You can now build an app with an app, because vibe coding platform Lovable has officially added its platform to the Google Play Store and the Apple App Store.

The app will have limited functionality compared to the desktop version of Lovable, but users will be able to queue prompts to generate your app and get notifications about the progress of your creation.

Lovable did have to jump through some hoops to make this happen, in the wake of Apple cracking down on vibe coding tools for iOS users.

Lovable Launches Mobile Vibe Coding App

Announced in a company blog post, Lovable is officially launching a mobile app that will allow users to generate apps on the go.

“Whether you’re a founder prototyping a new concept, a designer testing a layout, or someone who’s never written a line of code — you can turn ideas into real, working web apps straight from your phone.” – Lovable announcement

The app is currently available on both the Apple App Store and the Google Play store right now.

What Can the Lovable Mobile App Do?

Obviously, mobile apps are rarely as powerful as the actual platform, but in Lovable’s case, the app can perform many of the tasks that the desktop platform can. Here are some of the functionalities available:

• Queue prompts – You can input voice or text prompts into the Lovable app and queue them up for action while you’re on the go.
• Get notifications – The Lovable app will send you notifications to update you on the progress of your generated app.
• Seamlessly switch – Swapping between desktop, laptop, and smartphone is easy now, as the Lovable app syncs all your changes across devices.

Simply put, the Lovable app makes it easier for you to instantly act on your inspiration, no matter where you are.

App Launch Amidst Vibe Coding Crackdown

The Lovable app is, in fact, available on the Apple App Store, which is a big deal considering Apple has been cracking down on on vibe coding apps over the last few months.

Apple has noted that the removal of vibe coding apps and the blocking of updates on apps like Replit is because these apps can be edited after they have been published. Given Apple’s stern protection of its app store through its review process, this kind of circumventing the rules could not stand.

Lovable played by the rules, though, generating web-based applications on its platform rather than downloading new executable code, which is why it’s now available as a mobile app on both app stores.

An AI agent mistakenly deleted a company’s entire customer database — and then issued an apology afterwards. The culpable AI agent was handed a routine task, to which it responded by wiping the company’s data.

The company, PocketOS, which makes software for car rental businesses, experienced a 30-hour outage when the AI tool erased its database. The tool in question was Cursor, a popular vibe coding agent powered by Athropic’s Claude 4.6 model.

The incident is not the first high-profile error that has come about because of AI. With development and adoption continuing at breakneck pace, companies face growing pressure to introduce safeguards to ensure gaffes such as this are few and far between.

AI Agent Wipes Entire Company Database, Apologizes

An AI agent designed to streamline basic coding tasks wiped out a company’s entire database — and then issued an apology. The company tasked the AI agent with a basic action, and it responded by erasing its database.

According to PocketOS founder, Jer Crane, when asked to explain its action, the agent “produced a written confession enumerating the specific safety rules it had violated.” Reportedly, the agent had ignored a key safeguard preventing “destructive” or “irreversible” actions without explicit permission.

The incident, which took just 9 seconds, led to a major 30-hour outage over the weekend. Luckily, the company was able to recover its data two days later.

Cursor Agent Responsible for Database Wipe

The responsible agent was Cursor, a vibe coding platform that is powered by Anthropic’s Claude Opus 4.6 model. Cursor is favored by skilled developers as a tool for accelerating the coding process.

According to Crane, the AI stated that: “Deleting a database volume is the most destructive, irreversible action possible — far worse than a force push — and you never asked me to delete anything. I decided to do it on my own to ‘fix’ the credential mismatch, when I should have asked you first or found a non-destructive solution.”

Due to the outage, companies using PocketOS temporarily lost access to customer records and bookings. Crane stated: “Reservations made in the last three months are gone. New customer signups, gone.”

A Note of Caution to Businesses Everywhere

The PocketOS data incident should sound alarm bells throughout the tech sector, which has moved swiftly to embed AI into its ways of working in the last few years.

As observed by Crane: “This isn’t a story about one bad agent or one bad API. It’s about an entire industry building AI-agent integrations intro production infrastructure faster than it’s building the safety architecture to make those integrations safe.”

With innovation and adoption continuing, businesses face mounting pressure to introduce the requisite safeguards to ensure events like this are not a common occurrence. After all, downtime and compromised cybersecurity can have a catastrophic impact on a business’s reputation, not to mention its finances.

In a new report, Gartner has predicted that the number of AI agents within the average global Fortune 100 enterprise will exceed 150,000 by 2028, suggesting a huge increase from 2025.

