AI Trained on Chatgpt (Need VPN): https://chatgpt.com/g/g-693b657930d081919efeef1c716c9fe5-business-and-marketing-consultant-startup-advisor
AI Trained on Google Gemini (Need VPN): https://gemini.google.com/gem/f036c4b2a48d
AI Trained on Gemini at poe.com (No VPN needed): https://poe.com/Business_MarketingAI
AI Trained on Claude at poe.com (No VPN needed): https://poe.com/Business_Startup_AI
The AI is trained on more than 20 thousand pages of text (knowledge from startup gas pedals, business incubators, courses).
The AI is instructed to communicate as a business tracker and business mentor, not to lie, to tell the straightforward, sometimes hurtful truth.
Knowledge base:
Ways to make an MVP,
First sales
Customer Development (conducting problem interviews).
1) Tracking and acceleration as a process
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Track session / weekly sprints format (results – metrics – experiments – plan – risks – commit).
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Startup stage roadmap: Customer Discovery – Sales channel testing – Scaling.
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Managing focus and “doing only what leads to break-even”.
2) Startup Base: what a startup is and why it’s dying
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Definition of a startup (Steve Blank) and emphasis on a scalable business model.
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Typical reasons for failure (market doesn’t need it, ran out of money, team, model, etc.).
3) Idea – grocery vizen – screening
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Product creation process: idea – value proposition/MVP – proof of concept – market launch.
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Product visibility: why you need it, how to form it.
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Idea screening and viability criteria (market research, competitors, trends, etc.).
4) Customer Development / CustDev / Interviews
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Problematic interviews: rules (no selling, no “captain obvious”, listening, past vs future, etc.).
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Approaches from “Ask Mom” (how to talk to customers and not be self-defeating).
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Value interviews (what was “before/after”, what was the benefit/value).
5) Value Proposition and Value Packaging
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“Selling without value = piling on”, value is needed for sustainable sales and price management.
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Value Proposition Canvas (jobs/pains/gains; products/pains/benefit creators).
6) Business model, monetization, unit economics
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Business Model and Business Model Map + Lean Startup + Hypothesis Testing.
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Unit-economics (ARPPU/cost of engagement, etc.), revenue/expense structure.
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Market assessment (TAM/SAM and other elements of market analysis).
7) Hypotheses and experiments (Lean Startup circuit)
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“Idea = hypotheses”, reversals/pivot, validation of assumptions.
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Hypothesis prioritization, quick checks (HADI/sprint logic – as in gas pedals).
8) Funnels, growth metrics and analytics
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North Star / key metric and bundle: action chain – marketing funnel – AARRR – sales funnel.
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Marketing metrics: CPM/CPC/CPA and funnel metrics (reach/CTR/CR/leads, etc.).
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Lead-cost/lead-value and calculation logic (examples).
9) Marketing and engagement channels
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Performance-calculations (budget, reach, CTR, conversions, cost per click, conversion, revenue) + table templates.
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Channels and their comparison (digital/events/telemarketing/referrals/media advertising, etc.).
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Demand/keyword/trends research (Wordstat/Trends, etc.).
10) Sales (especially B2B): process, pipelines, materials
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Tracking sales through pipelines/stages, plan-to-fact and deal management system.
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Sales Kit preparation: one-pager, talking points/scripts, materials to send after the call.
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Traction map: segments×channels×hypotheses, search for bottlenecks.
11) PR for a startup
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Whether PR is necessary, types of media, media vs social media, “how much news costs”, case studies.
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Media practice (including a breakdown of “media about startups”).
12) UX/CX, product cards and design tools
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CJM + deepening tools: Impact Mapping, Empathy Mapping (as “outcome/pain design”).
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UX testing and prototyping tools (platforms and services).
13) Platform models / marketplaces
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Minimal Viable Platform Canvas (two-sided platforms: consumers/producers, hypotheses, tests).
14) Team, roles, hiring, management
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Early stage team roles (finance/product/customers/sales/hiring, etc.).
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Stages of team development (Forming/Storming/Norming/Performing) and company growth.
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Delegation: time value calculation as a trigger to normal delegation.
The technical part of the AI was handled by the IT association
, and the data for the knowledge base was provided by the business association
Logic of AI operation
Base navigator (mind-map)
0) Track session outline and focus control
Artifacts
- Track session template (week summary / metrics / experiments / plan / risks / commit)
- Backlog of hypotheses + HADI (Hypothesis-Action-Data-Insight) board.
