Thread by @vasumanmoza

How to do AI Product-Idea Validation in < 2 Hours:

You have either zero AI product ideas or a hundred of them, and somehow both situations leave you building nothing. While you're stuck in analysis paralysis, someone else just launched a basic AI agent that's making $50K MRR.

Here's how to find and validate AI ideas in a few hours before writing code:

2/ Problem Mining from Real Pain Points

Start where people are already spending money to solve problems manually. I scan three places: enterprise software feature request forums, freelancer job boards, and Reddit communities where business owners complain about repetitive tasks. The key is finding problems people currently pay humans $50-$500+ per hour to handle.

Copy-paste this prompt to find validated problems:
"I need you to analyze [specific industry/role] and identify the top 5 repetitive tasks that currently require human expertise but could potentially be automated. For each task, tell me:
1) Average hourly cost to hire someone for this
2) How often businesses need this done
3) What tools they currently use
4) Why existing automation fails. Focus on tasks where people spend $1000+ monthly."

This approach led me to discover, for example, that marketing agencies spend $5k-10k monthly on manual competitive analysis that takes 40+ hours per week.

3/ Revenue Validation Before Building

Skip the typical validation advice about surveys and interviews. Instead, sell the solution before it exists. The best builders create a simple landing page describing the AI agent's output and set up a Calendly link. Then they get scrappy: post short-form videos showing the problem, DM business owners who complain about this issue online, and share the solution in relevant Reddit threads. The key takeaway here: act like you’ve already built it. If you can't get at least 5 people to book calls wanting to pay for the solution within one week, the idea dies.

Use this landing page prompt:
"Create compelling copy for an AI solution that [specific problem you identified]. The audience is [specific business role] who currently [current manual process] and spends [current cost/time]. Structure it as: Problem statement that makes them nod, solution explanation without technical details, specific outcome they'll achieve, and strong CTA for a strategy call. Include social proof placeholder and address the main objection: 'this sounds too good to be true.'"

When I helped a founder test an AI agent for restaurant inventory management this way: 12 restaurant owners booked calls in 4 days. He turned that into a $30K MRR product.

4/ Technical Feasibility Check

Before those calls, verify you can actually deliver the promised outcome. I spend 2-4 hours building a minimal proof of concept using existing AI APIs. Not a full product, just enough to prove the core function works. If I can't demonstrate the key capability in 4 hours with current AI tools, I consider pivoting...

Here's my technical validation prompt:
"I need to validate whether current AI can handle [specific task from your problem research]. Break this down into:
1) What data inputs are required
2) What processing steps are needed
3) What existing AI models/APIs could handle each step
4) What's the estimated accuracy rate
5) What are the failure modes
6) How would you measure success?
Then give me the simplest possible implementation approach using existing tools like OpenAI API, Anthropic, or specialized APIs."

This saves months of building something technically impossible or unreliable.

5/ Market Size Reality Check

Finally, calculate if there are enough potential customers to build a real business. I use a simple framework: identify the total addressable market, estimate conversion rates based on your validation calls, and multiply by realistic pricing. If a very conservative (that means pessimistic) math breakdown doesn't show a path to $100K annual recurring revenue within 12 months, I move to the next idea.

This exact validation process led to a friend of mine’s most successful AI agent - it took no more than 2 total hours and saved him from building products that would fail.

6/ Level up in the AI game:

If you're an AI builder who wants more workflows like this that actually work, join my weekly newsletter at varickagents.com/newsletter. Every week I share the exact processes and tools that are making builders more efficient in using AI, whether that be for building or for making money.

If you run a business and want to cut operational costs by 80% while getting 10x faster results with better accuracy, book a strategy call at varickagents.com. I'll show you exactly how AI can transform your operations and bring you into the AI age