Customer discovery
Tailored hypotheses + questions
Generates a run-specific discovery kit (hypotheses, screening, interview questions) from the MVB packet.
Loaded from run #14
An AI-based therapist tailored for entrepreneurs provides confidential, on-demand “founder therapy” conversations grounded in startup realities. It aims to help founders manage stress, loneliness, decision fatigue, and identity challenges to improve emotional regulation and decision-making.
Founders experience persistent, high-stakes psychological strain (stress, isolation, decision fatigue, identity and leadership pressure) and often lack accessible, affordable, founder-relevant mental health support that fits their schedules and feels safe and confidential.
Generate discovery kit
This uses the OpenAI model configured on the server. Run-specific generation is recommended.
Ready to generate a tailored kit from this run.
Hypotheses
These are the explicit assumptions we’re testing in interviews.
H1: Seed–Series A venture-backed SaaS founders experience weekly (or more frequent) stress/loneliness/decision-fatigue episodes that they believe materially degrade decision quality and leadership behavior, and they lack a founder-relevant, confidential outlet that fits their schedule.
problemcriticalIf the pain is not frequent, severe, and tied to outcomes founders care about, they will not adopt or pay, and distribution via VC/accelerators will not convert.
Success signals
- >=70% report at least weekly high-stress or loneliness episodes tied to fundraising/runway/board dynamics
- >=50% can cite a recent decision or interpersonal incident they attribute to emotional dysregulation/decision fatigue
- >=60% say current options are too slow, too expensive, not founder-contextual, or not confidential enough
- >=40% say they would try an on-demand alternative within the next month if it felt safe
Failure signals
- <40% report frequent episodes (weekly+) or they describe the impact as minor
- Most say existing therapy/coaching/peer groups already meet the need
- Founders frame the issue as purely operational (no interest in emotional support)
- Low urgency: most say 'maybe later' with no near-term trigger
How to test
Run 15–25 problem interviews with the beachhead ICP; quantify frequency/severity (e.g., episodes/week), triggers (fundraising/runway/board/cofounder), and current coping methods; ask for concrete recent examples and what it cost them (sleep, conflict, missed work, bad decisions).
H2: The beachhead ICP (US venture-backed seed–Series A SaaS founders in accelerators/VC platforms) is willing to use an AI system for emotionally sensitive conversations if privacy/confidentiality and safety boundaries are explicit and credible.
customercriticalIf founders won’t disclose honestly to an AI due to trust concerns, the product won’t deliver value and retention will fail regardless of features.
Success signals
- >=60% say they would use it for real issues (not just 'light' wellness) if privacy claims are credible
- >=50% are willing to share sensitive context (runway, investor conflict, shame/fear) during a guided role-play
- Top objections are addressable (e.g., data retention, who can see transcripts) rather than categorical 'no AI for this'
- Founders can articulate specific trust requirements (e.g., no human review, deletion controls) that can be built
Failure signals
- >=50% refuse to discuss sensitive topics with AI under any conditions
- Primary objection is irreducible (e.g., 'must be human' for emotional safety)
- Founders assume data will leak to investors/employers and won’t be convinced by safeguards
- Role-play usage feels performative; they won’t engage with real details
How to test
Conduct 10–15 concept tests with a clickable prototype and a clear privacy/safety one-pager; ask founders to role-play a real scenario (e.g., board pressure, cofounder conflict) and rate comfort, trust, and likelihood to use; capture objections and required assurances.
H3: Founder-specific tailoring (startup-context prompts, playbooks, and language around runway, fundraising, board dynamics, cofounder conflict) produces meaningfully higher perceived usefulness and repeat usage than a generic mental health chatbot or journaling.
solutionhighDifferentiation and retention depend on being 'founder-native'; without clear advantage, generic tools and human therapy dominate.
Success signals
- >=70% prefer founder-tailored experience and describe it as 'more relevant' with specific examples
- >=40% say they would switch from their current tool to this primarily because it understands startup context
- In a 7-day pilot, founder-tailored mode accounts for >=65% of sessions
- Users report at least one actionable takeaway (script, reframe, plan) tied to a startup scenario
Failure signals
- No clear preference between generic and founder-tailored experiences
- Founders say the startup context is 'nice to have' but not a reason to adopt
- Pilot usage is low or evenly split; no repeat sessions
- Feedback indicates the tool feels like generic CBT with startup buzzwords
How to test
A/B concept test: show founders two short demo transcripts (generic vs founder-tailored) and a 5-minute guided interaction; measure preference, perceived relevance, and intent to reuse; follow with a 7-day pilot where users can choose modes and track which they return to.
