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About the BootCamp

Alex Rivera

CS junior at Foothill — building AI tutors that actually push back

Foothill College · Computer Science · class of 2027

Interning at Viva · Growth engineering intern · since Jun 15, 2026

Dream career

Founding engineer at a small AI startup that ships things people actually use.

What I'm working toward

I'm a CS junior at Foothill, six months into seriously using AI in my workflow and trying to figure out what "good" actually looks like. This summer I'm interning at Viva — a small AI startup doing customer ops automation. My main goal: ship one feature end-to-end and learn what the rhythm of a small engineering team really feels like. Beyond the internship, I'm investing in three things: • Picking up enough Rails + Postgres to be useful on a Ruby codebase • Getting comfortable with evals + measuring AI quality, not just vibes • Talking to founders/PMs at small startups — I want to understand the actual job before I commit to chasing it What I'm still trying to figure out: am I more excited by deep technical depth or by the messier early-stage product problems? Probably both, but the proportion still feels uncertain.

Résumé

Open alex-rivera-resume.pdf in a new tab ↗

AI Fluency BootCamp

  • M1
    Prompt design for real internship workCompleted May 19, 2026 · v1
  • M2
    Picking the right toolCompleted May 22, 2026 · v1
  • M3
    Verifying what AI gives youCompleted May 26, 2026 · v1

Verified skills

  • AI Skills
    How a student designs prompts, picks tools, verifies outputs, builds evaluation, and integrates AI into real work. The most prominent skill area in the CareerLauncher brand.
    No evidence yet
    Sub-skills (5)
    • Prompt design
      Writes prompts that are scoped, contextualized, structured, and iterative.
      1 evidenceBasic
    • Tool selection
      Picks the right tool for the task. Knows when to use AI and when not to.
      1 evidenceBasic
    • Verification
      Treats each AI output as a draft. Checks sources, runs the code, catches hallucinations. Per-instance, ad hoc.
      1 evidenceBasic
    • Evaluation
      Builds and runs systematic tests of AI behavior. Detects regressions, compares models. System-wide, repeatable.
      none
    • Workflow integration
      Knows where AI saves time and where it slows down. Integrates AI as augmentation, not replacement.
      none
  • Writing & Communication
    Structure, audience awareness, brevity, technical-to-non-technical translation.
    No evidence yet
    Sub-skills (0)
    • Data Skills
      Spreadsheet fluency, SQL, statistical literacy, visualization, ML basics.
      No evidence yet
      Sub-skills (0)
      • Workplace Navigation
        Asking for help, communicating up, reading the room, handling disagreement, ownership.
        No evidence yet
        Sub-skills (0)

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