An agency can use AI to help plan, write, test, document, or inspect parts of a backend. That does not mean an AI built the system on its own: the important questions are what project information the tools can access, what changes they make, and which people review and approve the work.
Where AI may enter backend development
AI assistance can appear at several stages of a project. NIST’s September 2026 DevSecOps practices guide describes AI-supported work such as translating requirements into tasks, helping with threat modeling, generating or modifying application code and infrastructure as code, drafting tests and API documentation, analyzing dependencies or vulnerability reports, and supporting CI/CD automation.
These are examples of assisted activities, not proof that an AI system independently delivered a production backend. The agency’s actual workflow depends on the tools and permissions it chose for your project. Ask which parts of your system involved AI and what validation each change received.
What information an AI tool may receive
Some coding assistants can transmit more than the file currently open in an editor. Depending on the product and settings, the context sent to a model provider may include project structure, other files, or terminal output. That material could reveal proprietary logic, internal architecture, personal data, or credentials. OWASP’s Secure Coding with AI guidance recommends understanding what context a tool sends and configuring exclusions for sensitive paths and file types.
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Ask the agency which tools it uses, what project materials they can access, what information leaves its environment, and what exclusions are configured. Do not assume that .gitignore keeps a local file away from an assistant: it is not a general access-control mechanism for tools that can read the filesystem.
Keep credentials out of AI-readable files
Secrets such as API keys, database passwords, and signing keys should be stored in environment variables, a vault, or an encrypted secret store—not in ordinary project files an assistant may read. Ask how the agency prevents credentials and other sensitive data from entering prompts or tool context.
What can go wrong—and which controls matter
Incorrect or insecure code
AI-generated output can be wrong, incomplete, or insecure. NIST’s DevSecOps reference material describes risks including inaccurate output and insecure code generation, and calls for human monitoring and validation alongside established security processes. AI assistance is not a substitute for the project’s normal review, testing, and security checks.
Changes to build and deployment systems
Review should cover more than application code. A coding agent may be able to change build scripts, package scripts, CI/CD configuration, or deployment infrastructure—files that can run with significant privileges. OWASP’s guidance highlights the risk of allowing agents to modify these trusted components without appropriate controls. Ask whether an agent can run commands or reach production systems, and which actions require human approval.
Unclear responsibility after handoff
A human developer who accepts and commits a change remains responsible for it, even if AI generated it. OWASP says every AI-assisted change should have a human owner who reviews and approves it. For your project, that means the agency should be able to identify who approved significant changes, explain how they were checked, and tell you who maintains the backend after delivery.
Questions to ask the agency
Use these questions to compare proposals or clarify how work on your project was performed. They are practical discussion points, not universal legal requirements.
- Data and tools: Which AI tools are used? What code, documents, logs, or other project information can they access, and what is sent to an external provider? What is excluded?
- Permissions: Can an AI agent run commands, access production systems, or modify CI/CD and deployment files? Which actions require a person’s approval?
- Review and testing: Who reviews AI-assisted changes? What code review, automated tests, security analysis, and independent testing are appropriate for this backend’s risks?
- Traceability and ownership: Can the agency identify the person who approved a change and preserve relevant change records? Who is responsible for maintenance after handoff?
- Acceptance and response: What review or test evidence will you receive at delivery? How will vulnerabilities be triaged, fixed, and communicated?
Use a shared security vocabulary
When you want to discuss development controls in concrete terms, NIST’s Secure Software Development Framework (SSDF), SP 800-218, offers a common vocabulary that purchasers and suppliers can use to talk about secure development. Its companion SP 800-218A supplements the framework with practices for generative AI and dual-use foundation models. These references can help structure a conversation; they do not prescribe one universal agency contract or client checklist.
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