Tim Paradis

Vibe coding is becoming a real job now

by with No Comment Xpandfy

Lazar Jovanovic trained as a forestry engineer and has never written code.

So, when he sits down to build software, he doesn’t open an editor and start churning out syntax. He begins by describing what he wants to build to an AI tool.

Before joining the vibe-coding company Lovable, Jovanovic oversaw operations at an online marketplace. His latest job title: vibe-coding engineer.

As Jovanovic sees it, his work isn’t all that different from traditional software development because he’s still building. At Lovable, part of his job is to show customers how easy the tools are for nontechnical users.

“The skill is no longer writing code,” Jovanovic, 36, told Business Insider. “The skill is ownership, clarity, judgment, taste, subject-matter expertise.”

Vibe coding is getting more attention because just about anyone can do it to build useful software. Now, people like Jovanovic are turning it into a full-time job, while others are vibe-coding their own apps and becoming entrepreneurs.


Lazar Jovanovic

Lazar Jovanovic sees vibe coding as the thing he was born to do.

Courtesty of Lazar Jovanovic



Sam Schneidman is head of community at Base44, which lets users build software with natural-language prompts. He said he expects vibe coding to produce a new professional class of creators who want to develop apps yet aren’t fluent in languages like Python or Java.

The era of vibe coding is “great for the ideas person,” he told Business Insider.

A dozen apps in five months

Antoni Tzavelas, who lives in Toronto, began his career as a fashion designer. When the industry faltered, someone told him how much money he could make in tech. So he went back to school to study systems administration.

Tzavelas eventually became a cloud computing engineer, later a DevOps engineer, and, down the line, moved into coaching software development teams.

Even while he progressed through seven career transitions, Tzavelas, 51, said he never learned to code. Then a friend introduced him to vibe coding.

“That took everything that I’ve ever learned from every single role and brought it all together,” Tzavelas told Business Insider.

He said he has since built a dozen apps in five months. One of them is a tool he developed in two days that analyzes conversations to help users improve their connections with others. Now, Tzavelas is the cofounder of a startup called MiruPulse, which aims to commercialize the app.

Vibe coding, he said, brought him the “ultimate joy of doing a job that I just love every single morning.”

A buildup of ‘judgment debt’

Tzavelas said that while it’s easy enough to build a basic app with vibe coding, turning it into a reliable, “battle-tested” system that a large company could rely on would likely require a deeper understanding of how IT systems work. That could be a problem if you are trying to turn your idea into a business that has legs.

Another challenge that entrepreneur Alibek Dostiyarov sees in vibe coding is the buildup of “judgment debt” — a pernicious accumulation of decisions that occur when AI alone constructs the technical scaffolding of software.

Dostiyarov, who has a background in software engineering and consulting, told Business Insider that the process can let flaws slip through, and over time, those can become like cracks in a foundation.

He is the cofounder of Perceptis, which develops AI-powered software for professional services firms.

Dostiyarov said that, more than ever, companies need to prioritize sound human judgment when developing software. Vibe coding has its place for testing ideas and prototypes. That’s about as far as he is willing to go.

“There is no world that I can imagine in the near future where we’ll be just saying, ‘OK, now that we’ve tested it, let’s just integrate it directly into our system,'” Dostiyarov said. Instead, he said, a vibe-coded prototype would need to be rebuilt by trained engineers.

The tools are changing fast

Vibe coding sometimes gets a bad rap among industry veterans, Adam Janes, a fractional CTO, told Business Insider.

“It’s a very touchy subject for devs, because they like to think that they have this real expertise,” he said.

Yet Janes thinks an opportunity exists for people who are experts in an area to become professional vibe coders because they can pair their knowledge with AI’s technical wizardry.

Because AI tends to either over-engineer or under-engineer a problem, Janes said, technical expertise is still a big help. Even so, as AI continues to improve, vibe coders could find it easier to develop robust software, he said.

“Three months ago, we were talking about a completely different world,” Janes said.

Will Wilson, CEO and cofounder of Antithesis, an autonomous software-testing platform, told Business Insider that he’s witnessed a similar shift since the arrival of models such as Claude Opus 4.5 last year.

Their emergence marked a tipping point, he said, though bottlenecks remain. Wilson said AI coding tools can spit out so much that it becomes “astonishingly hard” to review and ensure it won’t “blow up your business.”

With vibe coding, he said, “the burden all shifts to testing and reviewing the code and making sure it works right.”

There aren’t good estimates of how many professional-level vibe coders are out there, though AI is taking on larger chunks of coding, even in traditional engineering.