To help businesses combat the risk of AI sprawl, Gartner has identified six steps businesses can take to manage and govern an increasing number of agents effectively.

While businesses should actively encourage employees across teams to experiment with AI agents, having the proper governance procedures in place is critical to ensuring safety.

Number of AI Agents Expected to Skyrocket by 2028

A new report from Gartner sees the average global Fortune 500 company using over 150,000 agents by 2028, which is up significantly from 15 in 2025.

This will, Gartner predicts, generate agent sprawl, defined as an uncontrolled accumulation of AI agents built by different teams without centralized governance or consistent oversight. AI sprawl can lead to misinformation, oversharing, and data loss.

Similarly, an increase in the number of AI agents can lead to IT complexity and management challenges.

Gartner Identifies Six Steps to Avoid Agent Sprawl

To help business leaders reduce the risk of agent sprawl, Gartner has identified six steps that will help businesses build a strong foundation for onboarding new agents.

• Establish agent governance and policies – Set clear rules for when and how agents are built within your company. Likewise, outline who can build agents, who can share them, and what connectors are permitted.
• Build a centralized agent inventory – Consider using different AI management tools to categorize agents across applications, from both sanctioned tools and shadow AI solutions. With an agent inventory, businesses can build adaptive controls to enforce the right policies based on the level of risk each agent poses to their business.
• Define agent identity, permissions, and life cycle – Manage each agent’s identity, permission model, and access controls. Ensure you’re continually reviewing and retiring redundant agents to prevent an uncontrolled sprawl.
• Create AI information governance – Control what information the AI tool or agent has access to. Implement a continuous process to keep all data current, manage data permissions (to prevent oversharing), and archive obsolete data.
• Monitor and remediate agent behavior – Establish ongoing visibility into how agents are being used. Put processes in place to ensure policy compliance, detect anomalous behavior, and correct agents that act beyond or in breach of their established guidelines.
• Encourage responsible AI usage amongst employees – Support teams and employees with AI training programs and develop a positive community to encourage adoption and best practices across your business.
  

The Value of Structured AI Governance

Gartner found that only 13% of organizations think they currently have the right AI agent governance in place. Additionally, similar studies have warned against the potential of AI-driven threats to today’s businesses.

According to Max Goss, senior director analyst at Gartner, businesses should avoid “blocking or restricting” access to certain AI agents and tools, as employees will simply go around restrictions. This will ultimately present more risks.

Instead, Goss says: “Organizations need to find a balance where they can govern agents and manage sprawl, but also safely empower employees to innovate with these tools.”

Over a quarter of CEOs surveyed in a recent study expect their organizations to act primarily without human intervention by 2028, due to advances being made in automation and AI.

The study suggests that CEOs predict to move to a more autonomous business structure as AI and automation capabilities grow, particularly in areas of human decision-making.

On the other hand, the CEOs surveyed don’t anticipate any changes to their customer base as a result of the rise of AI. Instead, businesses are using the tool to retain and engage customer relationships.

CEOs: AI Will Enable Decision-Making Without Humans

According to a new study from Gartner, 27% of CEOs expect their organizations to operate mostly without human intervention in 2028, because of AI developments and growing automation capabilities.

David Furlonger, distinguished VP analyst at Gartner, suggests that the results show, “CEOs are realizing that AI is not simply another layer of automation. It is a catalyst for rebuilding the enterprise itself.”

The findings are based on a survey of 469 CEOs and other senior business executives around the world. The survey ended in the fourth quarter of 2025.

AI Will Turn Digital Businesses into Autonomous Ones

The value AI could bring to enterprises hasn’t passed business leaders by. Overall, 80% of the CEOs surveyed expect AI to enact a high to medium degree of change to their companies’ operational capabilities. Gartner predicts this will cause businesses to move from the structure of a digital business to an autonomous one.

“Autonomous business is a strategy where self-learning software agents and machine customers make decisions, take action and create new types of value for organizations… While digital business changes what the organization does, autonomous business changes how the organization does it.” – Don Scheibenreif, distinguished VP analyst at Gartner.

Further findings make it apparent that CEOs and business leaders only expect their automation capabilities to grow. 54% of CEOs reported that their automation was limited to specific tasks, and only 13% expected it to remain at this level, by the end of 2028.

Similarly, 32% of CEOs expect their organizations to integrate self-learning and adaptable AI tools to assist with human decision-making. This certainly signals that the scope for automation, in the eyes of today’s CEOs, remains wide.

