, is reportedly raising funds at a $6 billion valuation, Forbes reported on Friday. The funds would follow a $1.8 billion valuation it secured after its $200 million Series A in July.  

The news comes on the heels of AI coding firm Cursor announcing a $2.3 billion funding round, which has skyrocketed its valuation to $29.3 billion, more than 12 times its January valuation. 

The popularity of these platforms extends beyond investor attention. 

• Lovable has seen rapid growth in recent months, reaching $100 million in subscription sales since its launch in November. CEO Anton Osika said last week that it is nearing 8 million users and that 100,000 new products are built daily on the platform. 

• As for Cursor, the company said it surpassed $1 billion in revenue and has drawn in more than one million users. 

These tools are popular for a simple reason: They make engineers work faster, Thomas Randall, research Director at Info-Tech Research Group, told The Deep View. 

“These tools reduce cognitive load by integrating code generation, debugging, and refactoring into familiar environments like VS Code,” he said. “These tools succeed because they translate AI model advances into immediate, tangible workflow benefits for developers.” 

And despite their popularity, the market is far from saturated, he said. Because these tools are making coding more accessible to non-software engineers, such as data scientists, IT professionals and low-code “citizen developers,” these companies are actively increasing their total addressable market just by the nature of their products. 

But it might not remain that way forever, he noted. In the medium-term, these platforms may be forced to differentiate themselves to stand out with things like enterprise software integrations or compliance frameworks, he said. And in the long-term, sustainable profitability may require these companies to stop leaning on external model providers – especially as those companies push their own AI coding offerings.

While these tools can supercharge a good software engineer and remove a barrier to entry for a novice, they’re also creating an existential crisis for young techies. A Stanford University study published in late August found that employment for software developers ages 22 to 25 is down nearly 20% from its peak in late 2022. A July study from Microsoft detailing the top 40 occupations most exposed to generative AI included data scientists and web developers on the list. 

However, whether these models are good enough to replace their human counterparts is still up for debate. While these tools can rapidly spit out lines of code, they, like all AI models, still hallucinate and make mistakes. With fewer human eyes, it may be easier for bugs to slip through the cracks.

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ENTERPRISE

CIOs buy into agentic AI

AI agents might finally be breaking out of the pilot phase. 

Full AI implementation is up year over year, from 11% to 42%, according to a survey of 200 CIOs from Salesforce released today. Budgets dedicated to AI have nearly doubled, and 61% of CIOs reported feeling ahead of competitors on their deployments. 

And amid the hype of automation, agents are the industry’s It Girl, with CIOs earmarking 30% of their budget to agentic AI alone. Around 96% of CIOs reported that they are currently using or plan to use agentic AI in the next two years. 

As agentic AI comes to the fore, it’s caused a shift in the kinds of work that actual humans are doing. 

• 94% of CIOs say AI agent adoption will require  them to expand their skillsets, focusing on soft skills instead of technical duties. 

• Around 61% reported a desire to improve leadership skills, 57% reported improving storytelling skills, and 55% reported improving change management and communication. 

But despite shifting priorities and increased momentum, there are still bumps in the road: While 81% acknowledge that this kind of adoption requires collaboration between teams, less than half are actually doing this. 

And as investments in these deployments increase and companies become eager for returns, getting employees to trust, use and continuously integrate this tech is crucial: 93% reported that successful deployments hinge on integrations into “everyday work.” 

“A huge part of my job has become about enabling employees and having them understand that AI can complement the work they do, and isn’t here to just replace them,” said Daniel Schmitt, CIO of Salesforce, in a call with reporters.

The other major concern is data. While organizations have come a long way in cleaning up their data, trust still remains a major bottleneck in deployment. Only 23% of CIOs reported that they are confident they are investing in AI with built-in data governance.

“Having a clean dataset is absolutely key,” said Schmitt. “You have to be able to trust the data that AI is using. AI is not magic, it uses the same data that humans use.”

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CYBERSECURITY

Hackers, enterprises go head-to-head with AI

AI-powered cyberattacks are getting stronger. 

On Thursday, Anthropic said it disrupted the first reported AI-orchestrated cyber espionage campaign, involving agentic capabilities that go beyond just advising on attacks, to executing them autonomously. 

Anthropic claims “with high confidence” that the threat actor was a Chinese state-sponsored group that manipulated Claude Code to attempt to infiltrate thirty global targets. The targets include large tech companies, financial institutions, chemical manufacturers and government agencies. Anthropic tracked the severity of the operations, banned associated accounts and notified authorities. 

“We’re continually working on new methods of investigating and detecting large-scale, distributed attacks like this one,” Anthropic said in the report. 

The incident is just one case exemplifying that hackers are getting far smarter at using AI. Data from Google’s Threat Intelligence Group published in early November showed a shift in hackers’ AI strategies, leaning towards AI-powered malware and models being abused across the attack lifecycle. While the potential for bad actors to leverage this tech was clear from the start, “the speed at which it materialized is unsettling,” Adam Arellano, Field CTO at Harness.io, told The Deep View. 

And larger, coordinated attacks may inspire others, Arellano said. “More and more of the smaller groups and even individuals will start to figure out how to use (LLMs) as well, increasing access to these types of attacks.” 

But that doesn’t mean that enterprises are empty-handed, Eric O'Neill, former FBI counterterrorism and counterintelligence operative and founder of The Georgetown Group and Nexasure AI, told The Deep View. 

Plenty of organizations are deploying AI for counterintelligence, anomaly detection, rapid incident response and resilience in data integrity, he said. But as hackers become more sophisticated at a rapid clip, speed, adaptability and resilience are “the only winning strategies.”

“The battle has escalated into something out of the 1980s film Tron: AI vs. AI, dueling across digital landscapes for control of the currency of our lives—data,” said O'Neill.

LINKS

• Mozilla is working on an AI “Window” assistant for Firefox

• Amazon, Microsoft back effort to restrict Nvidia chip sales in China

• Google will invest $40 billion in new data centers in Texas

• XAI delays Grok 5 release until the first quarter of 2026

• Meta to focus employee performance reviews on "AI-driven impact"

• US Jury says Apple must pay Masimo $634 million for blood-oxygen tech

• Group chats in ChatGPT: collaborate with others in one ChatGPT conversation, now in Japan, New Zealand, South Korea and Taiwan. 

• Arcten: Add AI agents to your products and tools without the hassle.  

• Lua: Build, deploy and scale AI agents across your organization, without high costs or consultants. 

• Lancey: An AI coding agent to scan your customer channels and build products people actually want, without human prompting.

• Selfin: Get AI-powered, personalized financial advice in an all-in-one platform.

• OpenAI: Lead Research Engineer/Scientist, Cyber

• Latham & Watkins: Senior Machine Learning Engineer

• Postman: Applied AI Scientist, Small Language Model and AI Training

• Google: Senior Research Scientist, Google Research

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