AI software engineering workflows
Build AI engineering workflows for code review, incident response, documentation, testing, and developer operations.
Where these AI workflows fit
Engineering agents are most useful when code access, analysis, verification, and review are composed as a controlled workflow. This collection covers reusable patterns for software delivery and operations.
Inspect each blueprint's agents, functions, MCP tools, and stage order. You can then connect your repositories and systems while preserving the checks your team requires.
Software engineering blueprint catalog
Compare each workflow's inputs, stages, agents, functions, MCP tools, and availability before opening it in GraphN.
API Data Summarizer
Fetch any public JSON API and get a clear, plain-language summary of the response
SequentialSecretsApiReady to useAPI Docs Generator
Point it at your API code and get OpenAPI-style docs with examples
EngineeringApiDocumentationRequest accessArchitecture Decision Record Writer
Describe a technical decision, get a formatted ADR with tradeoffs and alternatives
EngineeringDocumentationAdrRequest accessProduction Incident Response
Triage a production incident: analyze the alert, logs, and evidence in parallel and propose next steps
ParallelAnalysisDevOpsReady to usePR Diff Review
Review a code diff and get structured feedback on risks, bugs, and suggested changes
SequentialCode ReviewGithubReady to useRelease Notes Generator
Generate user-friendly release notes from your git commit history and Jira tickets
EngineeringRelease NotesDocumentationRequest accessSpeech Roundtrip (TTS + ASR)
Synthesize text to speech, transcribe it back, and measure accuracy -- showcasing end-to-end voice AI
TtsAsrSpeechReady to useVulnerability Scanner
Scan your dependency list, check for known vulnerabilities, and get a prioritized fix plan
EngineeringSecurityDependenciesRequest access