Skip to content

Latest commit

 

History

History

agentic-sdlc

Folders and files

NameName
Last commit message
Last commit date

parent directory

..
 
 
 
 
 
 

README.md

status active
updated 2026-11-05
section Trust and Govern
audience
platform-engineer
architect
engineering-leader
level advanced
duration 90
format core-talk
decision What repository and CI infrastructure creates trustworthy agent throughput?
prerequisites
agentic-workflows
related
copilot-hooks
enterprise-patterns
unattended-agents
references
url label verified
Microsoft AgentRC repository
2026-03-19
url label verified
AgentRC concepts and maturity model
2026-03-19
url label verified
GitHub Actions documentation
2026-03-19
url label verified
Nx monorepo tools
2026-03-19
url label verified
SLSA supply chain security framework
2026-03-19

Agentic SDLC: Infrastructure for AI Velocity

The Question This Talk Answers: "How do I ship more with agents and still trust every change?"

Thesis: L3 is the launchpad: reliable context, repeatable checks, and habitual use create the conditions for outcome-focused governance and measured autonomy.

Duration: 90 minutes | Target Audience: Architects / Platform Engineers / Engineering Leaders

Deck: Open the native deck · Notes and handout: Read the speaker notes

Part 1 — Maturity Model

Assess platform readiness beside adoption practice. L3 is where repeatable infrastructure, quality controls, and habitual use first compound. The notes carry the five-level criteria, caveats, and instruction hierarchy.

Part 2 — PR Workflows

Give Copilot a bounded intent; let CI produce evidence; keep approval with named human owners. The section covers evidence bundles, policy gates, contextual triage, and recovery when a check or review disagrees.

Part 3 — Trust Manufacturing

Build fast feedback without sacrificing trustworthy checks. The notes distinguish scenario estimates from observed results and cover affected analysis, flaky tests, hermetic inputs, caching, and provenance.

Part 4 — Implementation Roadmap

Progress from the L3 foundation through L4 optimization to measured L5 autonomy. Each phase pairs platform work with adoption and governance signals; promotion follows evidence.

Transfer Actions

  • Today: Rate platform and adoption separately; measure PR-check time and flake rate; count recent changes crossing repository boundaries.
  • This week: Review repository instructions; require CI and CODEOWNERS for sensitive paths; choose one bounded agent task and define acceptance evidence.
  • This month: Pilot affected analysis and cache invalidation; assign an owner to a quarantined flake; revisit the maturity assessment and choose the next constraint.

Apply the decision to one repository and record what the evidence says.

Artifacts

  • FanHub walkthrough — a fork-based exercise for maturity assessment, fast-feedback CI, CODEOWNERS routing, evidence-oriented PRs, and baseline measures. It is an instructional artifact, not a reported run.
  • The native deck includes repository-boundary diagrams, an illustrative intent contract, evidence-bundle contents, a staged CI model, and a three-phase checklist. Numeric scenarios inherited from the long README are identified in the slide notes as estimates or illustrations, not observed outcomes.

Related Talks