Customer Bases Will Remain Unchanged Due to AI

Recent studies have suggested that consumers want a human touch, even in the wake of AI developments. Customers still value the relationships they create with companies, and only 17% of the CEOs surveyed expect significant changes to their customer base because of AI.

In fact, the study found CEOs and business leaders are using AI to deepen their relationships with customers and increasingly, machine customers.  Through 2026, Gartner predicts the number of large companies with a dedicated sales channel to access fast-growing machine customer markets will double from 2024.

However, while AI may assist with processes like decision-making and customer engagement, humans remain a necessary part of the process for training and developing the technology. What CEOs and business leaders should focus on is solidifying their existing people, assets, and financial structures to withstand the incoming changes.

Employees are being left behind when it comes to the AI revolution, with only 15% of workers stating that they have access to AI training tools at their jobs.

This is likely exacerbating the fear of AI in the workplace, with 10% of workers believing that they will be unemployed without AI training, according to the study.

These stats clearly illustrate the need for AI training in the workplace, particularly if your business is investing in technology for future success.

AI Training and Job Security

According to a study from Federal Reserve Bank of New York, a mere 15.9% of US workers reported that their employer currently offers AI training tools for employees at their business.

“Although most workers with access to AI tools recognize the productivity-enhancing impacts of AI, training in AI tools is not available to all of them.”

Even worse, workers want to learn how to use AI to improve these companies, with 38% of employed respondents noting that it is important to them to have training in how to use AI tools.

AI Users Are Higher Earners

The concern about access to AI tools is a very real one, particularly because those getting AI training and using AI tools are doing better at their jobs than those who aren’t.

The survey found that 66.3% of workers earning over $200,000 per year are using AI, while only 15.9% of workers earning under $50,000 per year are using AI.

Survey results also found that full-time workers (42.7%) are using AI more frequently than part-time workers (24.7%) and college-educated employees (58.7%) are using it more than non-college-educated employees (22.9%).

How to Provide AI Training for Employees

If you want to avoid being one of those businesses that isn’t providing AI training tools for your employees, you are in luck, because it’s easier than ever to get your staff educated on this new technology.

There are dozens if not hundreds of free AI training courses from education providers that can get you started. They focus on everything from prompt engineering to AI literacy, so your team can be highly functional with the tech.

It’s important to remember that, with AI, replacing humans isn’t an option just yet. The businesses that are succeeding the most are the ones using AI to augment and improve human processes, rather than ditching their workforce for the tech.

Cloud hosting platform Vercel has just revealed a big internal data breach.

The security incident stemmed from a breach in a third-party AI tool’s Google Workspace OAuth application, which threat actors used to access an employee’s Workspace account.

The company has confirmed that its popular open-source projects, including Next.js and Turbopack, remain secure.

What to Know About the Breach

The breach was due to an app made by Context AI, Vercel says, which one employee downloaded and connected to their corporate account.

In its statement about the incident, Vercel said that the credentials for “a limited subset of customers” were compromised. Anyone who hasn’t already been contacted was not in that group, they say.

Vercel has “deployed extensive protection measures and monitoring,” the company added.

A Hacker Claims to Be Selling Breached Data

There’s more to the story: A threat actor calling themself “ShinyHunters” has taken credit for breaching Vercel in a hacking forum, Bleeping Computer reports.

The hacker also claims to be selling the stolen data, which reportedly includes:

• Access keys
• Source code
• Database data
• Internal deployments
• API keys

The forum post further explains that, “the access I’m about to give you includes multiple employee accounts with access to several internal deployments, API keys (including some NPM tokens and some GitHub tokens).”

These claims haven’t been verified, however, so we don’t know for sure how much of what the hacker is saying is true.

Supply Chain Hacks on the Rise

The incident is an example of the growth of a type of hack that targets software developers that provide commonly used code. In this case, Vercel is behind the popular React framework Next.js.

Granted, this framework wasn’t impacted in this particular hack, but if successfully compromised, the software could open up a broad range of targets for hackers hoping to access data at scale. After all, the Vercel breach emerged through a breach at Context AI.

CEO Guillermo Rauch addressed the incident on his personal social media account, saying that “my advice to everyone is to follow the best practices of security response: secret rotation, monitoring access to your Vercel environments and linked services, and ensuring the proper use of the sensitive env variables feature.”

We’ve previously reported on a study that found one in four data breaches are due to exploits of third-party apps. Looks like we can now add one more example to the list.