- Weekly plan (SMART, owner, deadline)
Metrics
- Commits fulfillment (% of tasks closed)
- Rate of experimentation: # of tests/week
- Time-to-Insight: days from idea to fact
Experiments
- “1 week – 1 bottleneck”: pick a bottleneck, do 3-5 quick tests
- “Kill list”: kill 1-2 activities that don’t affect metrics
1) Problem, Segment, JTBD (CustDev kernel)
Artifacts
- Segment map (ICP: who, where, what they pay for)
- JTBD formulations (situation – motivation – result)
- Problem interview guide + insights table
- Problem/Solution Fit: a list of pains by frequency/strength/money
Metrics
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Interviews/week (target is usually 10-20 at the start)
- Proportion of confirmed pain (≥30-50% recurrence)
- “The power of pain” (score 1-10) + “how much is paid for a solution now”
Experiments
- 10 interviews in one ICP in 5 days
- Smoke test (slogan + “leave a request”) for 1 pain
- “False door” in a product: button/feature – click metering
2) Value proposition and offerer (packaging of meaning)
Artifacts
- Value Proposition Canvas
- One-liner + elevator pitch (1-2 sentences)
- Offer matrix: segment × problem × outcome × price/conditions
- “Before/after” (what measurable gain is given)
Metrics
- Conversion to application (CR of the lending site)
- Reply rate / occurrence in outreach
- Win-rate on offers (commercial – payments)
Experiments
- A/B offfer: 2-3 versions of the result promise
- 20-50 cold contacts with different offerers – compare reply/meeting rate
- “Proof of value”: case study/savings calculator – measuring CR growth
3) Product, MVP, UX/CX
Artifacts
- MVP list: hypothesis – minimal feature – method of verification
- CJM (user path) + list of barriers
- Prototype (Figma/No-code) + UX-test scenarios
- Product requirements lite (1 page)
Metrics
- Activation rate (share of those who reached the “first value”)
- Retention (D1/D7/D30 – by stage)
- Time-to-Value (time to useful result)
Experiments
- 5 UX tests on a prototype (before development)
- Concierge MVP: manually providing “service” – measuring value/willingness to pay
- Feature fake / Wizard-of-Oz: “as if by machine” + manual backing
4) Growth analytics and funnels (AARRR / marketing / product)
Artifacts
- Metrics tree (North Star – drivers – actions)
- Funnel: stages – conversions – causes of decline
- Cohort analysis (by week/month)
Metrics
- North Star Metric (NSM) – 1 main
- CR by stage (visit-lead-meeting-deal, or install-activate-retain)
- Retention / churn, DAU/WAU/MAU (if relevant)
Experiments
- “One Step Overclocking”: improve 1 conversion by 20-30% (copywriting/UX/script)
- “Bottleneck of the week”: picking a minimal CR – 3 tests of improvement
5) Marketing and engagement channels
Artifacts
- Channel Canvas: channel – ICP – offerer – creative – landing – metrics
- Channel test plan (2-3 hypotheses per channel)
- Content plan / PR reasons (if needed)
Metrics
- CPL/CPA/CAC
- CTR, CPC, Landing Conversion
- Payback (when CAC pays off)
Experiments
- 3 channels × 3 creatives × 1 offer – mini sprint for 7 days
- Content experiment: 5 posts/articles – measurement of leads/applications
- Partner test: 3 partners – 10 intros – measurement of meetings/transactions
6) Sales (especially B2B) and Pipeline
Artifacts
- ICP + list of companies/LPR
- Scripts: discovery call / follow-up / objection handling
- Sales kit: one-pager, presentation, KPs, cases
- CRM Pipeline: stages, SLAs, reasons for failures
Metrics
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touches – # responses – # appointments – # CPs – # payments
- Meeting rate, win rate, cycle time (deal length)
- Revenue/week, Pipeline forecast
Experiments
- 50 touches per week on one ICP – reply/meeting measurement
- 10 commercial proposals in one format – win-rate analysis
- Price/packaging test: 2 packages (base/pro) – compare conversion to payment
7) Business Model and Monetization
Artifacts
- Business Model Canvas / Business Model Map
- Price list/packages/restrictions
- Monetization hypotheses (subscription/recurring/usage/commission)
Metrics
- ARPA/ARPU, MRR/ARR (if subscription)
- Gross margin, contribution margin
- LTV (neat) and LTV:CAC
Experiments
- “Solvency test”: prepayment/deposit
- “Packages: 3 tariffs with anchor – choice measurement
- “Usage pricing”: limits/threshold – ARPA and churn metering
8) Unit economics and financial model
Artifacts
- Unit economics template (up to margin and payback level)
- P&L light (income/expense) + cash runway
- Scenarios (pessimist/base/optimist)
Metrics
- CAC, gross margin, payback period
- Burn rate, runway (months to zero)
- ROMI/ROI by channel
Experiments
- “Channel Economics”: Channel 1 – full payback to payback
- “Marginality”: 2-3 cost/process variations – GM growth
9) Market and competitors (evaluation and positioning)
Artifacts
- TAM/SAM/SOM (at least roughly)
- Competitor map + differentiation table
- Positioning: “for whom / why / how we are different”
Metrics
- Size of available demand in ICP (number of companies/LPR)
- Share of “switchers” (who already pay a competitor/resolve manually)
Experiments
- 20 competitive comparisons in interviews (“why not them?”)
