← Back to archive

Recursive Language Models: Why Bigger Context Can Hurt AI

27 April 2026 · 54 views · 1 likes · 0 reposts · 138 blog views

AI SEO coding rag research

Came across the paper about Recursive Language Models from MIT where they broke the whole "bigger context = better AI" narrative.

The core problem is something called context rot. The more you stuff into a model, the worse it gets. It forgets things, mixes details, loses structure. You've probably noticed that yourself - longer prompts often give worse answers.

The industry workaround was Retrieval-Augmented Generation (RAG). Split data into chunks, retrieve what seems relevant. But it’s guesswork ... if retrieval fails, the model never even sees the right info.

MIT flipped the idea.

Don’t force the model to remember. Let it search.

They keep the data outside the context and let the AI navigate it like a human:

1️⃣ find 2️⃣ read small parts 3️⃣ analyze 4️⃣ combine

That’s all, folks.

And apparently it works way better - even on huge datasets.

The insight?

intelligence isn’t about holding everything it’s about knowing where to look

if it's too obvious then why the whole industry optimized the opposite...

Source: arxiv.org/abs/2512.24601

View on X

A frightened child in bed expresses distress, stating they see "rag" everywhere, emphasizing confusion and anxiety.

Originally posted on X

PS: I'm pretty active on 𝕏 if you'd like to follow along

Related posts

Archive

2026

2025

2024

2018