Coding Assistance Without the Code Leaving the Building
The article discusses the challenges of using AI coding assistants in organisations, highlighting concerns about code security and offering a solution with eLLM's code API to keep code within the organisation's infrastructure.
The problem: useful tools, uncomfortable questions
Developers have quickly found AI coding assistants genuinely useful, for explaining unfamiliar code, drafting boilerplate, and speeding up routine work. For an organisation's own development team, that raises an uncomfortable question: where does the code go once it's pasted into a public coding assistant, and what happens to it after that.
For proprietary systems, internal tools, or anything built for a client, that's not a question IT or development leads can afford to leave unanswered, however useful the tool is proving to be.
Why banning AI coding tools outright backfires
Telling developers to stop using AI assistance rarely works in practice, and even where it's followed, it removes a tool that's become a normal part of how software gets written. It also does nothing to address the underlying concern. If the code shouldn't leave the organisation, the fix isn't removing the assistant, it's controlling where the assistant runs.
How eLLM addresses this
A dedicated code API centralises access.
eLLM provides a code API purpose built for developers, giving the organisation one place to manage how coding assistants are used, rather than a scatter of individual accounts on public services.
Usage is logged.
Access through the code API is tracked, giving development leads visibility into how the assistant is being used across the team.
Local model use keeps code secure.
By using local models through the code API, code can stay within the organisation's own infrastructure rather than being sent to an external service to get a useful response.
Dedicated coding modes and API keys support real workflows.
The code API includes modes built specifically for coding tasks, along with special API keys, so it fits into existing development workflows rather than feeling like a bolted on chat tool.
The outcome
Developers keep the AI assistance that's become part of how they work, without sending proprietary code to a public service to get it. Development and IT leads gain a centralised, logged system instead of an unmanaged spread of individual tool subscriptions.
Learn more
The eLLM Knowledge Base covers how the code API is set up, its dedicated coding modes, and how local model use keeps code within your own infrastructure.
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