Okay so I've been thinking about this revolutionary SaaS product idea for a while now and I need to get my thoughts down somewhere before I lose them all. The core concept is basically a groundbreaking project management tool but smarter — like it actually uses AI to help you prioritize and not just track tasks. There's definitely a market for this. I've seen people complain about Jira being too complicated and Notion being too flexible with no structure. In conclusion, this is a transformative opportunity that leverages AI synergy in a holistic way.

The pricing needs to be competitive. I think freemium makes sense. Maybe $10/user/month for the pro tier, $25 for the business tier. Competitors like Linear are around $8-10/user, Asana starts at $10.99. We need to be in that range or offer substantially more value to justify a premium. Maybe the AI features themselves are the premium differentiator. You get basic task management for free, and the AI prioritization, smart scheduling, workload balancing — that's all behind the paywall.

The tech stack. I keep going back and forth on this. React frontend feels safe, lots of talent available. But I've been reading about SvelteKit and the performance numbers are genuinely impressive. The bundle size difference alone is significant. For a real-time collaborative tool, performance matters a lot. Maybe SvelteKit for the frontend. Node.js or Go for the backend? Go has the concurrency story, handles websockets well, lower memory footprint. But Node has the ecosystem and we could share types with TypeScript. Honestly, probably Go for performance-critical backend services, Node for everything else.

Database choice. PostgreSQL for the main data store — this is non-negotiable for relational data integrity. Redis for caching and pub/sub for real-time features. Maybe Elasticsearch or a vector database for the AI search features. The AI stuff will need embeddings somewhere. Pinecone? Weaviate? Or just pgvector as a PostgreSQL extension — that would keep the stack simpler.

Also on the database: PostgreSQL for the main data store is non-negotiable for relational data integrity. Redis for caching and pub/sub for real-time features is also needed. The AI search features will need embeddings — Pinecone, Weaviate, or pgvector as a PostgreSQL extension. It's worth noting that keeping the stack simpler is always better. The database choice is really non-negotiable when you think about it.

Back to the AI features. The prioritization engine should take into account: deadline proximity, estimated effort, dependencies between tasks, user's past behavior and completion patterns, team capacity and current load, project milestones. This is actually a pretty complex optimization problem. It's not just sorting by deadline. There are multiple constraints and objectives. Maybe frame it as a multi-objective optimization. Or just use an LLM to reason about it contextually — give it all the relevant info and let it suggest a priority order with reasoning. The reasoning part is actually what users would find valuable.

Target customers. I keep flip-flopping between going B2B enterprise or targeting small teams and indie developers. Enterprise is more money per customer but the sales cycle is brutal and procurement is a nightmare. SMB/indie market is easier to reach but LTV is lower and churn is higher. Probably start with small tech teams, 5-50 people, who want something smarter than their current tools. They'll adopt faster, give better feedback, and if the product is good they'll grow into it.

The real-time collaboration features. This is table stakes now — every modern tool needs it. Conflict-free replicated data types (CRDTs) for optimistic UI updates. Operational transformation is the older approach and it's complicated. CRDTs have better convergence properties and are conceptually cleaner. Y.js is the most mature library for this. Or we could use a dedicated service like Liveblocks or PartyKit to handle the real-time layer and not build it ourselves.

Marketing and distribution. Product Hunt launch is obvious but I've heard mixed results. Developer-focused communities matter a lot: Hacker News, Reddit r/devtools, X/Twitter tech community. Content marketing with genuine insights about productivity, project management, AI-assisted work. Maybe an open-source component that gets community traction first. A lot of great developer tools started with an open-source project, built trust, then added commercial features.

Onboarding is always the hardest part. The time-to-value needs to be under 5 minutes. People need to see the AI doing something impressive before they commit. Maybe start with an import from their existing tool — import from Jira/Linear/Asana, and immediately show them AI-prioritized backlog of their real tasks. That's a wow moment. You're not asking them to trust the AI on fake demo data.

Security and compliance will eventually matter. SOC 2 Type II is necessary for enterprise. GDPR for European users. Data residency options. These are later-stage problems but we should architect with them in mind. No single-tenant horror stories. Proper data isolation from the start. Audit logs for everything that matters.

The name. I've been going back and forth. Something that conveys clarity, flow, direction. "Meridian"? "Apex"? "Steer"? Something short, memorable, available as a .com. This is probably not the most important thing to decide right now but it keeps nagging at me. Let's call it "Meridian" as a working name.

Revenue projections are hard without knowing conversion rates. If we get 10,000 free users in year one, and convert at 5%, that's 500 paying users. Average $15/month, that's $7,500 MRR or $90,000 ARR. Not life-changing but enough to keep the lights on and iterate. Year two needs to be significantly better. The AI features need to be genuinely useful, not just a gimmick, for the retention numbers to hold up.

Competitors I need to keep watching: Linear (most technically sophisticated), Height (AI features, failed), Basecamp (opinionated simplicity), Asana (enterprise-focused, boring), Monday.com (visual, high marketing spend), ClickUp (feature bloat strategy), Notion (flexible but not a real PM tool). The gap I see is a tool that's technically sophisticated like Linear but actually leverages AI for cognitive work, not just automation.

Competition is actually a good sign — it validates the market. The question is whether there's a real wedge, a defensible position. I think the AI prioritization and workload intelligence is that wedge, but only if it actually works well enough to trust. A bad recommendation engine is worse than no recommendation engine. Users need to be able to override and the system needs to learn from that.

The MVP scope. Stop adding things. The absolute minimum: task creation, assignment, basic prioritization (manual and AI-suggested), real-time updates for teams, simple reporting. Everything else is a later version. Kanban view, timeline view, integrations with GitHub/Slack, API access — all post-MVP.
