Public Roadmap

Autonomous agent that scans destinations, evaluates place candidates against HipScore criteria, and proposes curated spots for editor approval. Reduces manual curation overhead while maintaining editorial quality.

Responsive layout audit and fixes across all key flows: generation wizard, itinerary view, map, packing list, and sharing. Targeting core iOS Safari and Android Chrome breakpoints.

Elevate packing lists beyond a trip accessory: dedicated creation flow, category management, shareable via link, AI-assisted list generation from a free text prompt (e.g. 'week in Patagonia in October'). Navigation promoted in sidebar.

Recruit 20–30 real users for pre-launch beta. Tier 1: perfect ICP (independent adventurous travelers). Tier 2: adjacent travelers. Tier 3: travel creators/writers. Mix of self-serve (promo code + form) and live Zoom sessions for Tier 1.

Structured feedback collection from beta cohort: feedback form for self-serve users, note-taking template for live sessions. Key questions: output quality, willingness to pay, confusing UX moments, words used to describe the product.

Generate and distribute promo codes for beta testers. Track redemption rates and map codes to feedback submissions for cohort analysis.

Activate the built-in sharing mechanic as a growth loop. Add share prompts at key moments: post-generation, post-unlock. Track referral attribution. Consider a 'give 1 credit, get 1 credit' mechanic.

Authentic community presence in r/solotravel (6M), r/hiking, r/cycling, r/travel, r/digitalnomad. Not promotional — contribute real value (trip reports, answer questions) then introduce HipTrip naturally. Track which communities drive highest-quality signups.

Identify and outreach to 10–15 mid-tier travel/outdoor creators (10K–100K following). Offer early access + custom promo codes. Focus on authentic fit over follower count — creators who actually adventure, not just vacation.

Post-signup email nurture: welcome + product value prop, featured curated trip, tips for getting the best AI output, social proof when available, credit purchase CTA. 5-email sequence over 14 days.

Destination-specific itinerary pages (e.g. '7-day Dolomites hiking itinerary') targeting high-intent queries. Optimize for LLM citation in ChatGPT/Perplexity/Gemini. 20 seed destinations matching best-performing AI output quality.

Pre-built trip templates for popular adventure formats: week in Patagonia, Dolomites Alta Via, Pacific Coast biking, etc. Templates pre-fill the generator and serve as discovery + conversion entry points.

Export trip days as calendar events to Google Calendar or Apple Calendar. Day title, activity names, and location geocoordinates mapped to event fields. OAuth flow for Google; .ics export for Apple.

Search across all user trips, curated trips, and hip places by destination, activity type, or keyword. Powered by Postgres full-text search or lightweight embedding-based similarity.

Improve the current JSON/DOCX export with a print-ready PDF layout: cover page, day headers, activity cards with map pin references, packing list appendix. Printable offline trip guide.

Public-facing roadmap page showing upcoming features with upvote functionality. Drives product transparency, surfaces user priorities, and serves as a low-friction feedback channel for non-beta users.

Playwright E2E coverage for all critical user flows: signup, trip generation, unlocking, packing list, sharing, and editor tools. Integrate into CI/CD pipeline on Vercel deployments.

Automated backup strategy for Aurora DSQL. Define RTO/RPO targets. Implement point-in-time recovery verification. Document runbook for data restoration.

Profile and optimize the two-phase trip generation pipeline. Target: scaffold < 8s, enrichment < 15s. Investigate parallel day enrichment, prompt caching, and streaming chunk optimization.

Allow multiple users to co-plan a trip from the generation phase. Shared preference inputs, voting on activity options, split itinerary sections by day or person. Builds on existing real-time presence infrastructure.

Internal scoring system tracking AI output quality by destination. Identifies where Hip Place injection is sparse, where Google Places validation fails most, and which destinations produce the best user-rated itineraries. Guides editorial investment.