GitHub Certified: Agentic AI Developer Study Notes
Prepare Agent Architecture and SDLC Processes
Define agent boundaries, integrate into GitHub workflows, and establish observability
Domain Weight
Prepare Agent Architecture and SDLC Processes accounts for 17% of the GH-600 exam.
Prerequisites Before Deployment
Inputs — what data, events, or context the agent receives (issues, PRs, logs, specs)
Outputs — what artifacts or actions the agent produces (PRs, comments, test results, plans)
Success criteria — measurable conditions that define correct agent behavior
Without all three, the team cannot objectively validate whether the agent succeeds or fails
Plan → Validate → Execute
Key Pattern
Separate agent planning (reasoning) from execution (action). The plan is reviewed by humans or automated policy checks before any irreversible action is taken.
Structured plan output: JSON/YAML written to PR descriptions or CI workflow summaries
Pre-execution approval gates for high-risk or untested agents
Diff comparison between planned steps and actual tool calls to detect divergence
Anti-pattern: combining planning and execution in one indivisible step
SDLC Integration Patterns
Integration Point
Correct Pattern
Anti-Pattern
Code changes
Agent opens PR; human approves before merge
Agent pushes directly to protected main branch
PR review
Agent posts structured review comments; human merges
Agent auto-approves and merges its own PRs
CI workflows
Agent invoked as a workflow step with scoped secrets
Agent runs with org-wide credentials 'just in case'
Permissions
Least-privilege scoped to task repos/branches
Agent self-modifies permissions during a run
Audit trail
Durable logs in GitHub Actions summaries and PRs
In-memory-only logs with no persistent record
Graduated Autonomy Model
Phase
Autonomy Level
Human Role
Phase 1
Supervised — read-only or every action approved
Must approve every action
Phase 2
Semi-autonomous — low-risk writes autonomous
Approves high-risk actions only
Phase 3
Fully autonomous for proven low-risk operations
Reviews outputs post-hoc
Inspectable Agent Artifacts
Plans: structured reasoning traces in PR descriptions or workflow summaries
Diffs: code/config changes surfaced as standard GitHub PR diffs
Decision logs: step-by-step reasoning accessible in Actions output
Action logs: tool calls with parameters, timestamps, and results
Completion status: explicit success/failure with reason — no silent failures
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