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How SMBs Can Build AI Apps Using Plain Language

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Every new trend comes with its own nomenclature.

In the 1980s, it was yuppie for young urban professional. The 1990s saw the rise of the expression soccer mom. In the 2000s, we had hipsters.

Now there’s a new term in artificial intelligence programming: vibe coding.

Coined by OpenAI co-founder Andrej Karpathy, vibe coding refers to the writing of computer programs without knowing programming languages. Instead, users use plain language and focus on the vibe of the project.

“There’s a new kind of coding I call ‘vibe coding,’ where you fully give in to the vibes, embrace exponentials and forget that the code even exists,” wrote Karpathy in a February post on social platform X. “It’s possible because the [large language models (LLMs)] … are getting too good.”

For example, a company can use the Code Interpreter mode in OpenAI’s GPT-5 and instruct it to create a chatbot that answers customer questions. The AI model will generate the application for a company to test and refine through more prompts.

Smallto medium-sized businesses (SMBs) can turn an idea into a working prototype in hours instead of weeks. Tools from platforms like Google AI Studio are making this process accessible to non-technical users.

Some people have successfully launched businesses after creating apps using vibe coding, CNBC reported in May.

Amjad Masad, CEO of Replit, a coding platform, said in an interview with the Big Technology Podcast that anyone from HR folks to doctors and Uber drivers can now develop apps based on their ideas.

“Everyone in the world has ideas,” Masad said during the interview. “People build so much domain knowledge about their field of work, but they never could make it into software because they didn’t have the skill or capital.”

For example, Maor Shlomo, the non-technical founder of Base44, used vibe coding to create a no-code development platform. Within six months, it attracted 250,000 users and was acquired in June by website creator Wix for $80 million.

“This new approach allows people to simply express what they want to build, while intelligent agents do the heavy lifting,” Wix said in a statement.

Here’s one way to start, according to CNBC:

Read also: AI Coding Assistants Give Big-Tech Powers to Small Businesses

What Are the Risks?

In practice, vibe coding changes the role of the human from writing every line of code to guiding the AI, validating results and deciding what’s ready for production. This enables SMBs to experiment with new offerings, automate tasks or build internal tools without a large IT budget.

Vibe coding also gives users a faster way to test ideas, cut development costs and give creative teams the ability to build their own solutions. It can give them a competitive edge, letting small players innovate quickly without the overhead that slows down larger firms, Forbes reported Aug. 4.

However, for use in core financial systems, regulated processes or customer-facing platforms that carry legal or financial risks, experienced developers should review the code before launching it, according to the paper, “Vibe Coding as a Reconfiguration of Intent Mediation in Software Development: Definition, Implications and Research Agenda.”

“Black box codebases, ethical and data protection blind spots, and inconsistent documentation undermine auditability and verifiability, posing significant barriers to compliance in regulated sectors such as healthcare and finance,” the paper said.

This speed and accessibility come with trade-offs. AI-generated code can be buggy, not secure, and difficult to maintain if no one fully understands how it works. Also, the technology isn’t yet reliable enough for systems where accuracy, compliance and security are critical, the paper said.

As a result, companies must carefully weigh the risks and rewards of using vibe coding, ensuring it is used for the right use cases to prevent introducing a new risk to the business.

For all PYMNTS AI coverage, subscribe to the daily AI Newsletter.

Read more:

Apple and Anthropic Building AI-Powered Coding Platform

OpenAI Developing AI Agent to Replace Software Engineers, CFO Says

AI Agents’ Rise Promises IT Revolution, but Readiness Questions Remain





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How Artificial Intelligence is Redefining Business Process Automation

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In today’s fast-paced economy, businesses are under constant pressure to operate more efficiently while reducing costs and improving customer experiences. Automation has long been a solution, but traditional methods such as simple scripts or rigid workflows often fall short in terms of adaptability and intelligence. This is where artificial intelligence comes into play. By partnering with an Artificial Intelligence Development Company, organizations can unlock new opportunities for smarter decision-making, streamlined operations, and scalable growth.

The growing interest in AI-driven automation reflects its role as a key enabler of digital transformation. Unlike conventional automation, AI systems can analyze large datasets, learn from patterns, and make predictions that allow businesses to stay competitive in increasingly dynamic markets.

Why AI for Business Process Automation

Traditional automation methods—such as scripts or Robotic Process Automation (RPA)—are useful for handling repetitive, rule-based tasks. However, they lack flexibility and cannot adapt to new or changing conditions without manual intervention. Artificial intelligence takes automation a step further by enabling systems to learn, adapt, and improve over time.

