The accuracy and dependability of AI-generated prompts are more crucial than ever in the quickly developing field of artificial intelligence today. PromptScore, founded by Ben Cedeno, is pioneering a revolutionary approach to restore trust in the AI prompt marketplace by using AI itself to validate and score prompts for accuracy, relevance, and usability. This innovation is establishing new benchmarks that could revolutionize how people and companies interact with the AI-driven world.

Business Now got in touch with Ben Cedeno to find out more about the project’s beginnings, the difficulties in developing the Cedeno Stack, and PromptScore’s goal of becoming the “Verisign for AI” in a market that is changing quickly.

BN: What inspired you to create PromptScore, and how did you identify the trust gap in the AI prompt marketplace?

Ben Cedeno: I started building PromptScore in June 2025 because I was frustrated. The AI prompt marketplace was completely broken – thousands of creators selling “miracle prompts” with zero validation, no quality standards, and no accountability. As both a buyer who’d been burned and a creator who believed in quality, I knew there had to be a better way.

The trust gap was obvious: people were spending real money on prompts that might be complete garbage. There was no Yelp for prompts, no Consumer Reports, no quality assurance. In a $170 billion AI market, nobody had solved the most basic problem – how do you know if a prompt actually works?

My insight was simple but revolutionary: use AI to validate AI. I built an enterprise-grade validation system using Gemini 2.0 that scores every prompt from 0-100 based on accuracy, relevance, actionability, completeness, and reliability. Only prompts scoring 80+ get the PromptScore seal of approval. We became the industry’s first quality standard.

In simple terms, how would you explain the value of PromptScore to someone who has never used AI prompts before?

Imagine buying a recipe online, but you have no idea if it actually makes good food, if the ingredients are right, or if anyone’s ever successfully cooked it. That’s the current AI prompt marketplace.

PromptScore is like having a master chef taste-test every recipe before you buy it. We take any AI prompt – whether it’s for writing emails, analyzing data, or creating content – and give it a quality score from 0 to 100. We check: Does it actually work? Will it give you accurate information? Can you actually use the results? Is it worth your money?

If a prompt scores below 80, we won’t let it on our platform. It’s that simple. You get guaranteed quality, sellers get credibility, and the entire AI industry gets the trust infrastructure it desperately needs.

What were the biggest challenges you faced while developing the Cedeno Stack, and how did you overcome them?

The biggest challenge was that I was building five revolutionary products simultaneously while talking to what felt like a void. Zero users, zero revenue, zero validation that anyone would care. Just me, alone, building infrastructure for a future I could see but couldn’t prove.

The technical challenge was immense – I built what normally takes teams 6 months in just 2 weeks. Eight interconnected Notion databases, enterprise-grade validation systems, and comprehensive pricing algorithms. As a senior security engineer, I had the technical skills, but the scope was staggering.

The breakthrough came from systematic documentation. I documented everything – every decision, every pivot, every insight. This accidentally led to discovering the Multidimensional Memory System (MMS), which transformed my productivity 10x. What started as a coping mechanism for complexity became the core innovation.

The real challenge was psychological. Building in isolation, no immediate feedback, burning through savings. I overcame it by trusting the pattern recognition that got me here and building as if millions were already using it. From void to victory in 30 days – $7M in IP value, 17,000+ audience, and five integrated protocols that work together seamlessly.

How do you envision PromptScore impacting industries outside of AI, such as healthcare or education?

PromptScore isn’t just about AI prompts – it’s about trust in the age of AI. Every industry will need quality assurance for AI-generated content and decisions.

In healthcare, imagine doctors using AI for diagnosis assistance. How do they know the AI’s recommendation is reliable? PromptScore’s validation framework could score medical AI outputs for accuracy, safety, and compliance. A doctor sees “PromptScore: 95/100” and knows they can trust this AI-assisted diagnosis.

In education, teachers are already using AI to create lesson plans and assessments. But how do they know the content is age-appropriate, factually correct, and pedagogically sound? PromptScore becomes the quality control layer – only lesson plans scoring 85+ get approved for classroom use.

The real vision is bigger: we’re building the trust infrastructure for the AI age. Any industry where AI touches human decisions – finance, law, engineering, research – needs our validation layer. We’re not just scoring prompts; we’re ensuring AI serves humanity safely and effectively.

What’s your long-term vision for the company, and how do you plan to maintain your competitive edge as the market grows?

My vision is for PromptScore to become the universal trust layer for AI – the “Verisign for AI” that validates every critical AI interaction. Within 5 years, seeing “PromptScore Validated” will be as essential as seeing “https” in your browser.

We’re not just building a product; we’re creating a category. The Cedeno Stack – PromptScore, MMS Framework, Delta-State Protocol, Bridge Commands, and Trinity System – represents the first complete operating system for human-AI collaboration. It’s infrastructure-as-code for AI, like Terraform revolutionized cloud computing.

Our competitive edge is unassailable because we’re 18-24 months ahead and accelerating. While others might copy surface features, they can’t replicate:

• The integrated ecosystem where each component amplifies the others
• The documented patterns from thousands of hours of R&D
• The patent portfolio we’re filing across all five innovations
• Most importantly, the philosophical depth – we’re not optimizing for engagement metrics but for human cognitive evolution

The plan is aggressive but achievable: bootstrap to $10-25K MRR, then strategic funding to scale. We’re targeting AI-native startups first, then enterprises, then government contracts. The $499 billion infrastructure opportunity is ours to capture because we’re the only ones who’ve built the complete solution.

From zero to industry standard in 5 years. That’s not optimism – that’s pattern recognition.

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