prepare-agent-architecture-sdlc

GitHub Certified: Agentic AI Developer (GH-600) · 71 questions

• A developer is designing a GitHub Copilot agent that will automatically triage incoming issues and assign them to team members. Which sequence correctly describes the fundamental steps an agentic AI system performs?
• An agent deployed to a production repository begins making file changes immediately upon receiving a user prompt, without first outputting a plan. What anti-pattern does this represent, and what is the best mitigation?
• Your team is designing a new GitHub Copilot agent to automate code review feedback. Before writing any agent code, which three elements should be explicitly defined in the agent's design specification?
• A developer is architecting a GitHub Copilot agent that will refactor a large codebase. The agent must first determine what changes are needed before making any modifications. Which architectural approach best separates planning from execution?
• An agent that automates dependency updates is designed to output a plan before making changes. Which format is most appropriate for the agent's plan output so that it is both human-readable and machine-parseable for downstream validation steps?
• A GitHub Copilot agent generates a plan to delete several files from a production repository. Before executing, the agent must validate the plan. Which validation approach is most appropriate for this scenario?
• An engineering team is deploying an agent to manage GitHub repository labels — creating new labels, updating colors, and deleting obsolete ones. The team wants the agent to operate autonomously for low-risk actions but require human approval for deletions. Which configuration best implements this tiered autonomy model?
• An agent performs automated dependency upgrades in a monorepo. The team wants all intermediate agent reasoning and proposed changes to be inspectable within their existing GitHub-based development workflow — without requiring engineers to access external dashboards or log aggregation tools. Which approach best satisfies this requirement?
• A team deploys an agent to handle routine infrastructure changes — updating environment variables and rotating non-critical secrets. They want human-in-the-loop oversight without blocking the rest of the CI/CD pipeline when a reviewer is unavailable. Which design best achieves both goals?
• You are designing an agent that must migrate a legacy REST API to GraphQL. The agent will need to analyze the existing API, generate a schema, update resolvers, run tests, and open a pull request. Which approach best reflects proper task decomposition for this agent?
• A developer notices that their agent, configured to refactor a monorepo's shared utilities, immediately begins modifying files across dozens of packages as soon as it receives the task prompt — without producing any plan or requesting confirmation. The agent completes several changes before a type error cascade is detected. Which anti-pattern does this behavior represent?
• You are designing an agent that automatically triages GitHub Issues, assigns labels, and routes them to the correct project board column. Before implementing the agent, you need to define its success criteria. Which definition most completely captures both the output contract and measurable success?
• A team is configuring a GitHub Copilot Extension agent that will automatically generate and merge dependency update PRs. They want to ensure the agent reasons about what to update before taking any action. Which configuration approach enforces the separation of planning from execution?
• You are building an agent that generates database migration scripts. Before any scripts are written, you want the agent to output a machine-readable plan that downstream systems can validate and log. Which configuration produces the most useful structured plan output?
• An agent has emitted a JSON migration plan for a production database. Before the agent proceeds to generate and apply scripts, the team wants to validate the plan programmatically. Which validation approach is MOST comprehensive for preventing dangerous migrations from proceeding?
• Your team has deployed an autonomous agent that creates and merges pull requests for infrastructure-as-code changes. After a near-miss where the agent merged a Terraform change that would have deleted a production S3 bucket, the team wants to implement a hard gate that prevents any merge action until an approval is explicitly granted. Which mechanism BEST enforces this gate?
• A platform team is deploying agents across three different workflows: (1) auto-formatting code on every commit, (2) proposing architectural refactors for legacy services, and (3) rotating API credentials on a weekly schedule. Which autonomy configuration is MOST appropriate across all three workflows?
• A developer is debugging an agent that occasionally generates incorrect test fixtures. The agent runs inside a CI pipeline and the developer cannot interactively prompt it. Which configuration produces the MOST useful inspectable artifacts for diagnosing the root cause?
• A developer reports that an agent deployed to refactor a large codebase began deleting files and rewriting modules immediately after invocation — before producing any plan or summary that the team could review. No human had an opportunity to approve the approach. Which anti-pattern does this behavior represent, and what architectural change would prevent it?
• A team reports that their code-review agent continues running and submitting new review comments long after the pull request has already been approved and merged. The agent never stops on its own. What is the most likely root cause of this behavior?
• After deploying a repository-migration agent, your team notices it begins executing file moves and branch deletions immediately after receiving a user request — before producing or reviewing any migration plan. Which principle of agent architecture is being violated?
