Video script

10.Video/script.md

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+
+# Video script
+
+
+## AI Script
+
+Creating a 5-minute video that presents a new software architecture using Amazon's "working backwards" principle involves focusing on customer needs and clearly explaining how the architecture addresses these needs. Here’s a structured guideline for your video:
+
+We are internal architects, trying to sell the idea to our own business.
+
+**How to make:** ask AI to create small chunks of a video.
+
+
+## [Opening Scene – 0:00-0:30]
+
+Visuals: Engaging animation or graphics showing a customer-focused environment
+
+Narrator:
+"Welcome to [Your Company/Team Name], where innovation is driven by your needs. Today, we unveil our latest software architecture designed to transform how you [specific benefit related to the architecture]."
+
+- intro to AI
+- people working --> machines working, people service machines
+
+
+## [Scene 1: Define Customer Needs – 0:30-1:00]
+
+Visuals: Customers facing challenges, infographics highlighting pain points
+
+Narrator:
+"Before we started designing, we asked ourselves: What are the biggest challenges our customers face today? We listened to [specific problems] and identified key areas for improvement: [list 2-3 major pain points]."
+
+Quote from CEO: "Change is hard on its own, and keeping the grading quality consistent while hanging is even harder."
+
+On-screen text: Key customer pain points
+
+- static scale up 5-10x, impossible with current resources
+- dynamics of scale up fast enough (hiring, reduced bandwidth while growing, smooth transition)
+- keep consistent quality while changing the business
+- paying for the scale up, margins are thin at the moment
+- heard about AI but how to make it happen consistently, reliably, maintaining the control?
+
+
+## [Scene 2: Present the Solution – 1:00-2:30]
+
+Visuals: Transition to technical diagrams, flowcharts of the new architecture, animations demonstrating core features
+
+Narrator:
+"Our response is a groundbreaking software architecture that [briefly describe the core function]. By leveraging [mention any technologies, e.g., microservices, cloud computing], we've built a system that is [mention key attributes like scalable, secure, efficient]."
+
+Technical Explanation:
+
+Scalability: "Our architecture scales effortlessly with your business, thanks to [specific technology or method]."
+Security: "Security is foundational, with [describe security features]."
+Performance: "Optimized for speed and reliability, our system delivers [describe performance benefits]."
+Interview Clip:
+Lead Architect (on-screen):
+"This architecture allows us to integrate seamlessly with existing systems and adapt to future needs, ensuring your operations are always at the forefront of innovation."
+
+--------
+
+- general approach 1: AI is good at simple tasks, bad at complex tasks
+- general approach 2: divide and conquer, split grading into simple tasks and handle each one separately
+- general approach 3: ensure highest grading quality locally (per-task) and globally (per-applicant)
+
+- tasks: a question or a grading aspect of task 2
+- keep a larger pool of questions or grading dimensions than necessary, to enable smooth rotation
+- AI task workflow:
+    1. introduce a new task or a new grading dimension
+    2. deploy to a small share of students and grade manually
+    3. deployment eval: run AI system in parallel until it reaches "X" performance metric; do prompt tuning at same time
+    4. switch grading to AI; if AI system never stabilizes then goto 6
+    5. continuous eval: keep manually grading a small part of submissions, check AI system performance over time
+    6. sunset: obsolete question or poor AI performance --> replace question with another
+- global system eval:
+    1. send 5% students to manual evaluation
+    2. 4% are with the largest AI uncertainty (sample from the decision boundary of Certifiable Inc "function")
+    2. compare per-task performance and whole system performance
+    3. investigate differences, add new questions of grading aspects that open up these differences
+- question variations: propose few different formulations for the same question, grade with the same AI system
+- fraud detection
+
+
+## [Scene 3: Customer Impact and Testimonials – 2:30-3:30]
+
+Visuals: Happy customers using the new system, graphs showing improvement metrics
+
+Narrator:
+"The impact? [Specific benefit] for our customers. Here’s what a few of them have to say."
+
+Customer Testimonial Clips:
+
+Customer 1 (on-screen): "With [software name], we've seen a [specific improvement], making our workflow smoother and more efficient."
+
+Specific improvements:
+
+- prompts to check for specific parts in the solution document
+
+
+Customer 2 (on-screen): "The transition was seamless, and the support has been exceptional."
+
+- transition with shifting one question at a time
+- use historical evals to test model performance
+
+
+## [Scene 4: Architecture Details & Trade-Offs – 3:30-4:30]
+
+Visuals: FAQ list, roadmap timeline with future features
+
+Narrator:
+"We know you have questions. Here are some we’ve anticipated and addressed:"
+
+On-screen text:
+
+"How does it integrate with existing platforms?"
+"What is the cost structure?"
+"What support is available?"
+Narrator:
+"And we’re not stopping here. Our roadmap includes [mention upcoming features or enhancements]."
+
+
+## [Closing Scene – 4:30-5:00]
+
+Visuals: Company logo, contact information, call to action
+
+Narrator:
+"Thank you for joining us on this journey. We’re excited to continue working with you to create the future of [industry or specific area]. For more information, visit [website/contact info]. Let’s build the future together."
+
+This structure ensures that the video remains customer-focused, aligning with the "working backwards" principle while providing enough technical depth to convey the significance and capabilities of the new software architecture.
+
+
+- info about our team