AI advisor for solo founders of expert businesses
Challenge: Solo consultants, agencies, and service founders need real business advice, but generic AI chatbots give theoretical answers disconnected from their actual situation. Reading four different business books (positioning, pricing, selling, decision-making) leaves them with conflicting voices and no way to apply the wisdom to their specific week.
Solution: Mentor compiles multiple expert sources into a single unified-voice wiki and grounds every reply in the user's real schedule, priorities, and progress. It uses Claude Haiku 4.5 with strict output rules — maximum two short paragraphs, direct language, candid but encouraging — to deliver advice that feels like a trusted advisor, not a search engine.
Five topic articles — positioning, selling, pricing, business model, decision-making — compiled from multiple expert sources into one synthesized voice. Browse or click any topic to read the full framework.
One random teachable chunk from the wiki on each click. A bite-sized idea to absorb at the start of the day, no commitment required.
Ask any business question. Retrieval finds the top 3 relevant wiki chunks, Claude Haiku generates a grounded answer in ≤2 short paragraphs, and sources are shown so you know where the advice came from.
Always-on access to the user's weekly schedule, priority order, and latest progress log — loaded into every chat request so advice is never generic.
Fast, low-cost LLM that generates concise grounded replies. Roughly one sen per question in production — cheap enough for daily use without cost anxiety.
Every question is tokenized and scored against all wiki chunks. The top three are sent to the LLM as context, keeping token usage low and answers focused.
The system prompt enforces maximum 2 paragraphs of 3 sentences each, unified voice, candid tone, and honest gap-flagging. No theoretical advice without reality grounding.
Layer 1 is always-on context: user profile, schedule, priorities, progress. Layer 2 is retrieved wiki chunks per question. Both are sent with every request to ensure advice matches both reality and frameworks.