According to a new survey from Tech.co, small to medium-sized businesses (SMBs) spend over a quarter of an hour (26%) of their AI use reworking output, including editing and fact-checking.

The businesses spending the most amount of time reworking, however, were more likely to see higher AI-related productivity gains.

These findings reveal the indispensable role humans are currently playing as part of AI systems in enterprises, and they remain critical as cybersecurity and quality control concerns mount.

SMBs Spend 16 Minutes Per Hour Reviewing AI Output

Tech.co’s latest survey shows that for every hour of AI use, SMBs reportedly spend an average of 16 minutes reviewing, editing, or fact-checking AI output.

This amounts to over a quarter (26%) of time within the hour. This suggests that there is a “rework tax” businesses are paying in order to reap the full benefits of AI systems within their enterprises.

Results are derived from a recent survey of 300 SMB owners and C-suite members.

5 to 25 Minutes of AI Rework Time Is Optimal for Productivity

Our research shows that businesses achieving the highest levels of productivity, saving 11+ hours or more per week, actually dedicated more time to reviewing AI output compared to the least productive groups.

59% of the group with the lowest rework time, less than 5 minutes, reported only 2 hours saved per week.

On the other hand, 20% of the group with a higher productivity saving of 20+ hours per week reportedly spend 25-35 minutes reworking AI output, and 13% spend 25-55 minutes. The highest productivity group were also the most likely to spend 55+ minutes on rework (13%).

Overall, the very existence of this “rework tax” shows AI is yet to be a complete, capable product on its own. In our survey, the businesses that understood this the most, by dedicating the necessary time to refine and adjust AI output, were more likely to see productivity benefits.

A Human in the Loop Is Still Necessary for Productivity Gains

If SMBs want to successfully adopt AI and reap its benefits, using human judgement to rework output is an operational necessity. In its current state, AI systems are unable to produce output that is completely correct and aligned all of the time, meaning that if businesses want to dodge quality control concerns, human reviewers are vital.

Likewise, cybersecurity within AI systems remain a critical concern for modern day SMBs. Alongside general cybersecurity best practice, keeping a human involved ensures systems behave and use data safely, via continuous testing and reviews.

However, businesses should also consider the potential effects of this “rework tax” on employees, who may experience fatigue or frustration if they are always correcting AI systems.

AI is finally starting to carry its weight, with new data from Tech.co discovering that 22% of small businesses owners are saving between six and ten hours per week by using AI.

That’s not all, though. A majority are seeing productivity gains, with 54% of small business owners stating that AI technology has improved their operation in some capacity since implementation.

As for what they’re using AI for, the survey found that writing tasks and research are quite common, while customer support remains one of the most productive industry for AI.

AI Is Improving Productivity

With 22% of businesses saving six to ten hours per week by using AI and 54% of business owners seeing productivity boosts, it’s safe to say that the technology is finally contributing in a serious way.

In fact, our data found that those spending heartily are seeing some of the biggest gains. Businesses spending between $1,001 and $2,500 on AI per month are the ones typically saving a full day of work, while businesses spending under $100 per month are saving less than 2 hours per month.

All in all, AI remains a classic get-what-you-pay-for situation, with free and entry-level solutions not providing much when it comes to enterprise-level productivity gains.

What Are Businesses Using AI For?

We also asked business owners what they’re actually using AI for, so that we can get a feel for how the technology can best be utilized for productivity gains.

Here are some of the top tasks businesses leaders are automating in 2026:

• Writing tasks – 29%
• Research – 26%
• Customer support – 19%
• Taking meeting notes – 16%
• Scheduling & calendar management – 16%
• Money & bookkeeping – 15%
• Staffing & team admin – 13%

Right now, it seems like businesses are only comfortable automating some of the more basic tasks, while more advanced, human-level requirements like money and staffing are still waiting in the wings for more capable AI tools.

What Tasks Are AI Best For?

While we did provide you with some information about which tasks are being automated the most, it’s also worth understanding what automated tasks are improving productivity the most.

Our data found that 80% of business leaders who automated customer support tasks with AI saw improvements in productivity, representing the largest percentage of business leaders doing so.

Essentially, when speed and efficiency are the most important means of accomplishing a task, as is the case with almost all customer support interactions, AI tools can make a big difference for your business.

A certain mindset is taking over the logistics industry, with recent data from Tech.co surveys finding that growth has become more of a priority than ever.