Articulating what AI needs

For Jovanovic, there’s no going back. Before Lovable hired him, he said he built dozens of apps — including one for journaling and one to track his jogs near his home in Sarasota, Florida.

It took Jovanovic about a year of vibe coding to go from enthusiast to employee. The toughest part of the job, he said, is articulating what he needs so AI can build it.

Jovanovic still gets goosebumps when he thinks about the first time he built an app.

“This feels like the thing that I was born to do,” he said.




Source link

Employees-who-dont-vibe-code-are-probably-underperforming-fintech-startup.jpeg

Employees who don’t vibe code are ‘probably underperforming,’ fintech startup product chief says

by with No Comment Xpandfy

The product chief of a $32 billion fintech startup has called out employees who aren’t using AI-assisted coding tools.

Geoff Charles, chief product officer of Ramp, an AI fintech startup that helps companies pay their bills, said in a Sunday episode of “Behind the Craft” podcast that employees are expected to be AI-native.

“If you’re not using Claude code this year, no matter what your role is, you’re probably underperforming compared to others on the company,” he added.

Charles said that the company frames AI proficiency across multiple levels. At the bottom level — level zero — are people who “sometimes use ChatGPT.” At the top, level three, are people who are “systems builders.”

Employees who vibe code and can proficiently build apps that automate parts of their job belong to level two, while staff who have built custom GPTs and have some experience with Claude Code fall under level one.

“Our job is to get everyone in the organization up the ladder,” Charles said.

“The people who are still in L0, they will most likely not be at the company,” he added, referring to level zero.

“If you’re not a self-starter and you don’t have that growth mindset, it’s going to be very, very hard to train,” he said.

Charles said 50% of the company’s code is built by AI, and it would probably be 80% by March. He added that the role of product managers will evolve in the AI-native era, with some becoming builders and others focusing on business strategy.

The fintech startup announced in November that it raised $300 million in funding, bringing its valuation to $32 billion. The round was led by Lightspeed Venture Partners, with investors including Founders Fund, Coatue, GIC, Thrive Capital, and Khosla Ventures, among others.

Companies going all in on AI

Charles’ comments come as tech companies increasingly reshape their workforces around AI.

Block last month cut nearly half of its workforce, saying advancements in AI were behind the layoffs.

Last week, Atlassian laid off about 1,600 roles, roughly 10% of its global staff, as the Australian-American proprietary software company reorganizes to prioritize AI development and enterprise growth.

“It would be disingenuous to pretend AI doesn’t change the mix of skills we need or the number of roles required in certain areas. It does,” CEO Mike Cannon-Brookes wrote in a message to employees.

Ramp is not the only company paying closer attention to how employees use AI at work.

In February, managers at Google told some staff in non-technical roles that they are expected to incorporate AI into their daily workflows, four employees familiar with the matter told Business Insider.

In some cases, non-technical employees were told their use of AI could factor into their performance reviews later this year, two of the employees said.

Daniel Yanisse, the CEO of background-check startup Checkr, said the company has pushed employees across departments to adopt AI tools, not just engineers.

“We gave every employee a monthly stipend to try AI tools, and we did AI days and demos. After one year, 95% of the employees use prompting daily,” Yanisse said last month.




Source link

Lovable-exec-says-big-boys-and-girls-like-OpenAI-and.jpeg

Lovable exec says ‘big boys and girls’ like OpenAI and Anthropic worry her more than other vibe coding startups

by with No Comment Xpandfy

Other vibe coding players are not the biggest competition, says one Lovable exec.

“I always worry about the big boys and girls in the world,” Lovable’s head of growth Elena Verna said on a Sunday episode of the “20VC” podcast. “So, OpenAIs, Anthropics, Googles, Apples, more so than our competitors that spring up from the bottom or from sideways.”

This is because the distribution power of these tech giants and frontier labs in the market is unparalleled, she said.

Stockholm-based Lovable was valued at $6.6 billion in a December funding round led by CapitalG and Menlo Ventures. It competes with other vibe coding startups like Cursor, Replit, and Emergent, as well as far bigger and better-funded players, including OpenAI, Anthropic, and Microsoft, that make their own AI coding tools.

Verna, who joined the startup last May after a series of advisory and head of growth stints at various startups, said that in a world where products are becoming increasingly similar, distribution and growth are winning strategies.

“Whoever has the best distribution that is earned, that is competitively defensible, that is sustainable, that is predictable, is going to be the winner in the market,” she said. “I worry about the companies that have that figured out.”

