Agent skill · writing content · erichowens
tech-presentation-interview
Prepares for "reverse system design" rounds where you present YOUR past technical work. Use for project selection, narrative arc structuring, whiteboard diagrams, depth calibration, and hostile
Why this skill is useful
Provides structured frameworks for project selection and presentation that the AI wouldn't reliably generate on its own.
What it needs
About 8k tokens when loaded. Last updated 2026-07-14. 180 stars on the source repository.
What this skill does
Tech Presentation Interview The tech presentation round is a reverse system design: instead of designing a hypothetical system on a whiteboard, you present a real system YOU built. This tests three things no other round can: genuine depth of understanding, ability to communicate complex ideas under pressure, and authentic ownership versus inherited knowledge. When to Use Use for: Selecting which project to present from your career Structuring a 25-45 minute technical presentation with narrative arc Calibrating depth -- which components to go deep on, which to skim Preparing whiteboard/virtual-board diagrams with progressive disclosure Rehearsing answers to hostile follow-up questions Adapting presentation to different audience compositions (researchers, engineers, managers) NOT for: Designing a system you haven't built (use ml-system-design-interview) Writing your resume or extracting career stories (use cv-creator or career-biographer) Coordinating across multiple interview rounds (use interview-loop-strategist) Practicing coding problems or behavioral STAR stories Conference talk preparation (different format, different evaluation criteria) --- Project Selection The most common failure mode is choosing the wrong project. Use this decision tree: Selection Criteria Scorecard Rate each candidate project 1-5: Criterion Weight What to evaluate ----------- -------- ------------------ Personal ownership 5x YOUR decisions, not team consensus or inherited architecture Technical complexity 4x Non-obvious tradeoffs, scale challenges, algorithmic depth Interesting failures 4x Things that broke, surprises, pivots, lessons learned Relevance to role 3x Overlaps with what the target team builds Quantified impact 2x Metrics you can cite (latency, throughput, revenue, accuracy) Recency 1x More recent is better, but a great 5-year-old project beats a boring recent one Threshold: Total score > 60 = strong choice. 40-60 = acceptable if nothing better. < 40 = find another project. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills erichowens/tech-presentation-interview