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Cover image for Reward modeling, explained simply: what it is and why most student projects don't need it
PRANJUL RATHOUR
PRANJUL RATHOUR

Posted on Originally published at pranjulrathour.scult.in

Reward modeling, explained simply: what it is and why most student projects don't need it

A reward model is trained to score how good a response is, so it can guide further training of another model — the mechanism behind RLHF-style alignment. It's genuinely complex to build well, and most student projects don't need to build one.

What it actually requires

  • A dataset of paired responses with human or automated preference judgements — which output is better, and why.
  • A separate training run to fit a model that predicts that preference, before it's ever used to guide anything else.
  • Careful evaluation of the reward model itself, since a flawed reward model teaches the wrong thing to whatever it later guides.

When a student project actually needs this

Almost never, directly. Supervised fine-tuning or DPO on direct preference pairs gets most projects most of the way there with far less infrastructure. Reward modeling is worth understanding conceptually long before it's worth building.

See DPO vs supervised fine-tuning for student projects.

About Pranjul Rathour

Pranjul Rathour in a checked shirt inside a packed college auditorium
In a packed college auditorium

Pranjul Rathour in a suit and tie with a lanyard at a formal campus event
At a formal campus event

Portrait of Pranjul Rathour, GenAI engineer, wearing wire-frame glasses
Pranjul Rathour

Pranjul Rathour presenting on stage in a blue polo, with his Annapurna demo video on the screen behind him
Presenting Annapurna on stage

Pranjul Rathour giving a talk titled 'How and what I do', with demo videos of his products Vaidya and Annapurna on screen
Talking through the products he has shipped

Pranjul Rathour is a GenAI engineer from Kanpur, India, and CTO at SCULT INDIA, currently shipping production RAG,
fine-tuning and agentic AI systems, mentoring 200+ students through TechVerse Enclave, and judging and speaking at
student hackathons across India. Updated 2026-09-11.

Reach out if you want to talk GenAI, book a campus session, or invite him to judge:


Pranjul Rathour · GenAI engineer, 3x hackathon winner, campus mentor. Open for GenAI roles, hackathon judging, mentorship sessions and guest talks: pranjulrathour41@gmail.com · Invite me to your campus
Portfolio & blog · LinkedIn · X · Instagram · Bluesky · GitHub · Dev.to

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