Verna’s comments about competition follow a period of brutal comparisons between products made by vibe coding startups and Anthropic’s Claude Code.

After Anthropic released its latest model, Opus 4.6, founders and developers said on X that they are ditching their expensive Cursor and Lovable subscriptions for Claude Code.

Still, Lovable is going strong.

The Swedish startup’s annual recurring revenue has surged by more than 30%, from $300 million to $400 million in a single month, Business Insider reported. ARR, a key metric to gauge startup performance, refers to the predictable revenue a company expects to generate over a year.

Lovable’s chief revenue officer, Ryan Meadows, told Business Insider that the company plans to more than double its head count by the end of 2026, from 146 to 350 employees.

He added that Lovable, which specializes in making coding user-friendly, sees at least 200,000 new vibe coding projects created each day.




Source link

Im-an-Amazon-tech-lead-who-got-promoted-by-building.jpeg

I’m an Amazon tech lead who got promoted by building AI products. Here are my top vibe coding tips.

by with No Comment Xpandfy

This as-told-to essay is based on a conversation with Anni Chen, who has worked in Amazon software engineering for about three-and-a-half years. It has been edited for length and clarity. Business Insider has verified her employment history.

AI helped me code, but more importantly, it helped with turning it into products. It’s the combination of grasping AI and translating it into scalable products that helped me get promoted faster.

I started off as a Software Engineer I, an entry-level role, in 2022. I was in the recommendations team working on serving recommendation widgets.

About two years ago, I started working on AI products on the side. That became huge and eventually spun off into its own team, which I’m a founding engineer of.

I was promoted in the recommendations team to Software Engineer II, and then I got promoted in the current team to senior engineer.

I focus on what we call memory, which powers personalization in generative AI experiences across Amazon.

AI writes 95% of my code

I started using AI as a side project to generate engaging titles for recommendation widgets when ChatGPT and Claude emerged. I saw how powerful it is in generating something really creative.

I started thinking: whenever I have a question or I want to code something up, I’ll just ask AI for help first before I attempt it.

I saw that the solution it came up with was leveling up my own code, and it helped me code more, too. Now I would say almost 95% of the code authored by me is written by AI.

I’m not just using AI to code; I also integrate AI’s output into products. I need to have a deep understanding of how AI works, what works well, and what doesn’t.

I have to be open and receptive to new models and tools coming out that can help with product iterations and make products better.

I work as a tech lead on large-scale LLM-driven systems in production environments, so I have a front-row seat to how AI-assisted workflows behave, not just in prototypes but under real-world scale and cross-team collaboration.

Top tips for vibe coding

The first tip is understanding the inner workings of LLMs and where they might fail.

LLMs are pre-trained — they’re trained on a large corpus, and it’s a probabilistic game. It’s followed by supervised fine-tuning, so the model will answer based on the structuring of a question and the answering format. Lastly, it’s followed by RLHF — reinforcement learning from human feedback.

By understanding these three steps, you can know, for example, when the LLM will not understand what you’re talking about, and when it needs domain knowledge from you. You will know when to use a new window or why hallucinations happen.

By understanding the limitations of the context window, you know when to break problems down. You will learn how to follow the structure to break things down into lower levels, and then you slowly focus on each component and generate.

By understanding the inner workings, you also know that you have to explain things to a peer. If you don’t explain in detail, it will default all those assumptions to the most common pattern, but that might not fit your use case.

My second tip: Think before vibe coding.

If you check the answer first, then your thoughts will be swayed by the answers. Compare your thoughts versus the LLM’s and see what the gaps are — what you didn’t know, and why the answer differs. From there, you know what implicit assumptions you haven’t told the LLM.

Thirdly, prompt for hard questions. Ask questions like what is the fallback when there is an error, or how this is going to scale? This is like a teacher asking a student, or a senior engineer asking a junior engineer to make sure the hard cases are covered. If you want the product to scale, think about it from day one and be conscious about asking those scaling questions.

Lastly, review and understand. Always review at each step, not just review after the whole code is generated. This ensures errors stop early rather than cascading all the way to the end, where you need to redo everything.

Creating wrong code is very dangerous. The presence of code makes people think, “Okay, this is good, it’s working.” But wrong code that enters production can cause more damage than the absence of functionality.

Understanding code is still important

You have to understand your own code. AI lowers the barrier to writing code, but not the responsibility for understanding it.

If something goes wrong and the code was committed by you, you’re the one responsible.