• An agent that automates dependency updates across multiple repositories is failing a compliance audit. Auditors report they cannot determine what reasoning the agent used, which packages it evaluated, or why it chose specific version upgrades. The agent completes its work but leaves no trace of its intermediate decision-making. What should be added to correct this?
• A team reports that their automated release agent, once triggered, cannot be paused or redirected mid-task. When a critical vulnerability is discovered during a release run, the team has no way to stop the agent before it deploys to production. Which missing architectural feature is the direct cause of this problem?
• After deploying an automated access-provisioning agent in a financial services organization, the compliance team flags it as a violation. The agent independently approves, provisions, and audits all access changes without any human review step. The organization's policy requires segregation of duties for access management. What is the most appropriate remediation?
• An agent tasked with generating GitHub Actions workflows is failing in production. Investigation reveals that users submit requests like 'set up CI for my project' without specifying the language, test framework, or deployment target. The agent silently assumes defaults — often incorrectly — and generates workflows that fail immediately. What is the root cause of this failure?
• A team reports that their security-scanning agent produces results that downstream systems cannot reliably parse. On some runs the agent returns a JSON array of vulnerabilities; on other runs it returns a narrative paragraph; on others it returns a partially structured object with inconsistent field names. Automated ticketing that depends on the agent's output fails unpredictably. What is the most appropriate fix?
• After a security audit, a company discovers that it cannot determine which commits in its repositories were authored by AI agents versus human developers over the past six months. The agent was configured to commit using a shared service account with no additional metadata. Which traceability mechanism should have been implemented from the start?
• Your team wants an AI agent to plan a feature before any code is written. The plan must be reviewable and approvable by humans before implementation begins. Which GitHub artifact is best suited to serve as the planning surface where the agent records structured tasks that humans can inspect and approve?
• An analysis agent generates a feature plan during a GitHub Actions workflow. The plan must be passed to a separate implementation agent in a later job. Which approach best preserves the structured plan so the implementation agent can consume it reliably?
• Your team wants an AI agent's success criteria to be automatically verifiable, not just described in prose. Which approach makes success criteria machine-readable and directly usable as an evaluation gate?
• A DevOps team wants an AI agent to analyze a monorepo's dependency graph, identify outdated packages, and then automatically update those packages across all affected services in a single pipeline run. A senior engineer recommends splitting this into two distinct agents. What is the primary architectural reason for this recommendation?
• In a multi-agent deployment system, a planning agent generates a JSON deployment plan and writes it to a shared artifact store. An execution agent is subscribed to the same artifact store and will begin deploying resources as soon as a plan appears. A Domain 1 reviewer flags this design as incomplete. What is missing?
• A developer submits the prompt 'Clean up the repo' to an autonomous agent that has write access to the GitHub repository. Without requesting clarification or generating a plan, the agent immediately deletes branches it classifies as stale, removes files it judges redundant, and closes issues it considers resolved. The repository owner later discovers that a critical hotfix branch and several open feature branches were deleted. Which agent anti-pattern caused this outcome?
• An engineering team is deploying two GitHub Copilot agents in their pull request pipeline: Agent A posts automated code quality feedback comments on open PRs, and Agent B merges approved PRs into the main branch when certain criteria are met. How should the autonomy degree differ between Agent A and Agent B?
• An autonomous deployment agent successfully rolls out a new microservice version across three environments. When the SRE team reviews the deployment afterward, they find no structured record of which container images were deployed, which Kubernetes namespaces were modified, what configuration values were applied, or what the pre-deployment and post-deployment states were. Which Domain 1 requirement does this agent design violate?
• A tech lead assigns an AI agent the task of refactoring a 200-file Python monolith to follow a domain-driven design pattern. The task is expected to take multiple pipeline runs spanning several hours. Before the agent begins, the tech lead wants to ensure the team can pause the agent at any point, evaluate its progress against the original goals, and decide whether to continue, redirect, or roll back. What must be defined first?
• Your security team is reviewing a new Copilot agent that will autonomously triage issues, label PRs, and close stale tickets across 12 repositories. During threat modeling, they identify that the agent's GitHub App has write access to all repositories in the organization. Which threat does this configuration most directly introduce, and what is the correct mitigation?
• A cleanup agent is granted permission to delete stale branches. It reads a list of branches and immediately begins deleting them — including a branch named 'release-candidate-2.1' that is 47 days old. The deletion triggers a production incident because the branch was being used as the source for an active hotfix. Which architectural pattern would have prevented this incident?
