Been experimenting with setups where different AI specialists give independent views rather than one model giving a single answer. The conflict between them is where the insight lives. Curious if others have found this useful or have better approaches.
Will love to share what version 2 i have developed which has helped 50+ founders identify issues before they commit time and money
Been experimenting with setups where different AI specialists give independent views rather than one model giving a single answer. The conflict between them is where the insight lives. Curious if others have found this useful or have better approaches.
Will love to share what version 2 i have developed which has helped 50+ founders identify issues before they commit time and money
Been experimenting with setups where different AI specialists give independent views rather than one model giving a single answer. The conflict between them is where the insight lives. Curious if others have found this useful or have better approaches.
Will love to share what version 2 i have developed which has helped 50+ founders identify issues before they commit time and money
Been experimenting with setups where different AI specialists give independent views rather than one model giving a single answer. The conflict between them is where the insight lives. Curious if others have found this useful or have better approaches.
Will love to share what version 2 i have developed which has helped 50+ founders identify issues before they commit time and money
I’ve been working on a tool where we stress test startup ideas using multiple perspectives (strategy, GTM, finance etc).
After 30+ founders:
Biggest pattern:
People don’t fail because of execution.
They fail because:
- wrong problem
- wrong pricing
- wrong customer
Curious — what’s the biggest mistake you made early?
I’ve been working on a tool where we stress test startup ideas using multiple perspectives (strategy, GTM, finance etc).
After 30+ founders:
Biggest pattern:
People don’t fail because of execution.
They fail because:
- wrong problem
- wrong pricing
- wrong customer
Curious — what’s the biggest mistake you made early?
Do not mention the obvious - Like talk to customers etc as people who are early they do not have the access to time it right. I am curious to know any specific methods that have helped you caught and validate these assumptions early. Especially for D2C market where distribution margins play a pivotal role and change the maths significantly.
Do you talk to any advisors / other experts in the field. Or you use any AI tool to stimulate or do deep research?
Mine: assumed ₹80 MRP was viable for a D2C product going through quick commerce. After 30% QC commission and 18% GST, net realisation was ₹44 against ₹52 COGS. Discovered it 3 months in.
Genuinely curious what others have run into — pricing, channel, customer segment, regulatory
An AI boardroom (40+ specialist agents) to validate startup ideas. In 2 weeks, 347 ideas were scanned. Here's what we learned.
The 5 ideas that failed hardest (score: 0-30/100):
The ideas that scored 70+ (the winners):
- Founder had conviction + understood market: They knew their customer intimately. Not a guess, a reality.
- Unit economics made sense: CAC < LTV, payback < 12 months, margins > 40%.
- Regulatory clarity: They'd talked to a lawyer or an advisor. At least thought it through.
- Market size was real: TAM > ₹500 crores, SAM > ₹50 crores, SOM was achievable in 3 years.
- Execution plan was specific: Not 'grow to 10K users' but 'acquire via Product Hunt (week 1), then sales outreach to 100 B2B targets (month 2).'
What I'm sharing publicly (without doxxing anyone):
The biggest mistake founders make isn't the idea. It's not stress-testing it before they build.
Most founders spend 6 months building, then realize: "Oh, nobody wants this."
A better way: 60 seconds of boardroom stress-test, get a score and action plan, iterate the idea for 1 week, validate again.
By week 4, you've either killed a bad idea (saved 6 months) or pivoted into a good one.
Happy to answer questions and give the tool in the comments.
Hi all,
A non-tech founder with the hep of claude and a lot of experience and exposure trying to solve my own pain point as a founder has built a platform (would not promote my platform yet)
So reaching out to fellow builders to understand how can i get the first 100 users who can try the platform and give feedback / roast my idea (positive, negative, anything).
Built a platform for early stage founders and solo founders avoid costly mistakes and drive better business outcomes by giving them a boardroom of AI specialists that challenge assumptions, debate decisions, and think in parallel before anything is executed.
Unlike ChatGPT, that always echoes a user’s thinking and provides linear answers, 1founder.ai acts like a real decision-making boardroom—where multiple AI specialists challenge assumptions, debate ideas, and stress-test decisions in parallel. It’s powered by real-world success and failure data as proprietary KB, making outputs grounded and actionable.
Genuinely curious what process people use.” I’ve seen founders (including myself) rely on gut + ChatGPT, which tends to agree with whatever framing you give it. Trying to understand what process actually works before committing capital.
Do you guys use AI in research while making any business decisions?
If yes, then how helpful it is in terms of getting the clear clarity so you can make a go/no go decisions?
I am asking as i am building a platform where founders, entrepreneurs can validate their ideas and decisions in much better way where they dont just get information but decision clarity and next steps.
Helped 10+ founders identify the right challenges / risks that helped them wither get their next 20 customers or help them position and challenge their assumptions for growth and scale
Happy to share more, but doing a dipstick to understand what is the core problem faced while making business decisions