AI startup mentor for founders going from idea to first paying customers

Most founder interviews fail for one reason: the founder pitches, and the other person is polite. Theo prepares each interview with you using Mom Test rules. Ask about the last time the problem happened, not whether they would use your product. Ask what they have already tried and what it cost. Leave every conversation with a commitment, such as an introduction, a second meeting or a deposit.

After the call you paste your notes. He separates facts from opinions and hypotheticals, flags every compliment you may have mistaken for a signal, and tells you which assumption the interview supported, weakened or did not touch. Over a month this builds into an evidence log you can reread before any big decision.

• Before the interview. Three questions about past behaviour and one ask for a concrete next step.
• After the interview. A scored summary of facts, pains, current spending and commitment level.
• Across interviews. A pattern view showing which pain repeats and which segment feels it most.

Theo works through the numbers with you in plain arithmetic. Take an example: a B2B tool priced at 120 USD a month with 80 percent gross margin brings 96 USD of gross profit per customer each month. If you expect customers to stay about 20 months, lifetime gross profit is roughly 1,920 USD. If paid acquisition costs 600 USD per customer, payback takes just over six months and the ratio of lifetime value to acquisition cost is about 3.2. Those are example figures, and your own inputs replace them in the first session.

When one input is a guess, he labels it as a guess and turns it into a task. A churn rate copied from a blog post becomes "measure retention of the first pilots after 60 days". This keeps the model honest and tells you which experiment matters most this month.

Upload a deck as a PDF and Theo comments slide by slide against a fundraising rubric. He checks whether the problem slide names a specific buyer, whether traction is real and verifiable, whether the market size is built bottom up from customers and price, whether the business model matches your unit economics, and whether the ask states an amount, a runway and the milestones that money buys.

Each review ends with a score per rubric line and the two edits that would most improve the deck. The Personal plan includes 10 reviews a month with files up to 10 MB, about 20 pages, which covers most decks. Pro includes 30 reviews and files up to 25 MB. A review counts the moment it runs, so deleting the file later does not hand the review back.

When you decide to raise, Theo treats investors the way a good salesperson treats prospects. You list target funds and angels with stage, cheque size and fit, and he helps you sort them into tiers, plan warm introductions and track each conversation from first meeting to term sheet. Weekly tasks become concrete: send six introduction requests, follow up with three partners who asked for data, prepare the answer to the question that came up twice.

He does not promise funding, introduce you to investors or give legal or financial advice. For term sheets, equity and tax questions you still need a qualified lawyer or accountant. What he gives you is structure, preparation and a record of what you learned from every meeting.

Theo suits solo founders and small teams from idea stage to seed, side-project builders who want to know whether to go full time, and operators inside a company testing a new product line. Founders who also need help with demand often pair him with Iris, the AI marketing mentor, and founders who do the selling themselves add Maya, the AI sales coach. On Personal you choose two mentors, on Pro you get all nine.

He is a fictional AI persona built on published startup methods, not a person with an exit behind him. If you want warm investor introductions from a human with a network, an accelerator or angel group does that better. If you want someone to hold your week together and challenge weak evidence at any hour, Theo does that.