• An organization must demonstrate to external auditors that all automated changes made by their GitHub agent comply with their change management policy. The auditors require evidence that every automated change was authorized, executed within approved parameters, and reviewed. Which combination of architectural planning decisions best supports this audit requirement?
• A developer is building a Copilot agent that only reads open pull requests and posts review comments. During the SDLC security review, the architect asks which GitHub App permissions should be requested. The developer suggests requesting 'Pull requests: Write' plus 'Contents: Write' to future-proof the agent. What should the architect recommend instead?
• An agent is tasked with 'fixing security vulnerabilities in the authentication module.' After 40 tool calls, the agent is still iterating because it cannot determine when it is done. It has patched several issues but keeps finding new edge cases to address. What should have been defined before the agent was launched?
• A team is defining success criteria for a refactoring agent that will automatically update deprecated API calls across a large codebase. Which success criteria definition best incorporates both functional performance and Responsible AI safety constraints?
• A Copilot agent is embedded in a GitHub Actions CI/CD pipeline to auto-fix linting errors and push corrected code directly to the triggering branch. A security engineer notes that this agent runs with the workflow's default GITHUBTOKEN. Which security boundary violation does this pattern most clearly represent?
• A code migration agent is assigned the task of migrating a monolith to microservices. Within the first 3 tool calls, the agent begins modifying production configuration files before it has completed an analysis of the dependency graph, service boundaries, or data layer. Which anti-pattern does this behavior represent?
• During the planning phase of an agentic AI system that will read issue descriptions and automatically create pull requests, a security architect performs a threat model. Which threat is most specific to agentic AI systems and should be prioritized in the architecture review?
• After deploying a Copilot agent that automatically closes resolved issues and merges approved PRs, your compliance team reports that the organization's audit log shows actions attributed only to the GitHub App service account, with no indication of which agent run, which user request, or which model decision triggered each action. What is the most important improvement to implement?
• A security team needs to audit why an automated deployment agent approved and deployed a specific build last Tuesday at 2:17 AM. The agent produced no persistent artifacts during its run — it processed everything in memory and exited cleanly. The team cannot reconstruct the decision. What should the agent have produced to make this audit possible?
• A database maintenance agent is currently configured to autonomously run VACUUM, ANALYZE, and REINDEX operations on a PostgreSQL cluster. An operator wants to expand its capabilities to include write operations — specifically UPDATE and DELETE statements for data cleanup tasks. Which change must accompany granting write access to the agent?
• Your team uses a copilot-setup-steps.yml file to configure the environment that Copilot agent runs use during coding tasks. A security review finds that the file installs several npm packages using an unpinned 'latest' version tag and downloads a bash script from an external URL using curl | bash. Which change should be prioritized to harden this configuration?
• An architecture team is designing a CI/CD pipeline in which an AI agent generates code changes and immediately commits them. A security engineer recommends inserting a dedicated security-review step between code generation and commit. Which design pattern does this recommendation implement?
• An autonomous Copilot agent has been generating and merging its own pull requests for test file changes. A developer notices the agent has started modifying files in the /security/ directory, which contains authentication middleware and secrets configuration. The repository has a CODEOWNERS file. How should CODEOWNERS be used to prevent the agent from self-approving changes to these sensitive paths?
• An organization operates in a regulated industry (healthcare, HIPAA scope). They are planning an agent that performs database schema migrations. Their compliance team requires that any schema change affecting tables that store PHI (Protected Health Information) must receive explicit human approval before execution. Which architecture planning decision correctly implements this requirement?
• An infrastructure agent generates a Terraform plan before applying changes. The security team wants to automatically validate that no planned action will open inbound traffic from 0.0.0.0/0 on any port before the plan is executed. What is the prerequisite that makes this automated safety check possible?
• Your organization's main branch has branch protection enabled requiring two human approvals and passing status checks before merging. A new Copilot agent is configured to auto-approve its own pull requests once its internal confidence score exceeds 95%. During testing, the agent successfully merges a PR to main with only its own approval. What is the most likely cause of this failure?
• A financial services company deploys a Copilot agent for code analysis and developer assistance. Compliance requirements mandate that no code change can be made without a human approval chain. What tool configuration satisfies this compliance requirement while maximizing the agent's usefulness to developers?
• A Responsible AI principle states that AI systems should be transparent and explainable to users affected by their decisions. A code-review agent is being designed that will automatically approve or block pull requests based on quality and security criteria. Which architectural decision best implements the transparency principle for this agent?
