Why this exists
Students in Digital Media Arts complete career readiness work across the semester, resumes, job research, networking plans, interview practice, but when Canvas access ends at graduation, all of that work disappears. Render gives students a single personal learning environment they build themselves and take with them, organized around six areas that map directly to course competencies.
The framing is connectivism in practice. Render is the student’s personal learning environment (PLE), a space they own where learning, goals, and connections live in one place rather than scattered across a course that ends. The tool is built in Claude as a single HTML file with no server dependencies. All student data stays on their device, anonymous by design, with no student PII ever entering AI. AI assistance is embedded into each workflow, not as a blank prompt, but as structured coaching tied to the student’s own goals and one real reach job.
And Render does not get replaced by a separate career agent at the end. Render builds the agent. The career agent and personal learning plan are Render’s capstone export, the final layer of the same environment the student has been growing all semester.
The arc: a PLE that builds your agent
From day one to take-with-you
1 · Day one. Inside Render, the student sets robust goals, guided by the right questions, and picks one real reach job as their anchor. Everything that follows aligns to that anchor.
2 · All semester. Render runs alongside the whole AVC 248 capstone as the student’s launchpad, profile, goals, job log, resume vault, skills tracker, networking, and interview prep, every module aligned to that one reach job.
3 · Capstone. At the end of the course, Render analyzes the gap between what the student has actually built and what that reach job requires, then generates a portable personal learning plan and career agent, a Markdown file aligned to the goals they set on day one, which they keep iterating.
4 · Take-with-you. The student leaves with Render itself, their data and dashboard, exportable and owned, and the agent and learning plan, which runs in any AI tool they choose (Claude, ChatGPT, and others).
One big version of Render, the PLE, with the agent and personal learning plan as the final export. The environment builds the thing the student carries forward.
Latest feature · text preview, screenshots coming
Career Agent and Personal Learning Plan
The capstone layer, and the heart of Render. After a semester of building, Render runs a gap analysis between everything the student has actually made (profile, goals, saved jobs, resume drafts, skills, networking, and interview practice) and the requirements of the one real reach job they chose on day one.
From that gap it generates a portable personal learning plan and career agent as a Markdown file: a study plan with modules, applied tasks, and a self-assessment checklist, all aligned to the goals the student set at the start. The student downloads it and runs it in any AI tool they choose (Claude, ChatGPT, and others), and keeps iterating it as their career develops after graduation.
Render does not get replaced by the agent. Render builds it. It is generated from the student’s own anonymous data, with no personally identifiable information entering AI. Screenshots of this panel will be added after the Fall 2026 pilot.
What students build
Profile, Goals & Search Strings
Students define their dream job, creative identity, target market, and 3-year vision. The AI generates ready-to-paste search strings for LinkedIn, Indeed, and Glassdoor based on their specific goals and field.
Job & Client Log
Students paste job descriptions and receive AI-driven skills gap analysis, tailored cover letters, and career positioning advice. A freelance track generates prospect lists and outreach strategies. Entries feed Career Services via an automated pipeline.
Resume Vault
Four-draft revision workflow with instructor feedback integration. AI generates targeted resume edit suggestions tied to each saved job’s specific requirements, not generic advice, but edits grounded in the actual posting.
Skills & Professional Development
Software stack mapping across six categories (~60 tools), plus professional skills and industry knowledge surfaced from saved job postings, things like project management, creative briefs, production workflows, and client communication. AI gap analysis, named learning resources, portfolio project ideas, and a PD activity log that tracks growth throughout the semester.
Networking & Interview Prep
Contact log with outreach tracking and AI-drafted LinkedIn messages personalized to each connection. Role-specific interview questions generated from saved job descriptions, answer practice with AI coaching feedback, and Big Interview integration.
Launch Plan, Career Agent & Export
The capstone layer. Render analyzes the gap between what the student built and their day-one reach job, then generates a portable career agent and personal learning plan, a Markdown file aligned to the goals they set at the start, alongside a personalized 90-day PD plan and weekly schedule. The whole dashboard exports as a standalone HTML file the student keeps forever, no login, no server, no Canvas dependency, and the agent runs in any AI tool they choose. Render does not get replaced by the agent. Render builds it.