H4: Asynchronous, on-demand conversations (5–15 minutes) fit founder schedules and can deliver measurable short-term relief and improved clarity without requiring a long-term human relationship.
workflowhighIf founders need synchronous human rapport to benefit, the product’s core delivery model and unit economics break.
Success signals
- Median session length 5–15 minutes and >=50% complete 3+ sessions in 14 days
- Average self-reported stress decreases by >=2 points immediately post-session for >=50% of sessions
- >=60% report improved clarity/next-step confidence after sessions
- Users cite 'available when I need it' as a top-2 reason to continue
Failure signals
- Low repeat usage (e.g., <30% do 3+ sessions) despite initial interest
- Founders demand live human interaction as the main missing element
- No consistent pre/post improvement in stress/clarity ratings
- Sessions drift into long, time-consuming interactions founders avoid
How to test
Run a 14-day concierge MVP with daily check-ins and on-demand sessions; measure session length, time-to-first-response expectations, repeat rate, and pre/post self-ratings (stress 1–10, clarity 1–10) after each session; conduct exit interviews.
H5: A meaningful portion of the beachhead ICP will pay $29–59/month for individual access, and VC/accelerator programs will sponsor an enterprise plan ($8–20/user/month annual + platform fee) if outcomes can be reported in aggregate without exposing individual data.
pricinghighWithout willingness to pay or sponsor, the product cannot sustain acquisition costs, safety/compliance investment, or defensible growth.
Success signals
- >=30% of founders indicate willingness to pay within $29–59/month and pass a fake-door paywall click-through >=8–12%
- >=3 B2B buyers (VC/accelerator) agree to a paid pilot or sign an LOI contingent on basic safety/privacy requirements
- Founders compare price favorably to therapy/coaching time cost and say it’s 'worth it for runway stress'
- B2B buyers accept aggregate reporting and do not require individual transcript access
Failure signals
- Most founders anchor to free or <$10/month and reject $29–59 as unjustified
- B2B buyers insist on individual-level visibility that breaks confidentiality expectations
- Fake-door conversion is very low (<3–5%) even with strong messaging
- Buyers view it as a 'perk' with no budget owner or procurement path
How to test
Run pricing interviews using Van Westendorp + direct 'would you pay' questions; test checkout intent with a fake-door paywall; for B2B, interview 10 VC platform/accelerator operators with a one-page ROI/outcomes dashboard mock (aggregate only) and ask for pilot LOIs.
H6: Distribution through accelerators, VC platform teams, and founder communities can generate efficient acquisition (low CAC) because the problem is common, time-sensitive, and aligned with portfolio support mandates.
channelmediumFounder-by-founder outbound is expensive; channel leverage is needed to reach enough founders quickly and credibly.
Success signals
- Partner campaigns achieve >=10% opt-in from reached founders and >=40% activation among opt-ins
- At least 2 partners offer to repeat the program or expand to more cohorts/portfolio companies
- Founders cite partner endorsement as increasing trust and willingness to try
- CAC via channel is materially lower than direct outreach (e.g., >50% lower)
Failure signals
- Partners are reluctant due to liability/reputation concerns
- Opt-in is low (<3–5%) even with strong partner endorsement
- Activation/retention is weak, suggesting channel reach doesn’t translate to usage
- Partners require heavy customization or long sales cycles incompatible with early-stage iteration
How to test
Recruit 5–10 channel partners for a co-branded pilot; measure opt-in rate from partner emails/Slack posts, activation (first session), and 30-day retention; compare to direct-to-founder outreach benchmarks.
Screening questions
Use these to qualify people before scheduling a call.
Which best describes your current role?
Qualifies if: Select one of the Founder/Co-Founder options.
What stage and company size best matches your startup today?
Qualifies if: Seed or Series A AND 1–50 employees AND venture-backed.
In the last 30 days, did you have a moment where founder stress, loneliness, or decision fatigue noticeably affected your work or sleep?
Qualifies if: Answer is Yes within the last 7 days or Yes within the last 30 days.