• Six months after deploying a Copilot agent, the underlying model is upgraded by GitHub, two new tool integrations are added, and the agent's task scope is expanded to include writing release notes. The security team has not performed a review since the initial deployment. At which point in this lifecycle should a security review have been triggered?
• A developer notices that their dependency-update agent, originally scoped to update npm packages in a single repository, has begun modifying CI/CD pipeline YAML files and .github/workflows/ configuration as part of its updates — actions that were never authorized. This is an example of which Responsible AI risk, and what architectural control prevents it?
• A deployment agent produces a 12-step deployment plan. A validator tool reviews the plan and identifies that step 7 will drop and recreate a production database table without a preceding backup step. What is the correct agent behavior at this validation point?
• An agent that performs database schema migrations uses a gate function before each migration step. The gate checks three conditions: (1) the target database is not a production instance, (2) a backup exists from within the last 24 hours, and (3) the migration script has been tagged 'approved' by a reviewer. What is the primary security benefit of this gate pattern?
• A Copilot agent that was managing dependency updates is being retired because a third-party solution is replacing it. The agent had a GitHub App installation, a stored fine-grained PAT, a secrets manager entry, an MCP server running on an internal host, and a webhook configured on 15 repositories. What is the correct order of decommission steps to avoid security gaps?
• An organization is preparing for a SOC 2 Type II audit that will evaluate their agentic CI/CD pipeline. The auditors require evidence that every code change merged by an automated agent can be traced to an authorized request, that the agent operated within its defined parameters, and that its actions can be reconstructed from logs. Which combination of artifacts satisfies all three audit requirements?
• An engineering team is evaluating where in their SDLC to introduce agentic automation. They track four metrics: story-point velocity, defect escape rate, mean time to merge (MTTM) for pull requests, and on-call incident frequency. After a six-week pilot, agent-assisted code review reduced MTTM by 40% but defect escape rate increased by 12%. Agent-assisted test generation had no measurable velocity impact but reduced defect escape rate by 18%. Which conclusion BEST describes where agentic automation is currently adding genuine value?
• A platform team is designing a graduated autonomy program for a dependency-update agent. In Phase 1, the agent proposes PRs for human approval. In Phase 2, it can auto-merge PRs that pass all CI checks. In Phase 3, it is allowed to tag and release patch versions. Which condition MOST appropriately gates the transition from Phase 2 to Phase 3?
• A team designs a single 'super-agent' that, when triggered, reads the full repository, generates an implementation plan, writes all required code changes, runs the test suite, reviews its own output for quality, and opens a PR — all within one agentic loop. After three months, the team observes frequent mid-run failures, inconsistent PR quality, and difficulty diagnosing which step failed. Which architectural principle does this design MOST violate?
• A team starts with two agents and observes them effectively using structured logs per agent. They then scale to 20 agents across five repositories. Which observability design change is MOST critical to maintain diagnostic capability at 20-agent scale?
• An organization is choosing which SDLC activities to keep human-driven versus automate with agents. They have four candidates: (1) gathering ambiguous stakeholder requirements, (2) generating boilerplate service scaffolding from an approved template, (3) performing final architectural review of a new microservice, and (4) running regression tests after each commit. Which TWO activities are MOST appropriate for full agent automation?
• An engineering director wants to present agent ROI to the executive team. She has the following data after 90 days: story-point velocity increased 22%, review turnaround time dropped from 4.2 hours to 1.1 hours, defect escape rate decreased 15%, and agent infrastructure costs $8,000/month. Which metric combination MOST convincingly demonstrates ROI to a business audience?
• A platform architect is designing guardrails for an agent that spans the full SDLC pipeline: planning, implementation, testing, code review, and deployment. The team wants to minimize unnecessary human interruptions while maintaining safety. Which guardrail placement strategy is MOST appropriate?
• A senior engineer is reviewing the autonomy configuration for a code-review agent that has been in production for six months. The agent started at a conservative autonomy level but the team wants to expand its scope. Which set of signals MOST appropriately indicates that the agent is ready for expanded autonomy?
• A startup wants to introduce its first agent into the SDLC but has limited engineering bandwidth to manage agent infrastructure. They are choosing between: (A) an agent that monitors issues and automatically creates implementation-ready GitHub Issues from support tickets, (B) an agent that autonomously writes, tests, and deploys hotfixes to production with no human review, or (C) an agent that generates draft PR descriptions from commit diffs. Which option provides the BEST balance of value and appropriate scope for a first agent deployment?