Jeremy Morrell suggests that LLMs and modern sandbox primitives create opportunities for extensible software on the web, allowing users to safely extend applications and gain enhanced capabilities.
# A quote from Jeremy Morrell
Source: [https://simonwillison.net/2026/Aug/19/jeremy-morrell/](https://simonwillison.net/2026/Aug/19/jeremy-morrell/)
19th August 2026
> My hypothesis is that**there is a new opportunity for Extensible Software on the web**\. LLMs radically lower the cost of authoring extensions, and modern sandbox primitives lower the deployment cost and provide good security boundaries\. We can build our app as a solid, accountable core, and allow users to safely extend it in many directions by having LLMs fill in the missing pieces\.**We can give our users super powers\.**
—[Jeremy Morrell](https://jeremymorrell.dev/blog/extensible-software-in-the-age-of-llms/),Extensible Software in the age of LLMs
Posted[19th August 2026](https://simonwillison.net/2026/Aug/19/)at 10:56 pm
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This is a**quotation**collected by Simon Willison, posted on[19th August 2026](https://simonwillison.net/2026/Aug/19/)\.
[sandboxing54](https://simonwillison.net/tags/sandboxing/)[ai2,194](https://simonwillison.net/tags/ai/)[generative\-ai1,943](https://simonwillison.net/tags/generative-ai/)[llms1,910](https://simonwillison.net/tags/llms/)
The article discusses how LLMs are enabling a new era of extensible software on the web, allowing users to create personalized applications and address long-tail needs through concepts like 'Small Software' and 'LLM-native software'.
Argues that using code generated by LLMs to call external tools (code calling) is more efficient and capable than traditional JSON-based function calling, but requires secure sandboxing. The author is building a framework for this approach.
An article discussing how software engineering best practices are evolving with the integration of LLM-based coding tools, offering guidance for developers.
Bryan Cantrill critiques LLMs for lacking the optimization constraint of human laziness, arguing that LLMs will unnecessarily complicate systems rather than improve them, and highlighting how human time limitations drive the development of efficient abstractions.