Through machine learning and advanced data analytics, AI can identify hidden patterns, make predictions, and support real-time decision-making. This makes it possible not only to automate processes but also to optimize them dynamically, driving more value than traditional approaches.

Key Areas of Application

Finance
AI enables faster and more secure payment processing, advanced transaction analysis, and fraud detection systems that continuously learn to recognize suspicious patterns.

Marketing and Sales
From demand forecasting and personalized customer experiences to intelligent chatbots, AI helps companies better understand their audience and increase conversion rates.

Manufacturing and Logistics
AI-powered tools streamline supply chain management, predict equipment maintenance needs, and reduce downtime, ensuring smoother operations and higher efficiency.

Human Resources (HR)
Recruitment processes are enhanced through automated resume screening, predictive analysis of employee retention, and data-driven insights for workforce planning.

Advantages of Implementation

The implementation of AI in business processes brings several clear advantages. One of the most significant is cost reduction: by automating repetitive, labor-intensive tasks, companies can cut manual rework and optimize resource allocation, which lowers operating expenses without sacrificing quality. AI also accelerates processes, as models are capable of handling large data streams in near real time.

This speed translates into faster approvals, more efficient routing, more accurate forecasting, and quicker customer responses, all of which shorten cycle times. Another key benefit is error minimization. With advanced pattern recognition and anomaly detection, AI reduces human error, ensures data consistency, and helps stabilize performance metrics across workflows.

Finally, AI offers unmatched flexibility and scalability. Systems continuously learn from new data, allowing them to adapt to changing rules and business volumes, while cloud-native deployments make it possible to scale operations seamlessly as demand increases.

Potential Challenges

Despite these benefits, businesses face certain challenges when adopting AI automation. Costs and timelines are among the first hurdles. The discovery phase, data preparation, model training, and integration require significant upfront investment, and success often depends on a phased delivery approach to manage risk.

Data quality is another critical factor. If the available data is incomplete, biased, or siloed, the outcomes will inevitably suffer. Strong governance, robust cleaning pipelines, and continuous monitoring are necessary to maintain reliable results. Ethical and legal considerations must also be addressed.

Organizations need to ensure that their AI solutions operate with transparency, fairness, and respect for privacy, while remaining fully compliant with regulatory standards and internal policies.

Conclusion

AI-driven automation is now a core lever of competitiveness, improving speed, accuracy, and margins while enabling adaptive operations. Start small, pick a high-impact process, validate with a pilot, then scale iteratively with robust data governance and clear ROI checkpoints.

















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AI to Disrupt Stocks, Force Investors to adopt Bitcoin — Analyst

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Bitcoin (BTC) will be a better investment than stocks in the coming decades due to artificial intelligence speeding up innovation cycles, making public companies inefficient investment vehicles, analyst and investor Jordi Visser predicted.

“If the innovation cycle is now sped up to weeks, we are in a video game where your company never hits escape velocity, and in that world, how do you invest? You don’t invest, you trade,” Visser told Anthony Pompliano on Saturday. He also said:

“Bitcoin is a belief. Beliefs last longer than ideas. There are no companies in the S&P 500 from 100 BC; gold has been around since then. Bitcoin will be around for a long, long time. It’s a belief at this point, and people can fight it, but it’s going to be around. 

I think you want to start shorting ideas, and you want to be long beliefs,” Visser continued, adding that AI may compress what normally would have taken 100 years to accomplish in only five years. 

Visser makes his predictions about the future of Bitcoin and the stock market in the AI age. Source: Anthony Pompliano

The prediction sheds light on the potential future of finance and capital structures, as artificial intelligence and blockchain technology disrupt the legacy financial system, driving more value and participants to the digital economy.

Related: Bitcoin faces a fee crisis that threatens network security: Can BTCfi help?

Eric Trump predicts $1M BTC as public companies adopt crypto

Companies continue buying crypto and Bitcoin directly as treasury reserve assets, often rebranding as pure crypto treasury plays and dumping their legacy business models.

These legacy financial vehicles provide equity investors with indirect exposure to BTC and crypto, while siphoning funds from traditional capital markets to digital finance.

Eric Trump predicted Bitcoin would hit $1 million per coin, telling the audience at the Bitcoin Asia 2025 conference in Hong Kong that nation-states, wealthy families, and public companies are all buying BTC.

Bitcoin’s market capitalization is over $2.1 trillion at the time of this writing, with some analysts predicting that it will overtake gold’s market cap over the coming decades.

The digital asset’s cross-border nature and ability to earn yield through deployment in decentralized finance (DeFi) applications give it a competitive advantage over gold as a store of value, some crypto industry executives have argued. 

Magazine: Danger signs for Bitcoin as retail abandons it to institutions: Sky Wee