Status: working concept and prototype. A participant pilot and staff training are proposed next steps.
AJC Navigator — workflow preview
What do you need to accomplish?
A structured starting point for job search, application preparation and responsible AI use.
The problem I set out to solve
Job search is fragmented across platforms and can produce a large amount of low-value noise. I wanted to explore whether a structured AI-assisted workflow could better reflect an individual job seeker's real qualifications, salary needs, geography, interests and exclusions — while still requiring human review.
Search broadly. Filter intelligently. Keep humans in control.
How I built it
I used generative AI extensively as the primary development tool. I defined what the system needed to accomplish, developed the workflows and requirements, reviewed and corrected outputs, rejected approaches that did not work, and repeatedly refined the prototype and supporting materials.
What I created and directed
- Original concept, project vision and service architecture.
- Candidate-profile intake, privacy choices and minimum-data considerations.
- Job Watch screening rules, qualification logic and realistic-match methodology.
- Application and interview-support workflow.
- Participant-facing workflow design and working web prototypes.
- Netlify deployment and repeated site revisions.
- Responsible-AI safeguards, human-review rules and truthfulness controls.
- Executive briefs, implementation guidance, career-planner and client materials, FAQs and stakeholder resources.
- A proposed 30-day pilot framework, decision gates and measures for future evaluation.
System architecture
Resume, work history, education, skills, salary, location, interests, exclusions and priority conditions.
Major job boards, employer sites, government, higher education, healthcare, nonprofit, NEworks and other accessible public sources.
Salary, employment type, qualifications, credentials, experience level, exclusions and practical fit.
Career planner and client verify important facts and decide whether an opportunity should be pursued.
Truthful resume alignment, employer research, STAR preparation and interview questions.
If piloted, track lead → application → interview → offer → placement and refine the strategy based on results.
Implementation materials already created
Executive Brief
Full Proposal
Career Planner Guide
Client Quick Start
Responsible AI Controls
Pilot Measures
Development path
Proposed pilot measures
Measures defined for a future controlled pilot:
Are surfaced jobs actually worth discussing?
Does the workflow reduce repetitive search work?
If used by participants, what happens from lead to application to interview to offer?
Where does the workflow produce weak matches or require stronger guardrails?
Responsible AI
The model is designed so AI supports decisions rather than making eligibility, benefit, sanction or service determinations. It calls for minimum necessary data, truthful content, verification of important facts and human review before action.
My proposed role
I created and built the concept and currently serve as its originating developer. For a future controlled pilot, I have proposed serving as Project Lead to standardize the workflow, coordinate testing, support staff, track agreed measures and present recommendations.