At LinkORB Engineering, we use AI-based workflows to accelerate and streamline the software development lifecycle. It is integrated into everyday workflows to support activities such as:
These use cases also help minimise context-switching and surface multiple approaches quickly, enabling faster, more informed decision-making.
AI-generated output is never treated as authoritative. All contributions, regardless of origin, must meet the organisation’s standards for code review, continuous integration, and security. AI usage must comply with our established data handling policies, and only approved AI tools may be used.
Our AI usage policy outlines strict boundaries on which environments and data AI can or should access. AI tools are not allowed in environments where production secrets, client data, personally identifiable information, or similar sensitive data are accessible.
Each team member is expected to fully understand and take ownership of what they merge, including implementation decisions, trade-offs, edge cases, failure modes, and operational impact. While AI can accelerate initial drafts, we prioritise security, maintainability, observability, and long-term cost over simply passing CI on the happy path.
All AI-assisted contributions are reviewed in the same way as any other changes, including scrutiny of dependencies, potential injection surfaces, authentication boundaries, and handling of sensitive data. Confidence in generated output does not replace proper threat modelling or review.
To ensure consistent and effective use, teams share proven guidelines, prompt tips, trusted tools, and lessons learned. Ongoing investment in AI literacy enables all engineers, not just early adopters, to benefit from these workflows.
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