SDLC Transformation with AI
Automated PR reviews and AI contributions detection
AEM Sites AI review bot — an automated code review workflow that runs the /review-pr skill from aem-cursor-toolkit on every pull request across the org, flags issues by severity, and lets you implement the fixes without leaving your editor.
Demo: PR Review Demo.mp4
SDD over Github actions
From idea to PR without the need for a local setup. All inside Github:
- Open an Issue
- Generate the spec
- Implement the feature
- Review the PR
Multi-rep features are next.
Closing the review loop
Two new Experience Success Skills that:
- triage-pr-reviews triages findings from any reviewer source and produces an action plan you approve
- implement-pr-reviews executes it batch by batch, replies to every thread, and hands the PR back
AEM Sites Omnichannel
Agentic CF Management
Agentic CF bulk operations technical agent to be integrated under EPA Content Updater and surfaced in AI Assistant.
Demo: CFMA-full-demo.mov
Agentic AEM Sites Workfront Integration
Agentic integration between AEM Sites and Workfront for better management of Content Supply Chain.
AEM Sites Optimizer
Contente Copy Agent for ASO
Rolling out the Alt-Text opportunity for 500 customers all at once presented with unique challenges. One of them was around testing the proposed fixes without impacting the customers.
This agent is helping us to generate pages on the RV (staging) clones, matching the Prod Context.
Demo: cloning skill.mov
ASO RV clone service
In partnership with the RV and CM
teams, we started creating a service which can support the production scale validation that ASO needs.
We have already a start on it and we have also a PoC which can already be used for manual validations.
Summit 500+ sites Alt-Text analysis
A way of agent mass validating and reporting on the alt-text opportunity for the PLG summit experience.
We generated alt-text audits for 500+ CS sites, generating 50k+ suggestions. Each suggestion was agentic tested to identify the fixability potential.
LLM Optimizer
OffSite Opportunity Monitor [App]
When creating Offsite Opportunities, we rely on AI generating quality content, which is not always the case. In order to improve quality, reduce hallucination and be able to scale we needed to validate AI content faster and efficiently. For Offsite Opportunities we validate Brand Sentiment and Share of Voice accuracy, as well as Recommendations /Suggestions quality.
OffSite Market Discovery [PoC]
Service that identifies quality prompts and brand-related topics to uncover offsite opportunity recommendations. The flow maps brand's market categories based on products and services, then generates category-specific topics and prompts. It analyzes responses share of voice across brands, competitors, while identifying cited sources. Comparing these sources with URLs already configured in LLMO reveals opportunities to recommend and track additional high-quality prompts, improving brand visibility across offsite sources.