Most places I know that have strict on-premise/air-gap requirements are just investing in on-premise AI and open source harnesses instead. The only ones that don't are the typical places that are slow to adopt technology in general (usually because they can afford to due to historic moat).
Most places that must do things on-prem also have strict requirements and long deadlines.
LLMs can be nice sometimes, but not necessary. Internal teams with "not invented here" syndrome currently working on that stuff are ultimately wasting money until the dust settles a bit more.
Those long deadlines have nothing to do with implementation. It's the game of telephone and accountability bottlenecks. You still want to retain your most experienced devs and give them plenty of time to work. Writing the code was never the bottleneck. A good dev team has balanced experience of the business and the code, not just the code, and certainly not the kind of code an LLM generates. Most of the decisions by those devs happens outside the codebase.
I can only tell you what we see across our customers, which are exactly the on-premise crowd. We are building a ChatGPT/Cowork competitor focused on on-premise needs[0]. While we cover most things outside of the coding side of things, I know that all of them are also embracing coding agents, typically with your usual open weight coding models hosted on-premise.
Sure, the slow behemoths that you talk about exist as well, but I am seeing many companies that have successfully turned compliance into just another kind of process that isn't slowing down the product development lifecycle. And within those process steps they are also able to leverage AI to speed up e.g. review processes.
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Places that can't have code leave the work site still do not use AI.
Most places I know that have strict on-premise/air-gap requirements are just investing in on-premise AI and open source harnesses instead. The only ones that don't are the typical places that are slow to adopt technology in general (usually because they can afford to due to historic moat).
Most places that must do things on-prem also have strict requirements and long deadlines.
LLMs can be nice sometimes, but not necessary. Internal teams with "not invented here" syndrome currently working on that stuff are ultimately wasting money until the dust settles a bit more.
Those long deadlines have nothing to do with implementation. It's the game of telephone and accountability bottlenecks. You still want to retain your most experienced devs and give them plenty of time to work. Writing the code was never the bottleneck. A good dev team has balanced experience of the business and the code, not just the code, and certainly not the kind of code an LLM generates. Most of the decisions by those devs happens outside the codebase.
I can only tell you what we see across our customers, which are exactly the on-premise crowd. We are building a ChatGPT/Cowork competitor focused on on-premise needs[0]. While we cover most things outside of the coding side of things, I know that all of them are also embracing coding agents, typically with your usual open weight coding models hosted on-premise.
Sure, the slow behemoths that you talk about exist as well, but I am seeing many companies that have successfully turned compliance into just another kind of process that isn't slowing down the product development lifecycle. And within those process steps they are also able to leverage AI to speed up e.g. review processes.
[0]: https://github.com/EratoLab/erato
Looks interesting. Might want to double check your website - the Customization / Assistants / MCP pills in your hero aren't working for me
Some do, DOD is pushing grok
Wonder how that happened...
Someone bought a very expensive golf club membership?!