Imagine your code breaks in production, and you need to fix it, and you say, “I also don’t know, AI told me.” That’s not the correct way.

I don’t think we can entrust AI with such high-stakes tasks yet.

Understanding becomes easier with AI because it’s also a perfect learning opportunity. You can simply open another window and ask it to explain the concept.

If you ask in the same window about what it produced, it will explain only in that context. But you want to understand the concept more generally and see whether it makes sense to apply in this case.

Do you have a story to share about coding with AI? Contact this reporter at cmlee@businessinsider.com.




Source link

Chong Ming Lee, Junior News Reporter at Business Insider's Singapore bureau.

Emergent’s CEO told us these are the 2 biggest threats to vibe coding

by with No Comment Xpandfy

Emergent CEO Mukund Jha told Business Insider the fast-growing vibe coding movement faces two major risks.

The “biggest threat to vibe coding” is the quality of the software it produces, Jha said.

Many AI coding tools can generate apps quickly, but the output can still be buggy, fragile, or difficult to scale. The vibe coding industry depends on those systems getting better.

“There’s a big bet that the quality of software that gets produced is going to improve exponentially,” he said. “If that doesn’t happen, that’s a big threat,” he added.

Another risk could come from AI itself. Jha said it is possible the industry could eventually “skip the whole software building aspect” if autonomous AI systems become powerful enough to replace software.

“We went from like Nokia phones to BlackBerry, and then everybody went to iPhone,” he said. “It could be that the software was the BlackBerry.”

People might eventually rely on AI agents or large language models that perform tasks without needing apps, he added.

Emergent announced in February that it reached $100 million in annual recurring revenue, or ARR, in just eight months after launching. ARR is the revenue a company expects to generate in a year from subscriptions or other recurring payments.

The company said it doubled its ARR from $50 million to $100 million in a single month, underscoring the rapid growth of AI coding startups.

In January, Business Insider reported that the vibe coding startup raised a $70 million Series B round, bringing its total funding to about $100 million. Investors include Khosla Ventures, SoftBank Vision Fund 2, Lightspeed, Prosus, Together, Y Combinator, and Google’s AI Futures Fund.

Just six months earlier, the startup raised $23 million in a Series A round, highlighting how quickly top AI startups are attracting capital during the boom.

Read more about vibe coding

The rise of AI coding startups

It’s not just Emergent. Ryan Meadows, the chief revenue officer at Lovable, a Swedish vibe-coding startup, told Business Insider in an exclusive interview that its annual recurring revenue jumped more than 30% in one month, rising from $300 million to $400 million.

Meadows, said that the recent growth surge came after the launch of Claude Code, Anthropics’ AI coding tool. Rather than hurting Lovable’s business, Meadows said many developers are using both products.

“It’s a rising tide,” he told Business Insider. “We’ve been super happy with what we’re seeing.”

Other players are also seeing explosive growth. In late 2025, Cursor, another breakout company in the vibe coding space, said it had reached $1 billion in annualized revenue and was valued at nearly $30 billion, according to a company announcement in November.

But some industry leaders have warned about the rising costs associated with AI coding tools.

Billionaire investor Chamath Palihapitiya said his software company is reconsidering its use of Cursor amid rising expenses tied to AI development.

“Our costs have more than tripled since November,” Palihapitiya said on an episode of the “All-In Podcast” published Friday. “Between the inference cost that we pay AWS, which is ginormous, between our cost with Cursor, between Anthropic, we are just spending millions.”

AI companies themselves have acknowledged that more advanced features can drive up costs. Earlier this week, Anthropic introduced Code Review, a tool designed to detect complex coding issues and identify bugs. The company said the feature “optimizes for depth,” which makes it “more expensive than lighter-weight solutions like the Claude Code GitHub Action.”




Source link

Ben Bergman

AI vibe coding darling Lovable is racing toward $1 billion in revenue

by with No Comment Xpandfy

Lovable, a Swedish vibe coding startup valued at $6.6 billion, saw its torrid growth accelerate even as Anthropic’s Claude Code went viral over the past few months.

The Swedish startup says its annual recurring revenue has surged by more than 30%, from $300 million to $400 million in a single month, and could top $1 billion by year’s end, Lovable’s chief revenue officer, Ryan Meadows, told Business Insider in an exclusive interview. ARR refers to the predictable revenue a company expects to generate over a year from subscriptions or recurring contracts.

Lovable’s breakout growth comes amid a broader boom in AI-powered coding tools, which include Claude Code and startup Cursor, which was last valued at nearly $30 billion. In late 2025, Cursor said it had $1 billion in annualized revenue.

