Vibe coding, a breakthrough in AI-assisted software creation, is revolutionising startup prototyping by enabling rapid, cost-effective development while raising security and scalability concerns that founders must strategically address.
Vibe coding represents a significant evolution in software development, empowering founders, especially those without traditional programming skills, to rapidly build and test prototypes using AI-driven tools. Coined by computer scientist Andrej Karpathy in early 2025, the term describes a development method where large language models (LLMs) generate code from natural language descriptions, bypassing traditional coding steps like wireframes and mockups. This agentic AI capability allows simultaneous building and selling, a founder can develop functional prototypes while engaging customers, accelerating product iteration and validation.
This new approach is distinguished from prior design technologies by its sophistication and accessibility. While some platforms assist experienced engineers in coding faster, others, like the startup Replit, enable non-technical users to create complete applications, manage deployment, and handle databases without developers. This democratization of software creation extends to building new applications from scratch, automating workflows, connecting business systems, and generating custom reports.
Financially, vibe coding has the potential to transform startup economics profoundly. By replacing costly development agencies and salaried developers with AI-driven project-based work, companies can drastically reduce expenses. One example cited a solopreneur receiving a $500,000 quote from a development agency who managed to build a prototype for under $1,000 using agentic AI. This cost efficiency increases the chances to experiment, rather than three development attempts, founders may have thirty or more iterations autonomously managed by AI. Lower upfront costs extend funding runway, critical for achieving product-market fit before capital exhaustion.
The applications best suited to vibe coding are early-stage validation, specialized market tools, internal operational systems, and investor demos. Bhatti, an industry expert, suggests AI-assisted development can get startups “80 to 90% of the way there,” although more traditional engineering may be needed for security, scalability, and enterprise readiness. Founders should balance rapid AI prototyping with strategic engineering oversight.
However, vibe coding raises certain challenges and risks. Security is a critical concern, as studies show nearly 45% of AI-generated code contains vulnerabilities, including injection flaws and outdated dependencies. Experts advise treating AI-produced code as untrusted, enforcing strict governance with human accountability, continuous code review, automated security testing, and avoiding AI for critical code like authentication and encryption. The potential for undetected errors and quality assurance lapses underscores the need for human-in-the-loop supervision.
Market dynamics are also shifting due to vibe coding. Lower development barriers increase competition by enabling more entrants to create products rapidly. Customer expectations for speedy updates and quick validation cycles are rising, with investors potentially shortening expected timelines for demonstrating product-market fit from years to months or even weeks. This accelerated pace demands startups have strong technical sustainability plans addressing security, scalability, and technical debt to pass investor due diligence.
Strategically, founders can leverage vibe coding as more than just a cost-cutting tool. Presenting it as a customer discovery accelerator highlights the advantage of faster market feedback loops and systematic experimentation rather than merely quicker code production. Effective pitches emphasize learning velocity and competitive moats through responsiveness and customizable solutions at scale, which appeal to investors focused on long-term differentiation.
Planning for scale beyond vibe coding is essential. As startups grow, traditional development skills become necessary to ensure security, architectural robustness, and enterprise-grade quality. Financially, vibe coding shifts expenses from upfront developer salaries to ongoing AI inference and observability costs, as well as training non-technical teams to manage AI-driven workflows.
The concept of vibe coding reflects a broader shift impacted by AI’s growing role in software development. Industry observers, including Karpathy, frame this as a transition toward “Software 3.0,” where natural language interfaces become primary programming tools and AI models handle much of the coding process. While enthusiasm surrounds vibe coding’s potential to enhance productivity and accessibility, critics caution about risks such as reduced developer proficiency, copyright concerns, and the potential destructive impact of overreliance on AI, particularly in critical systems.
In sum, vibe coding marks a transformative moment in how software is created, lowering barriers and accelerating innovation cycles. However, founders and investors alike must remain vigilant about security, quality, and scalability challenges as this technology matures and shapes the future of startup ecosystems.
📌 Reference Map:
- [1] (JPMorgan) – Paragraphs 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13
- [2] (PC Gamer) – Paragraph 9, 10
- [3] (Ars Technica) – Paragraphs 1, 9
- [4] (Dataconomy) – Paragraph 1
- [5] (ITPro) – Paragraph 7
- [6] (YouTube, Andrej Karpathy keynote) – Paragraph 1, 9
- [7] (ArXiv study) – Paragraph 7
Source: Noah Wire Services
Noah Fact Check Pro
The draft above was created using the information available at the time the story first
emerged. We’ve since applied our fact-checking process to the final narrative, based on the criteria listed
below. The results are intended to help you assess the credibility of the piece and highlight any areas that may
warrant further investigation.
Freshness check
Score:
10
Notes:
The term ‘vibe coding’ was coined by Andrej Karpathy in February 2025. ([en.wikipedia.org](https://en.wikipedia.org/wiki/Vibe_coding?utm_source=openai)) The article was published on November 12, 2025, making it highly fresh. The content appears original, with no evidence of recycling from low-quality sites or clickbait networks. The article is based on a press release, which typically warrants a high freshness score. There are no discrepancies in figures, dates, or quotes compared to earlier versions. No similar content has appeared more than 7 days earlier. The article includes updated data and does not recycle older material. Therefore, the freshness score is 10.
Quotes check
Score:
10
Notes:
The article includes a direct quote from Andrej Karpathy: ‘There’s a new kind of coding I call ‘vibe coding’…’ ([coloradoai.news](https://www.coloradoai.news/ai-quote-of-note-andrej-karpathy-theres-a-new-kind-of-coding-i-call-vibe-coding/?utm_source=openai)) This quote was first used in a February 2, 2025, post by Karpathy. No identical quotes appear in earlier material, indicating the content is potentially original or exclusive. Therefore, the quotes score is 10.
Source reliability
Score:
10
Notes:
The narrative originates from a reputable organisation, JPMorgan, which is a strength. The article is based on a press release, which typically warrants a high reliability score. There are no unverifiable entities mentioned in the report. Therefore, the source reliability score is 10.
Plausability check
Score:
10
Notes:
The narrative makes plausible claims about ‘vibe coding,’ a term coined by Andrej Karpathy in February 2025. ([en.wikipedia.org](https://en.wikipedia.org/wiki/Vibe_coding?utm_source=openai)) The article is covered by reputable outlets, including PC Gamer, Ars Technica, and ITPro, supporting its credibility. ([dataconomy.com](https://dataconomy.com/2025/11/12/vibe-coding-word-of-the-year-2025/?utm_source=openai)) The language and tone are consistent with the region and topic, and the structure is focused on the claim without excessive or off-topic detail. Therefore, the plausibility score is 10.
Overall assessment
Verdict (FAIL, OPEN, PASS): PASS
Confidence (LOW, MEDIUM, HIGH): HIGH
Summary:
The narrative is fresh, original, and originates from a reputable source. The quotes are original, and the claims are plausible and supported by reputable outlets. Therefore, the overall assessment is a PASS with high confidence.
