Video summary

It took me 8+ years to learn what I'll tell you in the next 15 minutes

Main summary

Key takeaways

Educational

Main Ideas, Concepts, and Lessons

  • Long-term payoff from learning to code

    • The speaker frames their journey as taking 8+ years, beginning with learning to code and culminating in:
      • a VC-backed tech startup
      • an office in “dream city Toronto”
      • alongside Formula 1 driver Jack Doohan (mentioned as a key connection/association)

  • Start with foundational web technologies

    • Early languages/projects:
      • HTML
      • CSS
      • JavaScript
    • Where they learned it:
      • a high school Grade 10 “Introduction to Computer Science” course
    • First project:
      • a simple GTA-style adventure made for a preschool kid (class final project)

  • Recommendation for beginners: use structured courses + learn by building

    • Suggested approach:
      • take a beginner JavaScript course
      • build a React portfolio app to showcase projects
    • Core lesson:
      • The only real way to get better at coding is to build something (“get your hands dirty”)

  • Use project-based learning to accelerate skill

    • Key claim:
      • improvement comes from hands-on building, not just reading/watching
    • Practical methodology:
      • Search Google for: “project-based learning GitHub”
      • Click the first link
      • Use projects as templates to build your own hands-on experience (example given: JavaScript)

  • A major early mistake: delaying coding to focus only on grades

    • The speaker didn’t code after high school until their first university year.
    • They prioritized GPA/grades and assumed hiring would follow automatically.
    • Result:
      • couldn’t find jobs / no interviews, despite top performance

  • Career lesson: networking is essential

    • Process described:
      • used connections, career fairs, and coffee chats
      • eventually got a referral
    • Outcome:
      • first internship: Software Developer for the Government of Canada (remote), about $26/hour
    • Takeaway:
      • “Your network is your net worth”
      • first job can change everything
      • ask for referrals and talk to people even if the market is weak

  • Level-up phase: targeting big-tech readiness through projects + DSA/interview prep

    • What changed in second/third year:
      • researched what big tech expects
      • learned LeetCode (they admit they didn’t know it yet)
    • Credibility-building project:
      • Fantasy Premier League match predictor (React app)
      • later expanded into a points predictor and integrated into the React app
    • Interview outcomes:
      • an Amazon take-home with a LeetCode-style setup; they say they bombed it
    • Tool to recover:
      • neetcode.io for roadmaps, solutions, and videos (used to learn what they were missing)

  • Persistence after not getting targeted big-tech that year

    • They applied widely (200–300 applications) but didn’t land the internships they wanted.
    • Still, they got a good job:
      • Company: TRC
      • Wage: $38/hour
    • Implication:
      • progress can come from adjacent roles even if they aren’t your ultimate target

  • Teaching others publicly can unlock opportunities

    • They mention creating a full tutorial for backend building of a project.
    • Claim:
      • recruiters found it, leading to a subsequent internship.
    • Speaker-to-speaker moment:
      • they show a clip asking whether, with AI, you can still write from scratch; the other person responds “No. No way.”
    • Big-tech internship project (Autodesk):
      • McGill exam scheduler backend project
      • real impact:
        • thousands of users at McGill
        • users could add exam schedules to Google Calendar
        • motivation: handling huge exam PDFs and figuring out exam times/locations
      • interview leverage:
        • they say Autodesk (and later Amazon) valued identifying problems and building scalable solutions

  • Backend stack: Java + Spring Boot

    • Learned:
      • Java
      • especially Spring Boot
    • Why it matters:
      • widely used in big tech; the speaker claims Amazon legacy systems rely heavily on it (around 80%)
    • Resources mentioned:
      • Amigos Code (YouTube) for Spring Boot, including JWT authentication and practical details
      • FreeCodeCamp Java tutorial (2023) for backend login/registration concepts

  • Build “next caliber” projects

    • Workflow/method:
      • use build-your-own-x prompts on vercel.app
      • after learning a language (example: Java), build more intensive projects such as:
        • a 3D renderer
    • Purpose:
      • deeper engineering practice and moving to the “next level”

  • Broader project examples that show impact

    • Canadian Space Agency
      • satellite collision predictor
      • alerting system sending text alarms when collision risk crosses a threshold
    • First startup (resume differentiator):
      • Empore, Canada’s student-exclusive marketplace
      • achievements:
        • McGill Sustainability Grant (~a couple thousand dollars)
        • ~5,000 users at McGill
        • thousands of dollars in sales
      • tech stack:
        • React Native + Expo Go
        • scaled with a Spring Boot backend
      • interview impact:
        • speaker claims it impressed recruiters and helped lead to Amazon