- Test of differentiation: 2 positioning – metering of appointments/payments
10) Platforms/marketplaces (if you have 2 sides)
Artifacts
- Platform canvas (producers/consumers/curated rules)
- Matching mechanics + anti-fraud (minimal)
- Chicken-and-egg plan: which side to pump first
Metrics
- Liquidity: proportion of requests that closed (match)
- Time-to-Match
- Retention of both parties
Experiments
- Manual Matching (by operator) – check liquidity
- Subsidize one side – measure the growth of matches
11) PR and public communications (optional, but sometimes boosts)
Artifacts
- PR plan: occasions – media – messages – speakers
- Pitch letter + media kit
- Social proof package: testimonials, logos, numbers
Metrics
- Mentions/transitions/leads from PR
- Trust growth: conversion to meeting/payment after publications
Experiments
- 10 pitches to journalists/channels – response measurement
- 1 strong case study – redesign into 5 content formats
12) Team, processes, delegation
Artifacts
- RACI (who is responsible for what)
- Role description + “what we don’t do”
- Minimum level regulations (CRM, Finuchets, releases)
Metrics
- Time-to-ship, # of releases/week
- % of tasks “hung” due to owner/process
- The cost of an hour of funder (to stop doing nonsense with your hands)
Experiments
- Delegate 1 repetitive operation – metering of released hours
- “Process-detox”: remove 1 approval/step – cycle acceleration
13) Legal & Security (IP & Legal)
Artifacts
- Founder Agreement (shares, vesting, areas of responsibility)
- IP Assignment (code and content assignment contracts)
- Public offer and Privacy Policy
- Regulatory risk register
Metrics
- % of registered intellectual property rights
- LTC (Legal Transaction Cost) – the cost of legal closing of a transaction
Experiments
- “Exit test”: elaboration of a scenario for the exclusion of a funder from the shares
- Offer stress test: check for refunds and liability limits
14) Toolkit and AI Automation (Ops & Stack)
Artifacts
- Architecture Map (stack of services: CRM, No-code, databases)
- AI-Implementation Map (processes delegated to neural networks)
- Dashboard of key indicators (Notion / Data Studio)
Metrics
- Automation Rate (% of processes without human intervention)
- OpEx (IT infrastructure costs per customer)
Experiments
- “AI collaborator”: replacing one function (support/content) with AI in 48 hours
- Automate 1 bottleneck in the funnel via Make/Zapier
15) Fundraising and Investments (Fundraising)
Artifacts
- Pitch Deck (10-12 slides per VC standard)
- Investor Pipeline (database of funds and angels with touch history)
- Financial Model (18-36 months forecast + scenarios)
- Data Room (full package of documents for Due Diligence)
Metrics
- Conversion Rate: from cold pitch to meeting with an investor
- Burn Multiple (burn efficiency relative to growth)
Experiments
- “The 10 Angels Test”: sending out pitches to a narrow sample to collect a hard OS
- Checking an investment offer on LinkedIn (interest measurement through outreach)
16) Scaling and systematization (Scaling)
Artifacts
- Company Playbook (knowledge base and regulations for scaling)
- Sales Playbook (closing instructions for new managers)
- Hiring plan (HR-roadmap for revenue goals)
Metrics
- LTV / CAC Ratio (target > 3)
- Payback Period (payback period of the attracted customer)
Experiments
- “Stress test x10”: analyzing bottle necks at ten times the load increase
- Hiring an assistant/leadgen for one process to check delegation
