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.

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There’s often an assumption that gray hair means outdated technology skills.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.




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

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

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.”




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

  • 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.




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Are you a software engineer? Tell us what you think about vibe coding

  • Vibe coding has upended software engineering, strapping developers with a suite of new AI tools.
  • OpenAI and Tesla alum Andrej Karpathy, who coined the term, recently said he’s “never felt this much behind.”
  • Are you a software developer? Take our vibe-coding survey below.

Software engineering is changing — and we want to hear from those navigating the moment.

Programmers today find themselves with a whole new suite of AI tools, from Claude Code to Cursor to Codex. These editors enable engineers to generate entirely artificial lines of code or modify their handwritten code with the assistance of a large language model.

There’s a term for this type of AI-assisted programming: “vibe coding.”

Engineers from Meta to Google are embracing a vibe coding approach in their day-to-day work. Everyone, from teenagers to non-technical workers, suddenly seem to be building their own apps — or at least vibe-coding their way to a prototype.

It’s a whole new skill set for engineers to learn, though, one that can vary from tool to tool. (Replit is different from Lovable, which is different from Bolt, and the list goes on.) It’s also not clear, for the most experienced programmers, whether there are actually productivity gains.

Andrej Karpathy coined the famous term “vibe coding” early last year. He was a founding team member of OpenAI and led AI efforts at Tesla. In a recent X post reflecting on the field, Karpathy wrote that he had “never felt this much behind as a programmer.”

“I have a sense that I could be 10X more powerful if I just properly string together what has become available over the last ~year,” he wrote. “A failure to claim the boost feels decidedly like skill issue.”

Are you a programmer? Answer our vibe-coding survey below:




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