  • Explicit interview strategy (methodology / list)

    • For internship/job applications:
      • applied to around 350 software engineering internships in fourth year
    • Technical prep cheat-code:
      • go to shaunprashad.com/leetcodedpatterns
      • search by company (example: Amazon)
      • use “recently asked interview questions” to practice ahead of time
    • Behavioral interview structure:
      • use STAR method:
        • Situation
        • Task
        • Action
        • Result
      • tie answers to:
        • coding projects/experience and impact
        • why you fit the company’s leadership principles

  • Amazon internship details and tradeoffs

    • Location:
      • Amazon office in Toronto
    • Return-offer goal:
      • worked 9am–6pm daily, aiming for a return offer
    • Tech:
      • Java and TypeScript
      • learned AWS CDK (infrastructure as code)
    • Limitation:
      • internal tools, not user-facing—less progression toward high-impact, user-scale work
    • Outcome:
      • still received a return offer
    • Feeling:
      • elation at reaching “big tech job” level

  • From internship success to startup building

    • After Amazon, they wanted:
      • the feeling of building something impactful again
      • to ship something that generates revenue
    • Built product: ResumeMax
      • started as an AI resume generator
      • evolved into an all-in-one AI job-search tool:
        • tailor resumes per role
        • find roles worth applying to
        • track which resume versions lead to interviews
        • negotiation support to reduce “left money on the table”
    • Metrics stated:
      • 16,000 users
      • $18,000 revenue and counting
      • $1,300 monthly recurring revenue (MRR)

  • Building in public and VC/founder-level opportunity

    • Built in public attracted Jack Duan
    • Conversation + pivot:
      • discussed what was then Palm Shop, now Muse
    • Decision:
      • turned down the Amazon return offer after receiving the official email (around March, during an LA trip)
      • chose to go all-in on the startup
    • Current commitment:
      • “16 hours of work every single day”
      • excitement and confidence in the decision

Methodology / Instructions Presented (Detailed)

How to improve coding fast

  • Build something continuously (the speaker calls this the “only way”)
  • Track activity/examples (they cite GitHub contributions as evidence)

Project-based learning approach (practical steps)

  • Search Google for: project-based learning GitHub
  • Click the first link
  • Pick a language listed there (example: JavaScript)
  • Build a project hands-on to gain experience

How to get first job/internship (networking steps)

  • Exhaust connections
  • Attend career fairs
  • Do coffee chats
  • Ask for referrals
  • Keep talking to people you know, especially during a weak job market

How to prepare for big-tech technical interviews

  • Use a company-focused practice pattern source:
    • visit shaunprashad.com/leetcodedpatterns
    • search your target company (example: Amazon)
    • practice solutions to recently asked interview questions
  • Goal:
    • reduce surprise during the interview

How to answer behavioral interviews

  • Use the STAR format:
    • Situation
    • Task
    • Action
    • Result
  • Connect your stories to:
    • coding projects/impact
    • alignment with the company’s leadership principles

How to build “next caliber” projects after learning a language

  • Go to build your own x.vercel.app
  • Choose projects matching the level of the language you just learned
  • Example:
    • build a 3D renderer
  • Goal:
    • deeper engineering skills than basic tutorials

Speakers / Sources Featured (as Mentioned)

Speaker / primary source

  • The video narrator / main speaker (no name provided in subtitles)

People mentioned as interviewers or collaborators

  • Jack Doohan (Formula 1 driver; associated with the speaker’s world/company)
  • “Chris” (in a clip: “Can you still write from scratch with AI?” → “No. No way.”)
  • “Eric” (referenced as “old Eric” who teaches building something; last name not given)

Educational / content sources

  • Programming with Mosh (JavaScript beginner course; YouTube)
  • NeetCode.io (roadmaps + solutions + videos for LeetCode-style problems)
  • Amigos Code (YouTube channel for Spring Boot learning)
  • FreeCodeCamp (Java tutorial referenced for backend login/registration)
  • shaunprashad.com/leetcodedpatterns (practice resource for company-focused questions)

Sponsorship / product source

  • Higgsfield (sponsor; includes workflow with Claude and MCP)
  • Claude (AI model/tool used with Higgsfield)
  • MCP (mentioned as “Higgsfield’s new MCP”)
  • Vercel (implied by build your own x.vercel.app)

Organizations / projects mentioned

  • Government of Canada (internship)
  • Amazon (internship / return offer)
  • Autodesk (internship via McGill exam scheduler)
  • TRC (job after unsuccessful big-tech internships hunt)
  • McGill (users/context for exam scheduler; also Empore)
  • Canadian Space Agency (satellite collision predictor project)

Original video