Lovable launched at the end of 2024 and reached $100 million in ARR just eight months later, doubling to $200 million by the end of 2025.

Vibe coding allows novices with limited programming expertise to create code using AI. Lovable, founded by Anton Osika and Fabian Hedin, aims to make coding even more user-friendly, enabling non-engineers to make software and applications. It was valued at $6.6 billion in a December funding round led by CapitalG and Menlo Ventures’ Anthology fund.

“It’s accelerating quite a bit,” Meadows said. “We’ve doubled the number of active users daily just in the last couple of months.” Lovable now boasts over 15 million daily active users and sees 200,000 new vibe coding projects created each day, according to Meadows.

The vast majority of Lovable users are still non-technical founders and entrepreneurs, but Meadows says the company is seeing its fastest growth from the enterprise business it launched in August.

Anthropic is a partner rather than a competitor

Lovable’s most recent growth spurt occurred after the release of Claude Code. But rather than eating into Lovable’s market share, Meadows says most customers use both tools. Professional software developers and engineering teams use Claude, while non-technical staffers prefer Lovable.

“It’s a rising tide,” he said. “We’ve been super happy with what we’re seeing.”

Lovable is powered by Claude, and when Anthropic launched its marketplace this week, it prominently featured Lovable.

“They’re pretty committed to working with us to pass business through,” said Meadows. “We’re going to keep investing in that partnership.”

A hiring spree

Lovable has rocketed to $400 million in ARR with a lean staff of just 146 employees, said Meadows. This year, the company will embark on a hiring spree, mostly in product and engineering roles, and will end the year with around 350 employees, he added.

Though its engineering team will continue to be based in Stockholm, the company will be opening its first US office this year in Boston to house go-to-market roles.

“We can’t hire fast enough,” Meadows said.

Have a tip? Contact Ben Bergman via email at bbergman@businessinsider.com or Signal at BenBergman.11




Source link

Shuby headshot

An Accel VC says the vibe coding market is big enough for Cursor and Claude Code

by with No Comment Xpandfy

The great vibe coding war of 2026 isn’t the bloodbath it appears, says a venture capitalist whose firm backed Cursor.

On an episode of the “20VC” podcast released on Monday, Miles Clements, a partner at VC firm Accel, said that the AI-assisted coding industry is big enough for Anthropic’s Claude Code and Cursor.

After Anthropic released its latest model, Opus 4.6, last month, founders and developers said on X that they are ditching Cursor for Anthropic’s Claude Code.

“This market is growing enormously, and I don’t think a lot of these companies are actually experiencing success at the expense of the others,” Clements said.

Cursor, founded in 2022, was valued at $29.3 billion late last year. Accel first invested in the AI coding startup in June and co-led its $2.3 billion Series D round in November.

On the podcast, Clements called Claude Code an “amazing product.” Still, he said, there are two reasons Claude’s latest improvements don’t hurt Cursor.

“First of all, they’re bringing so many new cohorts of users online, so people who would not have been software developers a year ago today can be software developers with these tools,” he said.

Second, the market is expanding because consumption per customer is increasing, Clements added.

Last week, Chamath Palihapitiya, a VC and the founder of software incubator 8090, said that Cursor was one of his company’s biggest AI costs.

“We need to migrate off of Cursor,” he wrote on X. “It’s just too expensive vs Claude Code. The latter is equivalent, and if you use the Pro plan, you eliminate huge Cursor bills for token consumption.”

Cursor did not respond to a request for comment from Business Insider.

On a podcast released in late February, Insight Partners cofounder Jerry Murdock said that Cursor is behind its peers.

“Most of the companies I mentioned, their view is that Cursor is obsolete today,” he said. “I think those guys are going to have to quickly embrace autonomous agents.”

On Monday’s podcast, Clements countered Murdock’s remarks.

“Like, all due respect, I thought about playing in the NFL, but instead I walked onto a college football team and was the fifth-string inside linebacker,” he said. “You’re not looking at any real metrics. Like, who are these people to make these judgments?”

A representative for Murdock did not immediately respond to a request for comment.




Source link

Chong Ming Lee, Junior News Reporter at Business Insider's Singapore bureau.

I’m a 78-year-old retiree who’s vibe coding. Being out of the workforce doesn’t mean we can’t use AI like tech pros.

by with No Comment Xpandfy

This as-told-to essay is based on a conversation with Lewis Dickson, a 78-year-old retiree and technology consultant. It’s been edited for length and clarity.

