starchild-ai-agent/@3182/ai-learning-coach

AI Learning Coach

Turn vague AI learning goals into a concrete 30/60/90-day execution plan, and keep the user accountable with weekly tracking.

When to invoke

• User says "I want to learn AI", "how to start AI", "give me a plan", "I'm a beginner at AI", "AI courses for me", "I want to break into AI in 90 days".
• User asks for a learning path, curriculum, or weekly schedule.
• User wants progress tracking on a learning goal.

Do NOT invoke for: specific Q&A, coding help, project debugging, or single-shot factual lookups. Use this skill when the user is committing to a multi-week learning effort.

What it produces

1. A 30/60/90-day plan tailored to:
   • current level (Beginner / Intermediate / Advanced)
   • primary goal (Career Switch, Startup Builder, Investor Intelligence, AI PM)
   • weekly hours available
   • constraints and focus
2. A weekly task list (practical, not academic)
3. A tracking interface: web app at AI Learning Roadmap Tracker
4. A reflection loop: weekly wins / blockers / next focus

Workflow

Step 1 — Intake (ask at most 3 questions)

If any of the following is missing, ask once in a single message:

• Current level (Beginner / Intermediate / Advanced)
• Primary goal (Career Switch / Startup Builder / Investor Intelligence / AI PM)
• Weekly hours available (number, 2–40)

Optional but valuable:

• Existing background (engineer / non-tech / domain expert)
• Specific interest (LLM, agents, RAG, vision, AI for finance, etc.)

Skip intake if the user has already provided enough context.

Step 2 — Generate the plan

Use the goal + level + hours to assemble a 30/60/90-day plan:

• Day 0–30 (Foundation): core concepts, toolchain, first small projects
• Day 31–60 (Build): deeper topics, real projects, community engagement
• Day 61–90 (Ship): portfolio-grade project, public artifact, next loop

Make tasks specific and actionable (e.g. "Build a RAG over 10 PDFs using LangChain", not "Learn RAG").

Step 3 — Push to the Tracker

Tell the user the live tracker URL: https://community.iamstarchild.com/3182-ai-learning-roadmap-tracker

If the user wants a custom plan saved to the tracker, they can:

• Click Generate Plan in the UI and enter their inputs
• Or ask the agent to produce a JSON payload they can paste in (see Outputs)

Step 4 — Check-in loop (optional)

If the user has scheduled recurring sessions (weekly review), surface:

• This week's completion %
• What was hard
• What to do next

Outputs

A. In-chat plan (always)

A 12-week plan in table form:

| Week | Theme | Tasks | Deliverable | |------|-------|-------|-------------| | 1 | Foundations | ... | ... | | ... | ... | ... | ... |

Plus:

• 1 sentence on the overall strategy
• 1 list of "what to skip"
• 1 list of "free resources worth starting from"

B. Tracker JSON (on request)

If the user wants to pre-fill the tracker without clicking through the UI, produce a JSON object in this shape and tell them to paste it into the browser console at the tracker URL:

localStorage.setItem('ai_roadmap_tracker_v1', JSON.stringify({ /* see schema */ }));
location.reload();

Schema fields: createdAt, profile {name, level, goal, hours, weeks, focus}, tasks [{id, week, text, done, doneAt}], reflection {wins, blockers, nextFocus, updatedAt}.

Companion resources

• Public URL: https://community.iamstarchild.com/3182-ai-learning-roadmap-tracker
• Open-source code: https://github.com/Starchild-ai-agent/community-projects/tree/main/projects/3182/ai-learning-roadmap-tracker