About the AI Learning Lab
The AI Hands-On Learning Lab is a monthly, guided exploration of technology tools with a focus on their AI capabilities. Each session spotlights a specific software and provides learners the opportunity to delve into its distinct AI features through hands-on exploration. The lab will also foster discussions on how these tools can be effectively used across workplace contexts - from getting the job, reducing friction in your workflow processes, and leveling up your learning design.
We will rotate through focusing on an AI tool through one of these three specific lenses:
About Jack and Jill
You might think of Jack & Jill as something along the lines of a job matchmaking service. It’s a dual-agent AI platform designed to transform how job search and hiring operate. It features specialized autonomous agents called Jack & Jill.
First, there’s Jack, who acts as a job seeker’s personal AI agent. Jack learned your skills, search job markets daily, and prepares you for interviews.
And then there’s Jill. Jill is a recruiter agent for employers, evaluating applicant pools and introducing top candidates directly to managers.
Jack & Jill goes beyond automation. The platform's real value is seeing how dual-agent architectures streamline candidate-recruiter matching by processing real-time profiles and criteria.
This Hands On AI Lab will mostly focus on Jack, with a brief cameo by Jill. What we will explore and evaluate together:
- Conversational Profiling vs. Resume Uploads. We’ll give it a try, testing how Jack conducts a 20-minute voice or text intake to extract your skills, values, and working preferences, and evaluating what the conversational AI capture.
- Automated Job Matching & Daily Sourcing: We’ll look at how Jack scans thousands of job listings across open markets, surfaces high-fit roles, and provides clear match rationale without you ever scrolling a job board.
- Agent-to-Agent Pitching: : We’ll see how candidate agent Jack pitches your profile directly to recruiter agent Jill—bypassing traditional application forms, ATS keyword filters, and resume black holes.
- AI Career Coaching & Benchmarking: Learn how Jack handles real-time salary benchmarking, career clarity coaching, mock interview preparation, and negotiation strategy tailored to your level and target roles.
- Recruiter Agent Intake & Matching: We’ll take a look at how employer agent Jill ingests hiring criteria from talent teams and scans Jack's candidate network to deliver warm, high-fit introductions directly to hiring managers.
- Practical Dissections & Friction Points: We’ll analyze where dual-agent matching speeds up hiring versus where it introduces friction—such as match accuracy issues, algorithmic bias, privacy concerns, and missing passive candidate pipelines.
Mary serves as the Vice President of Technology for ATD Central Mass. Currently an instructional designer at Boston Scientific, she holds an M.A. in Educational Technology Leadership from George Washington University and an additional M.A. in Teaching English to Speakers of Other Languages with a focus on adult learners from Teachers College, Columbia University. A technology evangelist and project management professional with extensive experience managing diverse learning and development projects in the northeast, as well as Russia, Pakistan, Kazakhstan, Azerbaijan, and Germany, Mary’s interests encompass adult learning, educational technology, task authenticity, learning transfer, competency-based learning, and culturally responsive practices. Her favorite instructional design model is SAM (with Dick & Carey close behind). Mary is particularly passionate about adapting learning design, instruction, and technology to enhance cultural relevance for target audience as well as implementing small moves to address performance gaps.
Capability Model - Technology Application, Lifelong Learning, Future Readiness
