Private coding assistants: why your team shouldn't send code to third-party APIs

Copilot and Cursor have changed development productivity. They've also created the largest IP exfiltration channel a software company has ever had: one every developer participates in every day, with the best intentions.

What exactly travels with each prompt

A typical prompt isn't ‘write me a function that adds two numbers’. It's the entire file you're working on, plus context: imports, variable names, routes, endpoints, mishandled secrets, client names appearing in tests. The model needs that context; that's why it works. But the provider keeps it.

The real cost of a leak

Samsung banned internal ChatGPT use in 2023 after an engineer pasted proprietary chip code to fix a bug. The code stayed on OpenAI's servers. No technical breach, just normal workflow. The incident pulled Samsung's internal LLM investment forward by three years.

The operational lesson from the Samsung case isn't technical, it's internal product: banning is easy, replacing is expensive. If you don't give the team a fast, secure, productive alternative, they quietly go back to pasting code into their personal account and the ban becomes a dead letter.

What a private coding assistant needs to be viable

• Models competitive with GPT-4 / Claude: open-source like Qwen2.5-Coder-32B, DeepSeek-Coder-V3, Llama-3.3-70B already hit 85-92% on HumanEval+ benchmarks.
• Sub-300ms latency for autocomplete, which demands local state-of-the-art GPUs, not shared GPUs from two years ago.
• IDE integration (VS Code, JetBrains) without asking each developer to configure a manual proxy.
• Persistent storage for project context (RAG over the internal repo) without that context ever moving.

How we deliver it at GPU Solutions

We stand up the GPU Flow sandbox with preloaded models, mount Exascaler storage for the repo and context, and expose an SSH/HTTPS endpoint reachable only from your VPN. The team installs the VS Code or JetBrains extension and points it at the endpoint. From that moment, not a single line of code leaves the Madrid perimeter. Provisioning time: 48-72h.

This isn't a POC. It's the reference setup we deploy for teams of 10-200 developers, validated in our own lab under real load. The cost doesn't compete with Copilot Business on €/dev/month, and it doesn't need to: what you're paying for is no line of code leaving your perimeter and no exposure to the CLOUD Act. Once your CISO signs off on the IP risk assessment, that gap stops being a line-item and becomes coverage.

The sandbox isn't a dead end either: it's a rung on the ownership ladder. If tomorrow you want weights fine-tuned on your own code (OdiTuning) or the full stack on your own infrastructure orchestrated by GPU Flow, you climb one rung with no traumatic migration. The speed and cost math behind this setup is detailed in private inference: the speed that saves money, and the underlying thesis, built on Alex Karp's CNBC interview, in controlling your weights is controlling your fate.