I’ve been in technology for a long time. I worked for IBM in the late 1970s. I did technology consulting for a Fortune 500 company in Atlanta from 2015 to 2024. I’ve taught many engineers and customers over the years.

I’m in semi-retirement mode now. Technology isn’t work to me — it’s fun.

When ChatGPT came out, I jumped on it. About six or eight months ago, when vibe coding became hot, I said, “Well, I need to try this out.”

I researched and found Emergent. What I liked is that they had the full stack. I didn’t have to connect anything or get my developers on the line to handle the back-end. I could just get on there and start.

I began with a couple of simple things. Now I’ve probably done a dozen or more vibe-coded apps.

The last two were for this AED company. They wanted the ability to access their existing camera provider’s website and extract their data. So I vibe-coded an app that would do that — pull that data in.

I also vibe-coded an AI voice app for them. It’s a web app, so you go to it on your phone, hit a button, and ask, “What’s our AED status?” It checks the database, then returns the information.

When I first showed the CEO a demo, he lit up. He thought it was the coolest thing he’d ever seen.

Older people can move fast

Most people think an old guy like me would have a flip phone.

When I started as a ham radio operator at 13, I was using Morse code on tubes, transmitters, and receivers. To go from that to what we’ve gone through with phones and cellphones, and then to watch that transition over the years into AI and be closely involved, I just love the technology — both the hardware and the software.

A lot of young kids today are into software but don’t know much about the hardware piece. Having a wide background comes in handy.

There’s often an assumption that gray hair means outdated technology skills. I understand where that perception comes from, but it’s not always accurate.

Many of us have moved just as quickly with the rise of AI as younger professionals. The advantage we bring is perspective: decades of experience that allow us to apply AI strategically, not just technically.

Some people would say older people retire and lose purpose. I’ve never had that problem because I’ve always had a passion for doing technical things.

I’m constantly on my laptop and phone, doing something related to AI and learning. You’ve got to watch a lot of YouTube and social media, learn what’s coming and what’s new.

How seniors can use AI for everyday life

I’m teaching AI to seniors now. In my class back in November, we were talking about data centers, what’s behind AI.

There’s a lady named Sue who’s 100 years old. Near the end of the class, Sue came up and asked, “What’s a semiconductor?”

I have a hardware background, so I answered her question at a very high level. She listened intently and wrote down a few notes.

After that class, I thought, “I need to do more for her.” So I used AI to create a video that went through the evolution of tubes in the 20s and 30s — things they could relate to — and old radios and TVs. Then we went to transistors in the late 40s and 50s, and what that meant.

The seniors I taught have now learned enough to take over their internal resident newsletter and use AI to help write it. They also created images for the newsletter with AI.

They are using AI to shop, check for bargains, and research their items.

I’ve shown them how to recognize different plants and birds with AI. They’ll walk through their garden area, take a picture, and ask ChatGPT or Gemini.

Do you have a story to share about vibe coding? Contact this reporter at cmlee@businessinsider.com.




Source link

Katherine Li, West Coast breaking news reporter at the Business Insider.

An identity verification AI startup is having all employees try vibe coding

by with No Comment Xpandfy

If you work for a San Francisco startup and don’t know how to code, you could soon be asked to get creative with vibe coding.

Checkr, an AI-powered background check company, gave Business Insider a glimpse of how employees are actually using AI.

Checkr CEO Daniel Yanisse said that the company is going “all in” and trying everything to encourage its employees to fully embrace AI — including staff that don’t work in engineering roles.

“We really pride ourselves on using AI to the maximum possible amount,” said Yanisse. “We gave every employee a monthly stipend to try AI tools, and we did AI days and demos. After one year, 95% of the employees use prompting daily.”

“This year, we’re going to level up and move to building with AI, as in vibe coding,” Yanisse added. “I’m working with all of our teams now, and we’re going to do our AI days soon in March, where we’re going to make every non-technical person vibe code their own business apps.”

Yanisse said that many employees who have no idea how to code, who work in finance, legal, and HR, are already vibecoding apps to automate their workflows and problem-solve, such as building tools that help clean up large spreadsheets.

While Checkr is evaluating a variety of builder tools like Lovable, Replit, and Claude Code, Yanisse said Cursor is a clear standout and “has amazing adoption” among both engineers and non-technical staff, but Lovable is the best place to start for people with no coding experience.

“Probably, we’re going to buy all of them and just use the right tool for the right person,” Yanisse said of different AI coding tools.

