The Backstory Transitioning to software engineering was lonely. I avoided seeking mentorship and wasted time guessing my path because I hated the awkwardness of asking strangers for help. I’m building Vector to solve this: providing expert guidance for those who want to grow without the social friction.
What is Vector? It is an AI-driven career planning platform for people switching industries, changing roles, or aiming for a promotion. But rather than just a chatbot, I am focusing on the execution loop.
How I’m differentiating from "Just another wrapper" I know the "AI Wrapper" fatigue is real. Here is how I’m engineering around it:
Verified Data (No Hallucinations): Instead of letting the LLM guess career paths, I am currently prompting it to strictly refer to O*NET (US Dept of Labor) and ESCO (EU) standards. My next step is building a data ingestion pipeline to ground the model directly in these databases to force market-accurate roadmaps.
The "Radar" Engine: Most AI tools are passive. I’m building a background system that scans industry news (via RSS/Search APIs) and filters it based on your profile. It stays silent for the noise and only notifies you about the 1% of updates that actually impact your specific roadmap.
The Feedback Loop: If you struggle with a roadmap phase, the system dynamically adjusts future timelines, mimicking a real human coach.
Where I need your help I’m currently in the MVP phase and would love the community's take on a few things:
Trust: As builders, would you trust an AI to guide your career path if you knew it was grounded in O*NET data, or is the "human touch" non-negotiable?
The Business Model: Is this a tool you’d pay a subscription for (SaaS), or does it feel more like a "pay-per-roadmap" product?
The Stack: For those building with LLMs, how are you handling data verification to prevent hallucinations in educational contexts?
I’d really appreciate it if you gave the MVP a spin and let me know your thoughts.
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