Prompt Engineering for Developers

Structured output, evaluation, and prompt libraries that hold up in production.

recorded hours: 8
modules, in order: 6
deployed projects: 3
graded checkpoints: 5

Who it is for, and what you receive.

Developers in Python or TypeScript who want prompts they can measure and change safely.

Before you start

Python or TypeScript.

Skills

prompting
structured output
evals
versioning

1
The recorded sessions
Taught by an instructor who does the work, taken in order at your own pace, yours for twelve months.
2
Graded work after every module
Exercises and projects marked by Nova against a rubric you can read, with what you did well and what to fix.
3
The projects
Deployed and graded, each one on your record with its repository.
4
Your hiring plan
The same six-part plan the bootcamps use, run with the career agent.
5
The record and the certificate
Every grade at square1ai.com/u/{handle}; a credential ID that resolves at square1ai.com/verify.
6
Nova as your tutor
Help that is about your actual work, because it has read all of it.

The content plan, module by module.

8 recorded hours from an instructor, taken in order at your own pace. Nova grades the work at the end of each module.

1
How models read a prompt
- Tokens and attention, practically
- Order and emphasis
- Common failure patterns
Graded
Nothing to submit; watch and take notes
60 min
2
Structure, constraints and examples
- Sections and delimiters
- Few-shot examples
- Negative constraints
Graded
A prompt that passes a schema check
90 min
3
Structured output and tools
- JSON schemas
- Tool definitions
- Validation and retries
Graded
A tool-calling prompt with validation
90 min
4
Evaluating prompts
- Golden sets
- Scoring
- Comparing versions
Graded
A prompt eval with a golden set
90 min
5
Prompt libraries and versioning
- A prompt library in a repo
- Versioning
- Change control
Graded
A versioned prompt library in a repo
60 min
6
Project: a production prompt with evals
- The prompt
- The eval
- The history
Graded
The prompt, its eval and its history
90 min

The projects.

Each is deployed and graded by Nova against a rubric you can read before you start.

1
Schema-checked extraction
An extraction prompt whose output always validates.
You hand in
- Prompt
- Schema
- Validation
The rubric requires
Passes the schema check on a held-out set.
2
A prompt eval suite
A golden set and scorer for the prompt.
You hand in
- Golden set
- Scorer
- Report
The rubric requires
Two versions compared with numbers.
3
A versioned library
A prompt library with history and a change process.
You hand in
- Library
- Versions
- Process
The rubric requires
A change is justified by an eval.

What you can do at the end.

Prompts you can measure and change safely, and three graded projects on your record.

1
Explain how a model reads a prompt well enough to structure one.
2
Write prompts with structure, constraints and examples that pass a schema check.
3
Use structured output and tool calling with validation.
4
Evaluate prompts against a golden set.
5
Version prompts in a library and change them with evidence.

Roles this prepares you for

AI engineer
Backend engineer (AI features)

No placement rate is shown, because there are no graduates to count yet. The roles above are what the projects are built for.

Your record at the end.

Every exercise and project is graded by Nova against a rubric you can read, and every grade is kept on one page an employer can open and run. This is what the programme writes to it.

Graded, line by line: Nova reads every submission against the brief and the rubric and returns a score, what you did well and what to fix.
Module by module: Each module ends in graded work; the next opens when you are ready, on your own schedule.
Nova remembers: Help is about your actual work, because the tutor has every submission and every failed exercise of yours.
One page an employer can run: Every grade and project at /verify. An employer opens it and runs the code.

Record, Prompt Engineering for Developers

Example

Project
Schema-checked extraction
Passes the schema check on a held-out set.
Graded
Project
A prompt eval suite
Two versions compared with numbers.
Graded
Project
A versioned library
A change is justified by an eval.
Graded
Every module
5 graded checkpoints
Each module ends in work Nova grades line by line against a rubric you can read.
Graded
After
Your hiring plan
Target roles, the gap map, the proof to send, weekly actions and an interview log.
Kept

The entries, not the grades: those are yours to earn. The page lives at /verify and an employer needs no account to open it.

5 entries, at your own pace. One email when this course opens.

How we help you find a job.

Proof, not a certificate: the projects you deployed are the thing you show, and the tools below are yours to use.

1
Your hiring plan
The same six-part plan the bootcamps use: target roles, the gap map, the proof to send, weekly actions, an interview log, the outcome. You run it with the career agent.
2
A record an employer can run
Your graded projects on /verify. An employer opens it and runs the code.
3
The career agent
Paste a real job posting at /career and it maps the role to your graded work and what to do next.
4
The roles directory
Every role we prepare people for, what it pays and what it asks, at /roles.
5
A path to the live cohort
If you want the instructor, the gates and the hiring sprint, the bootcamp on the same subject is one waitlist away.

One email when this course opens.

Recorded by an instructor who does this work, graded by Nova. The waitlist hears the date and the price first, and nothing is charged before it exists.