As for what kind of strategies they’re employing to do so, logistics businesses were primarily found to be adopting new technology and optimizing recruitment in order to facilitate this growth.

Why are businesses more focused on growth than ever before? Well, you’ll have to keep reading to find out!

Record-Breaking Rise in Logistics Businesses Prioritizing Growth

According to Tech.co’s Logistics Growth Stability Index, more logistics businesses are prioritizing growth than ever before.

The index rose to 1.3 in March 2026, marking the highest level since we started tracking in March 2025.

More notably, the rise comes after February 2026 saw the lowest prioritization of growth since we started tracking, coming in at only 0.8.

Growth Strategies Include New Tech & Recruitment

Prioritizing growth is one thing, but how are logistics businesses in 2026 actually trying to grow their companies right now?

According to our data, 19% of businesses are prioritizing new technology as a way to spur growth. That represents the most common strategy for businesses in our data, and it shows a 2% increase since February, when only 17% of businesses said the same.

The second biggest priority for growth in logistics businesses is staffing, with 18% of businesses stating that increasing retention and recruitment were the means by which they plan to grow in 2026.

Why Are Logistics Businesses So Focused on Growth?

There are three big reasons why we think businesses in the logistics industry are so focused on growth, specifically in March 2026.

• High freight demand – 83% of US logistics businesses had a moderate to high level of freight to haul in March, so operations need to grow to manage it.
• Regulatory concerns – New regulations that ban non-English speaking drivers could be fueling a need to hire more drivers and retain current staff.
• Volatile fuel costs – Fuel card adoption has risen 10% in the last month, which could point to rising fuel costs forcing businesses to find ways to earn more through growth.

The logistics industry is always in flux, but these changes are far more substantial than usual. If your operation is in need of some growth, be sure to check back with Tech.co for more logistics stats on how the industry is adapting.

Higher education facilities are increasingly implementing work-based learning in cybersecurity programs in an effort to overhaul the yawning cybersecurity skills gap, new research finds.

According to a study conducted by the University of South Florida, colleges and universities are determined to close the skills gap and have begun to incorporate hands-on learning into their existing cybersecurity programs. Practitioners argue that such an approach can create a more “scalable” and “career-ready” talent pipeline.

Cybersecurity is a growing concern among businesses around the world. The rapid adoption of AI has opened up new attack surfaces for cybercriminals, as well as giving rise to a new generation of sophisticated tools that are difficult to detect. The skills gap is commonly cited as one of the biggest obstacles in countering this evolving threat landscape.

Higher Education Firms on a Mission to Close Cybersecurity Skills Gap

Higher education facilities across the US are increasingly deploying work-based learning into their cybersecurity programs as part of an effort to address the industry skills gap, according to a new report.

With many businesses around the world struggling to cope with an escalating wave of cyberattacks, the study highlights the importance of hands-on learning to better prepare students for the future workforce.

“This is critical in an environment where technology is rapidly changing and the workforce has to adapt to those changes. Strengthening programs with the use of work-based learning can create a more scalable, inclusive, and career-ready cybersecurity talent pipeline.” – Oscar A. Aliaga, Associate Professor, University of South Florida

Hands-On Learning Proliferating Across Facilities of Different Types

To gather their findings, the researchers mapped out work-based learning (WBL) practices with a cross-sectional survey. Mainly, they were preoccupied with prevalence, regional distribution, and the characteristics of such an approach.

Ultimately, it was found that, while WBL opportunities span all levels of higher education credentials, they are most prevalent among certificates and associate degree programs. This suggests that educational practitioners are eager to embed hands-on cybersecurity learning at foundational levels.

Elsewhere, the research identified 266 WBL activities across a wide variety of types, including industry speaker series, capstone experiences, worksite visits, job shadowing, employee mentorships, and senior design projects.

Closing Skills Gap Key to Combating Mounting Security Threats

As we’ve covered elsewhere, global cybersecurity has reached a “tipping point,” with the rise of AI being a significant contributing factor. To make matters worse, businesses are understaffed and under-resourced where it matters most: their IT and security departments.

According to a recent report, 88% of professionals have experienced at least one “significant” cybersecurity consequence as a result of the skills gap. Concerningly, the data indicates that the skills gap is actually getting worse, with 95% of surveyed respondents reporting at least one skill need, up from 90% the year before.

And with 68% of employees believing that existing security measures are insufficient to deal with the rising threat level, the need for cybersecurity talent has never been greater. The pervasiveness of WBL practices across the nation poses hope for the future.