“We have AI solution engineers who are available to actually partner and help, so they would come and help you and unstuck you if you have a problem, and take you all the way to success,” Yanisse added. “And then you’re on your way because then we share success stories with everyone in the company.”

AI adoption in some companies can be complicated

In practice, data shows that AI adoption can be complicated in a large enterprise. Competence with AI tools can be very uneven across the board, and security risks can mount without clear guidelines on AI usage.

According to a survey published in November by Moveworks, an AI-powered platform that automates IT and HR support, most executives said that non-technical employees are playing a bigger role in driving AI use, and that 78% have seen successful AI projects originate directly from support staff looking to solve daily challenges.

The National Cybersecurity Alliance also wrote in its Annual Cybersecurity Attitudes and Behaviors Report that AI adoption has surged to 65% globally as of the end of 2025, but more than half of these AI users never received any training in privacy and security risks. The report surveyed over 6,500 workers worldwide.

“A few years ago, most businesses were still debating whether AI was something they really needed,” Louis Riat-Bonello of Optisearch, an AI-powered marketing platform that specializes in SEO, told Business Insider.

“The businesses getting the best results aren’t blindly chasing automation. They’re using AI to support smarter decisions, move faster, and free up teams to focus on strategy and creativity,” Riat-Bonello added. “That balance is what will matter long after the hype fades.”

Yanisse said that in the age of AI, the company is looking for creative and adaptable people, because while AI will eliminate some roles, it will create others.

“We are constantly training and helping people update their skills and careers,” said Yanisse. “The job of the product designer and the job of the marketer are all completely shifting right now.”

“We’re over 900 people, so we’re not a small startup, but I’m a startup guy, and I’m a builder,” Yanisse added. “The people who come here need to be OK with uncertainty, be self-driven, adaptable, flexible, willing to do new things, and solve new problems without too much guidance or structure.”




Source link

I-embedded-myself-in-a-vibe-coding-team-at-Geminis.jpeg

I embedded myself in a vibe coding team at Gemini’s AI hackathon in Singapore. Building an app in 7 hours takes real work.

by with No Comment Xpandfy

  • I spent seven hours with a vibe coding team at Google’s Gemini 3 hackathon in Singapore.
  • Watching from the sidelines was intense.
  • From prompting and debugging to filming the demo — here’s how it all unfolded.

Just after sunrise, four vibe coding enthusiasts from Malaysia crossed into Singapore with a loose idea — and a bet that AI could build most of their app.

Hours later, they were racing to prototype it at Google’s Gemini 3 Hackathon in Singapore.

The four friends, all in their late 30s to 40s, came from different professional backgrounds. Chan Wei Khjan is an accountant. Chan Ler-Kuan lectures on AI at a private university. Loh Wah Kiang works in IT. Lee How Siem, who goes by Benny, is the chief technology officer of a Malaysian startup.

Their initial idea was a “feng shui” app to analyze properties in Singapore — a potentially lucrative use case in a market obsessed with housing and wealth accumulation. Feng shui is a traditional Chinese practice that evaluates how a person’s surroundings, along with birth factors, influence luck and well-being.

I embedded with the team at Google’s developer space in Singapore in January to observe how a vibe-coding project comes together — or nearly falls apart — in seven hours.

9:30 a.m.: The brief

Thorsten Schaeff from Google DeepMind welcomed the participants.

Lee Chong Ming/Business Insider

The assignment: Teams of up to four people had to build a working demo, publish a public repository with code, and submit a short video explaining their project by 5:30 p.m.

Each project had to fit into one of six tracks, including generative media, deep research, and enterprise orchestration.

Organized by Google DeepMind and 65labs, Singapore’s AI builder collective, the hackathon featured a 100,000-credit Gemini API prize pool, with first place getting 30,000 credits.

By the end of the day, 189 participants had built 76 projects.

10:30 a.m.: Getting started


Hackathon team getting started

The team discusses how to prototype their idea.

Lee Chong Ming/Business Insider

The team had pivoted to a new idea due to time constraints: a feng shui app that could analyse a user’s outfit and workspace through the phone camera in real time and assess how “lucky” they were.

Wei Khjan took the lead on prompting. He typed the first instructions into Claude, asking it to generate the workflow and code. Ler-Kuan focused on whether the AI’s output aligned with feng shui concepts. Wah Kiang and Benny hovered over the codebase, refining ideas and flagging issues.

“For people who don’t know how to read code, it’s helpful to have people who do,” Wei Khjan said.