Which of these situations have you personally dealt with in the last 60 days? (Select all that apply)
Qualifies if: Select at least one option other than 'None of the above'.
Have you used any of the following in the last 6 months to manage stress or mental health? (Select all that apply)
Qualifies if: Any selection is acceptable; used to segment, not exclude.
Interview plan
20 minutes. Start with a real recent incident. Avoid hypotheticals.
Outline
20 minutes
- 0–2 min — Warm-up: role, context, “good” looks like
- 2–10 min — Last time it happened: story + steps
- 10–15 min — Tools + alternatives + what broke
- 15–19 min — Value: impact, willingness to pay, buyer process
- 19–20 min — Close: referrals + follow-up
Q1: Think about the most recent time in the last 30 days when founder stress or decision fatigue spiked. What happened, and what was the specific trigger?
Anchors the interview in a real, recent incident and reveals the highest-intensity moments where support might be valuable.
H1
Follow-ups
- What day/time was it, and what was happening right before the spike?
- What was at stake (runway, board, customers, team, fundraising)?
- How did you notice it in your body or behavior (sleep, irritability, avoidance, overworking)?
Q2: In that incident, what did you do in the first 60 minutes after you realized you were struggling?
Identifies current coping behaviors and whether on-demand, asynchronous support could fit naturally into their workflow.
H4H1
Follow-ups
- Did you talk to anyone (cofounder, partner, investor, friend), or keep it to yourself? Why?
- Did you search for resources, journal, use an app, or just push through?
- What did you wish you had in that moment that you didn’t?
Q3: Walk me through the next decision you had to make while you were in that stressed state. What options did you consider, and how did your mental state affect the choice?
Tests whether emotional regulation support could improve decision-making quality and reduce costly founder errors.
H1H6
Follow-ups
- What would you have done differently if you felt calmer or clearer?
- Did you delay, avoid, or overcorrect? What was the outcome 24–72 hours later?
- Who else was impacted by that decision (team, customers, cofounder)?
Q4: During that same week, was there a moment you felt you couldn’t share what you were thinking with your team, cofounder, or investors? Tell me about the most recent one.
Validates loneliness/confidentiality needs and the demand for a safe outlet that feels founder-appropriate.
H1
Follow-ups
- What specifically made it feel unsafe to share (reputation, leverage, morale, board dynamics)?
- Who would have been the ideal person to talk to, and why wasn’t that available?
- What was the cost of holding it in (sleep, focus, relationships, performance)?
Q5: In the last month, what’s the most recent time you tried a tool or person for support (therapist, coach, app, journaling, friend)? What did you use and what happened?
Maps the competitive set and reveals gaps in accessibility, relevance, and effectiveness versus current alternatives.
H6H3
Follow-ups
- How long did it take from deciding you needed help to actually getting it?
- What part felt most helpful, and what felt missing or annoying?
- If you stopped using it, what caused you to drop off?
Q6: Tell me about the last time you considered therapy or coaching but didn’t book it (or postponed). What got in the way that day?
Surfaces practical barriers (time, scheduling, cost) and emotional barriers (stigma, trust) that an on-demand product must overcome.
H1H2
Follow-ups
- Was it mainly scheduling, cost, finding the right person, or privacy concerns?
- What would have made you take action in that moment?
- How often does this “I should talk to someone” moment happen in a typical month?
Q7: Imagine that same incident again. If an AI ‘founder therapist’ were available instantly, what would you have wanted it to do in the first 10 minutes?
Tests willingness to use AI for emotionally sensitive conversations and clarifies the expected job-to-be-done and success criteria.
H2H4
Follow-ups
- Would you want it to listen/reflect, give a plan, challenge your thinking, or help draft a message to someone?
- What would make it feel founder-native versus generic mental health advice?
- What would make you stop using it immediately (a red flag response)?
Q8: Thinking about that incident, what privacy or safety guarantees would you need before you’d share the real details with an AI system?
Validates trust requirements and guardrails needed to avoid unacceptable risk and meet founder expectations.
H2H1
Follow-ups
- What data would be absolutely off-limits (company name, investor names, financials, personal identity)?
- How would you want crisis situations handled (self-harm language, panic, substance use)?
- What would you need to believe about data retention, training usage, and access controls?
Q9: If this had helped you in that incident, how would you expect to pay for it, and what would you consider a reasonable monthly price?
