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CodeTracked since May 19, 2026

AI-DLC adds an opt-in resiliency extension with WAR-based reliability checks

This PR adds a new AI-DLC resiliency extension that introduces a 15-rule reliability baseline mapped to 11/13 AWS Well-Architected Reliability Pillar questions, an opt-in requirement during planning for RTO/RPO and DR strategy capture, and template-level validation so resilience rules can be checked end-to-end through workflow stages.

AI-DLCResiliency extensionAWS Well-Architected Reliability PillarRESILIENCY-02

What Happened

  • This PR adds a new AI-DLC resiliency extension that introduces a 15-rule reliability baseline mapped to 11/13 AWS Well-Architected Reliability Pillar questions, an opt-in requirement during planning for RTO/RPO and DR strategy capture, and template-level validation so resilience rules can be checked end-to-end through workflow stages.
  • This PR adds a new AI-DLC resiliency extension that introduces a 15-rule reliability baseline mapped to 11/13 AWS Well-Architected Reliability Pillar questions, an opt-in requirement during planning for RTO/RPO and DR strategy capture, and template-level validation so resilience rules can be checked end-to-end through workflow stages.
  • 1 evidence item attached for review.

What is Different

Before

Scattered source updates, isolated context, and manual follow-up across multiple feeds.

Now

Implemented a new workflow capability that captures reliability decisions earlier (requirements stage), enforces them through 15 explicit rules with blocking checks, and verifies generated infrastructure artifacts against those rules via a dedicated template review skill and resilient baseline templates.

Why Track This

Why It Matters

AI-DLC teams can generate application delivery workflows that are less likely to miss recovery, observability, and failover requirements, so operators get clearer reliability behavior during incidents instead of discovering missing controls only after deployment. The PR’s A/B validation shows compliance improving from 3/15 to 9/15 rules (with added alarms, tracing, cross-region DR, and RTO/RPO tagging), so adoption should be monitored for opt-in consistency, drift in downstream stages, and whether teams still miss REL 2/3 reliability areas not covered by this extension.

Impact

AI-DLC teams can generate application delivery workflows that are less likely to miss recovery, observability, and failover requirements, so operators get clearer reliability behavior during incidents instead of discovering missing controls only after deployment. The PR’s A/B validation shows compliance improving from 3/15 to 9/15 rules (with added alarms, tracing, cross-region DR, and RTO/RPO tagging), so adoption should be monitored for opt-in consistency, drift in downstream stages, and whether teams still miss REL 2/3 reliability areas not covered by this extension.

What To Watch Next

  • Watch whether AI-DLC becomes a repeated pattern.
  • Track follow-up changes around AI Workflow Automation.
  • Compare future signals against this evidence trail.
  • Re-check risk flags: low_opt_in_adoption, compliance_rule_drift_in_later_stages.
Open Topic TimelineOpen Technical EventOpen Original Sourcelow_opt_in_adoption / compliance_rule_drift_in_later_stages / rel_2_rel_3_coverage_gaps / resiliency_overhead_in_small_poc_flows

Supporting Evidence

GITHUB PULL REQUESTHigh Trust

awslabs/aidlc-workflows PR #265: feat(resiliency-extension): add new resiliency extension

awslabs/aidlc-workflows PR #265 introduces a new resiliency extension with `resiliency-baseline.md`, RESILIENCY-02 follow-up for RTO/RPO, resilient CloudFormation templates, and a template review skill for rule-level compliance checks.