Group coaches and educators repeatedly rebuild the same infrastructure — scheduling, homework submission, peer feedback, progress tracking — for every cohort they run. Selling the operating system for running a high-quality group program is a B2B belonging play where the coach's students are the end beneficiaries. Coaches stop using it if it adds friction to their existing workflow. Must replace existing tools (Notion + email + Zoom links), not add to them.
Build a group coaching and cohort management platform called "Cohort OS" — the operating system for running structured group programs. Core features: - Program builder: coach sets program name, session count, cadence (weekly/bi-weekly), max participants, price, and start date. Each session has a title, a pre-work assignment, and a post-session reflection prompt - Participant portal: each enrolled participant sees their program timeline, upcoming sessions, submitted assignments, and peer reflections in one dashboard - Assignment submission: participants submit written or link-based assignments before each session. Coach sees all submissions in one view, can leave written feedback per submission - Peer feedback rounds: after each session, participants are prompted to give one piece of structured feedback to one other participant (rotates automatically so everyone gives and receives equally) - Progress tracker: coach dashboard showing assignment completion rate per participant, attendance, and a simple engagement score - Certificate generation: at program completion, auto-generates a PDF certificate with participant name, program name, coach name, and completion date Stack: React, Supabase, Stripe Connect for coach payouts, Resend for session reminders and feedback prompts. Clean, professional design — coach-first UX.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Key sections: PDF Type detection — Vector vs Scanned, different extraction strategy for each Step-by-step workflow — 6 steps from file organization to discrepancy report Visual symbol table — per ELV system (CCTV, FAS, ACS, PA, SC, IPTV, etc.) Best practices — legend-first, one device type at a time, grid method, typical floor check Confidence rating — High / Medium / Low per drawing
