<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Continual-Learning on Suriya's site</title><link>https://suriya.cc/tags/continual-learning/</link><description>Recent content in Continual-Learning on Suriya's site</description><generator>Hugo</generator><language>en</language><copyright>This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.</copyright><item><title>the genius who never learns</title><link>https://suriya.cc/essays/continual-learning/</link><pubDate>Mon, 20 Jul 2026 00:00:00 +0000</pubDate><guid>https://suriya.cc/essays/continual-learning/</guid><description>&lt;p>an agent that learns and optimizes will outperform a frozen 1.8 trillion parameter model.&lt;/p>
&lt;p>i&amp;rsquo;m not saying a 7B model is smarter than a frontier model. it isn&amp;rsquo;t. on a cold-start, zero-context task the big models win. what i&amp;rsquo;m saying is that the moment you fix a task, a customer, a codebase, a distribution of tickets, and you let one system accumulate the corrections while the other one wakes up with amnesia every morning, the one that accumulates wins. and most valuable work is a fixed task with a customer and a distribution of tickets.&lt;/p></description></item></channel></rss>