While waiting for the code to be generated, Ler-Kuan opened Google’s AI Studio to design the app’s logo. They called their app “Feng Shui Banana.”

11:40 a.m.: The bugs arrive


computer screen with code

The implementation plan was generated by AI.

Lee Chong Ming/Business Insider

After about an hour, Claude generated the initial codebase for the app. It was designed to work with the Gemini Live API, enabling real-time image and text analysis. It ran but was riddled with bugs.

An error message flashed when they tested the camera feature, so Wei Khjan copied the error back into the AI and asked for it to be fixed. Minutes later, the feature worked.

It wasn’t right. The feng shui logic was off, especially where colour analysis intersected with the user’s birth timings. Ler-Kuan manually corrected the underlying dictionary and its mappings.

The team kept prompting to tighten the features: shorter explanations, clearer output, and more streamlined user interfaces.

By 12 p.m., the app was rough, but it existed.

12:20 p.m.: Lunch can wait


Testing the feng shui app

Ler-Kuan tests the camera feature on the app.

Lee Chong Ming/Business Insider

Lunch arrived. The team stayed glued to their screens.

The app didn’t respond instantly when a user changed their outfit, nor did it update its feng shui analysis in real time.

Wei Khjan explained how one prompt matters. Instead of issuing commands, he asked the AI to “discuss it with me.” The shift changed how the model reasoned, and it worked more like a collaborator.

After some prompting, the app updated with a real-time camera analysis. It was striking to watch a feature emerging from a short back-and-forth with AI.

1 p.m.: Putting the app to the test


Screenshot of me testing the app

A screenshot of the feng shui app on my phone as I test its camera feature.

Lee Chong Ming/Business Insider

I helped the team test the app.

The camera correctly identified what I was wearing: a dark green polo, a yellow participant tag, and a white name card hanging from my neck. According to the app, I was already wearing colours aligned with my luck for the day.

The app suggested small tweaks, such as additional accessories, that could enhance the feng shui of my outfit.

1:20 p.m.: Pizza break


Pizza break

The team munched down their pizzas in about 20 minutes.

Lee Chong Ming/Business Insider

They finally had lunch and joked around to ease the tension. Four hours remained before they had to submit their project.

1:40 p.m.: Back to work


Feng shui banana landing page

The landing page for their app.

Lee Chong Ming/Business Insider

Ler-Kuan shifted focus to workspace feng shui, feeding knowledge into the model and refining how the app would evaluate desks and work setups. Wah Kiang and Benny worked on the video demo.

By 2 p.m., they had a landing page that looked animated and 3D. When I asked Wei Khjan how he felt, he smiled.

The team also revisited the app’s tagline. After cycling through suggestions from multiple AI models, they settled on a line that didn’t come from an AI at all: “A wisdom, not a superstition.”

3 p.m.: Filming the demo


Filming the demo

Wah Kiang and Benny are filming Ler-Kuan as they reenact scenes for their demo video.

Lee Chong Ming/Business Insider

By late afternoon, the restlessness was showing. The team snacked and paced, then decided to film the video explaining their project.

They used Gemini to generate a storyboard for the demo video. The model laid out several scenes and drafted the script. The team followed along, filming clips and stitching everything together as they went.

Their workspace feature was also up and running.

4 p.m.: Final touches


Hackathon team scrambling

The team is hard at work as the deadline approaches.

Lee Chong Ming/Business Insider

The app had come together nicely. With some time to spare, they decided to add audio output for users who prefer listening to reading on a screen.

The first attempt to generate a voice using AI fell flat. It sounded robotic.

After debugging and several iterations, they landed on a voice they liked, similar to how a Chinese feng shui master might speak.

5:30 p.m.: Deadline


Finishing the hackathon

Taking a group photo as they submit the project.

Lee Chong Ming/Business Insider

As the deadline approached, the team was still stitching clips for their video and nitpicking the AI-generated presenter voice.

The organizers had urged teams to submit early. With about 15 minutes to spare, they made the call to lock the final cut and hit submit.

Then it was over. The hunger hit immediately, and everyone got in line for some well-deserved food.

Even as an observer, watching from the sidelines was tiring. Seven hours of vibe coding turned out to be anything but effortless.

The team didn’t win a prize, but agreed that the hackathon had been worth it.

“Sometimes, the best experiences come from saying ‘yes’ without overthinking,” said Ler Kuan. “Innovation starts with curiosity and a little bit of spontaneity.”

Do you have a story to share about vibe coding? Contact this reporter at cmlee@businessinsider.com.




Source link