Scenario

You are a software engineer supporting a new AI technique and must plan the technical marketing for a developer-facing blog post and launch.

Tasks

1. Discovery and Scoping
   • What discovery questions will you ask internal teams before drafting the blog? Consider: target users, jobs-to-be-done, problems solved, baselines, latency/accuracy goals, and usability outcomes.
2. Developer Persuasion Beyond Performance
   • How will you convince developers to adopt the technique beyond raw performance numbers? What product aspects do developers care about most?
3. Evidence for Usability Claims
   • If an engineer claims the feature improves usability, what evidence and measurements will you require?
4. Developer-Experience Metrics and Instrumentation
   • Propose concrete DX metrics (e.g., task effectiveness, task efficiency/clicks, onboarding time, code reduction, reliability/crash rates, satisfaction/NPS, adoption/WAU) and how to instrument them.
   • Illustrate how you would measure them for:
     1. A consumer app (e.g., streaming video).
     2. An ML framework (e.g., training/inference library).
5. Additional Blog Angles and Proof
   • What additional angles would you cover—observability (profilers/flame graphs), learnability (documentation burden), security (data-leakage risks)—and what proof would you include?
6. Competitive Comparisons
   • Should you publish competitive comparisons against a rival accelerator vendor? If so, what standards will you require for transparency, legal review, reproducible scripts, and respectful positioning?