| """Placeholder feedback generators for Phase 1 mock responses.""" | |
| from __future__ import annotations | |
| def generate_improved_answer(weak_answer: str, startup: dict) -> str: | |
| """Return a stronger mock rewrite for a weak founder answer.""" | |
| name = startup.get("name", "the product") | |
| return ( | |
| f"Instead of staying vague, anchor your answer in specifics: " | |
| f"'{name}' solves a concrete discovery problem for students by ranking events against " | |
| f"skills, deadlines, and location — not just aggregating listings. " | |
| f"We already tested ranking logic on scraped campus events and saw students shortlist " | |
| f"3x faster than browsing WhatsApp groups.' " | |
| f"(Your original answer was too thin: \"{weak_answer[:120]}...\")" | |
| if len(weak_answer) > 120 | |
| else ( | |
| f"Lead with proof: '{name}' matches events to student profiles using skills, goals, " | |
| f"and urgency — we validated this with a prototype on real campus event data. " | |
| f"Your answer needed more specificity than: \"{weak_answer}\"" | |
| ) | |
| ) | |
| def generate_improved_pitch(startup: dict) -> str: | |
| """Return a mock 60-second pitch rewrite.""" | |
| name = startup.get("name", "Our startup") | |
| problem = startup.get("problem", "a real student pain point") | |
| solution = startup.get("solution", "a focused product") | |
| why_ai = startup.get("why_ai", "intelligent matching") | |
| traction = startup.get("traction", "early prototype traction") | |
| ask = startup.get("ask", "feedback and support") | |
| return ( | |
| f"{name} helps student founders stop missing the events that actually matter. " | |
| f"The problem is simple: {problem} " | |
| f"Our solution: {solution} " | |
| f"AI is load-bearing because {why_ai} " | |
| f"Traction so far: {traction} " | |
| f"We're asking for {ask}." | |
| ) | |