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Case study01 · OverviewCode District

From a topic to a ready-to-teach lecture.

An AI platform that turns a topic or course outline into a structured lecture educators can deliver — designed, built and shipped by a single engineer.

Client[Client name]
IndustryEducation technology
RoleSole engineer, full stack
TimelineJun 2026 — present

Serverless generation

Long AI jobs kept off the request path

Billing built in

Stripe plans live from launch

One engineer

Frontend, API, infra and payments

Case study02 · Solution & capabilities2 / 4
02
The solution

One step from topic to lecture.

Four manual steps collapse into one. Educators type a topic, and the platform hands back a structured lecture they can edit and deliver.

1Enter a topicOr paste a course outline
2Platform plans itOutline and sections drafted
3Edit and deliverEvery section stays editable

Key capabilities

What the product does

Lecture generator

Topic in, structured lecture out.

  • Split into clear sections
  • Runs as a background job

Course workspace

Where lectures live and get refined.

  • Group lectures by course
  • Edit any section after generation

Plans & billing

A paid product from the first day.

  • Stripe subscriptions
  • Usage tied to plan limits

Admin & usage

[What the admin side covers.]

  • [Capability detail]
  • [Capability detail]
Case study03 · Architecture & build3 / 4
03
Architecture

Fast requests. Heavy lifting in the background.

Next.js · NestJS · AWS Lambda · PostgreSQL · Stripe

Stripesubscriptions01Next.js web appEducators enter a topicand edit their lectures02NestJS API + AWS LambdaAPI answers fast; Lambdaruns the generation jobs03PostgreSQLCourses, lecturesand users

How it was built

Four steps to launch
1DiscoverHow educators prep today2ArchitectAPI split from generation3BuildGenerator, workspace, billing4Launch[Launch detail]

Challenges

Problem, then fix
Long generations vs. Lambda time limits[How you solved it]
Consistent output across topics[How you solved it]
Plan limits in sync with Stripe[How you solved it]
Case study04 · Results & impact4 / 4
04
Results

What it delivered.

[X min]to a full lecture
[X]lectures generated
[X%]less prep time
[X]paying accounts

Impact

Who it changed things for
For educators

Prep time back

[X hours] saved per lecture, spent teaching instead of formatting.

For the business

Revenue from day one

Paid plans live at launch through Stripe; [X] paying accounts so far.

For the product

Room to grow

Generation runs on Lambda, so busy periods don’t slow the app down.

“

[Client testimonial — one or two sentences on what changed for them.]

[Name, Role · Client]

One engineer shipped a production AI product — frontend, API, infrastructure and payments.

Mohammad Abdullah · Senior Software Engineer, Code DistrictStart a similar project