Tests willingness to pay and who the buyer is (founder vs company/VC program), supporting sustainable unit economics.
H4H1
Follow-ups
- Would you expense it through the company, pay personally, or want it sponsored by an accelerator/VC?
- What would you need to see to justify $29–$59/month personally?
- What would make you comfortable recommending it to other founders in your network?
Scripts + templates
These should match the specific hypotheses above.
Intro script
I’m doing customer discovery with seed–Series A SaaS founders on founder stress, decision fatigue, and what support actually fits the job. Not selling therapy—just learning. If you’re open, I’d love 20 minutes to understand what spikes stress for you (fundraising/runway/board/cofounder stuff), what you’ve tried, and what “confidential + on-demand” support would need to look like to be useful. Everything is off the record; I won’t ask for sensitive company details. Would you be open to a quick chat this week?
Recruit email
Subject: Quick research chat on founder stress + decision fatigue (20 min)
Hi {{FirstName}},
I’m interviewing seed–Series A SaaS founders about the psychological load of building (fundraising/runway pressure, board dynamics, cofounder conflict, decision fatigue) and what support actually works with a founder schedule.
This is research—not a sales pitch. I’m trying to understand:
- What situations create the biggest stress spikes
- What you’ve tried (therapy/coaching/apps/peer groups) and what’s missing
- What “confidential, on-demand” support would need to look like to be genuinely useful
If you’re open to it, could we do a 20-minute call this week or next? I won’t ask for sensitive company metrics, and anything you share stays confidential.
A few times that work for me:
- {{TimeOption1}}
- {{TimeOption2}}
- {{TimeOption3}}
Thanks,
{{YourName}}
{{Role/Org}}
{{CalendarLink}}LinkedIn DM
Hey {{FirstName}} — I’m doing quick research interviews with seed–Series A SaaS founders on founder stress/decision fatigue (fundraising, runway, board pressure, cofounder dynamics). Not selling anything—just learning what support actually fits a founder schedule and feels truly confidential. Open to a 20-min chat? If yes, I can send a few times.Call notes template
CALL: Founder Therapy (AI) Discovery 1) Basics - Name / Role: - Company stage (seed/Series A) + team size: - Current context (fundraising, runway, major launch, board cycle): 2) Stress & Trigger Map - Biggest stressors in last 30 days: - Most common “spike moments” (before/after what events?): - Frequency (daily/weekly) + intensity (1–10): - What does it impact? (sleep, focus, relationships, leadership behavior): 3) Current Coping & Support Stack - What do you do today when it spikes? - What have you tried? (therapy, coaching, peer groups, apps, journaling): - What works / doesn’t work (founder relevance, scheduling, cost, trust): 4) Confidentiality, Trust, and Risk - What would make a support tool feel unsafe? - Privacy expectations (data retention, training on data, employer/VC access): - Comfort with AI for sensitive conversations (1–10) + why: - Safety expectations (crisis detection, escalation, disclaimers): 5) Concept Reaction (describe in 20 seconds) - “Imagine an on-demand, confidential AI ‘founder therapist’ trained on startup realities—runway, board dynamics, pivots, cofounder conflict—with strong guardrails.” - Initial reaction (top 3 thoughts): - Where would it help most? (specific moments): - Where would it fail / feel wrong? 6) Feature & Experience Requirements - Must-have behaviors (tone, directness, frameworks, action plans): - Personalization needs (role, stage, personality, values): - Preferred modality (chat/voice), session length, async vs live: - Red lines (what it should never do): 7) Willingness to Pay / Buying Path - Would you pay personally? Price sensitivity ($29–59/mo): - Would you expense it? Under what category? - Would your company/VC/accelerator sponsor it? Who decides? - What ROI would justify it? (burnout reduction, decision clarity, retention): 8) Validation & Next Steps - If we offered a 2-week pilot, would you try it? Why/why not? - What would success look like after 2 weeks? - Any peers you’d recommend I speak with? 9) Scorecard (0–3 each) - ICP Fit & Urgency: - Problem Severity & Frequency: - Alternatives & Dissatisfaction: - Trust/Privacy Acceptance: - Willingness to Pay / Buyer Path: - Usage Fit (On-demand/Async): - Outcome Measurability: - Total (0–21): - Decision (Priority / Screen / Survey / No): Key Quotes: - Risks/Objections: - Follow-ups / Commitments: -