Air-Gapped AI Coding: Running an AI Development Platform With No Internet Egress
Run an AI development platform air-gapped with no egress: the trust boundary, the model route, and what to verify before trusting an offline claim.
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Research and engineering guides
Browse articles about AI coding, engineering workflows and deployment. Page 2 of 3.
Does AI Actually Make Developers More Productive? The 2026 Evidence
Adoption of AI coding tools is near-universal, but rigorous evidence is mixed. Here is what the METR trial, the Stack Overflow survey, and DORA research actually show.
Read researchThe EU AI Act and AI Coding Tools: A 2026 Timeline for Engineering Teams
The EU AI Act is now partly in force. Here is a plain-language timeline and what it means for teams that build with or adopt AI coding tools.
Read researchHow Secure Is AI-Generated Code? What Veracode's 45% Finding Means
Veracode's 2025 research found 45% of AI-generated code contained security flaws. Here is what that means for engineering teams—and what does not follow from it.
Read researchKeeping Proprietary Code Private with AI Coding Tools: A Data-Governance Guide
After Samsung's 2023 ChatGPT code leak, every engineering team should know exactly where their code goes. Here is how to keep proprietary code private.
Read researchWhat the Model Context Protocol (MCP) Means for AI Coding Platforms
MCP is an open standard for connecting AI tools to data and services. Here is what it is, why interoperability matters for coding platforms, and the security caveats.
Read researchSecuring AI Coding Agents: An OWASP-Aligned Checklist for Teams
As coding assistants become autonomous agents, their biggest risk shifts from wrong code to unsafe actions. Map the 2025 OWASP LLM Top 10 to concrete controls.
Read researchShadow AI in Engineering: How to Govern Ungoverned AI Use
Surveys find most employees now use AI at work while far fewer organizations govern it. Here is how engineering leaders can replace shadow AI with a sanctioned path.
Read researchVibe Coding Safely: Reviews, Tests, and Guardrails for Teams
How to keep the speed of vibe coding without shipping unreviewed AI code: acceptance criteria, human review, tests, security checks, and bounded execution environments.
Read researchWhat Is Vibe Coding? A Practical Guide for Engineering Teams
Vibe coding, coined by Andrej Karpathy in 2025, builds software from natural-language intent and AI generation—what it is, where it works, and its limits.
Read researchWho Owns AI-Generated Code? Copyright and IP Questions for Teams
Can you copyright AI-generated code, and can it infringe someone else's? A plain-language look at the US Copyright Office's 2025 report and the GitHub Copilot litigation.
Read researchWhat Makes an Open-Source AI Coding Platform Ready for Engineering Teams?
A practical framework for evaluating AI development platforms across environments, governance, collaboration, model choice, and deployment control.
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