Most note-taking systems for a fast-moving field like GenAI turn into a graveyard of half-finished pages within a few months. The fix isn't a better app — it's a narrower, more deliberate scope.
What's worth writing down
- A decision and its reasoning ('picked pgvector over a managed service because...') — these age well and are genuinely reusable.
- A debugging story ('the model kept hallucinating dates until I added a confidence gate') — these teach more on reread than a summarised fact does.
- A short, dated take on a fast-moving topic, explicitly flagged as likely to be outdated soon.
What to stop writing down
Copy-pasted documentation and tutorial summaries — these are one search away at any time and decay the moment the underlying tool updates. Your own reasoning and mistakes are the only notes that actually compound in value.
See writing your first technical blog post for turning these notes into something public.
GenAI engineer and AI product builder with 2+ years shipping production-grade AI systems: RAG pipelines, fine-tuned LLMs, hybrid retrieval and multi-modal apps across vision, speech and OCR, architected end to end from ingestion to deployment. Leads engineering for SCULT INDIA's 14-member team, founded the 500+ member TechVerse Enclave community and has mentored 200+ students. Three hackathon first prizes: Changethon 2025 (IIT Roorkee), Product Genesis at Vividhotsava 2025 (CSJMU Kanpur) and BYTEBATTLE (MeetKats).
Open to GenAI roles, hackathon judging, mentorship sessions and guest talks at colleges. Email pranjulrathour41@gmail.com.
