AI in the Workplace · Eight Weeks · Live Online
Build the AI tools your team keeps asking for.
Eight weeks. Fully online. Two live sessions per week. AI in the Workplace is for early career professionals. If you are working now, you finish as the person on your team who builds the AI tools everyone else keeps asking for. If you are looking for work, you finish with five projects you can show, demo, and talk through in an interview.
You finish AI-fluent, with the work to prove it.
What you leave with
Five projects, and they are all yours to show.
- A prompt system you reuse every week, with a written reason each one works.
- A researched brief with every source checked.
- An AI assistant you built on a real set of documents, plus the test set that proves it works.
- An automation running in place of something you used to do by hand.
- A working web app, connected to live data, that you can explain line by line.
You also leave with a portfolio, a three-minute demo you have rehearsed, and a written policy on how you use AI.
Skills you can put on your resume
- Prompt engineering
- Context engineering
- RAG
- AI evaluation design
- Workflow automation
- AI agents
- Vibe coding
- AI-assisted development
- API integration
- MCP
- Responsible AI
- AI governance
How it works
Eight weeks, two live sessions a week.
You know what you are building and when you are done.
Fully online, applied from week one.
Every week you build something with current AI tools, based on work that turns up at real companies.
A coach, not a lecture hall.
You work with a coach on your own projects, at a pace that fits how you focus and process information.
Built for you from the start.
Fidgetech was founded for adults experiencing autism. We are expanding to welcome the broader community of neurodivergent learners.
Who this is for
Two doors, one program. Both run the same eight weeks.
You are working now.
You want to be the person who builds the thing, not the person waiting for someone else to build it. Every project uses work from the job you already have, so what you build in Week 5 can be running at work in Week 6. Your employer can sponsor your seat and be invoiced for it.
You are looking for work.
You need proof you can put in front of someone, not a certificate you can't demo. You build against a supplied case company in the industry you are targeting. Same eight weeks, same five projects, same portfolio. You can name every skill on your resume and show the work behind it.
The eight weeks
Each week you pick one project and build it.
| Week | Weekly project (choose one) | AI skills |
|---|---|---|
| 1Prompt engineering as a professional skillWrite structured, reusable prompts and explain why one works better than another. | A status update three audiences will read, meeting notes turned into action items, or a first-pass reply to a request that comes in every week. | Prompt engineering, system prompt design, few-shot prompting, prompt chaining, LLM fundamentals |
| 2AI-powered research and knowledge systemsRun AI research and check it well enough to put your name on it. | A competitor or vendor comparison, a background brief before a decision meeting, or a long report summarized for several audiences. | AI-assisted research, source verification, information synthesis, knowledge management |
| 3AI-assisted writing that still sounds like youDraft faster with AI without it reading like AI wrote it. | A dense internal doc rewritten for a general audience, a project update email, or documentation for a process only one person knows. | AI-assisted writing, content editing, voice and tone control, AI disclosure |
| 4Build your own AI assistant: context engineering and evalsBuild an assistant grounded in a real document set and test whether it actually works. | An onboarding assistant that answers new-hire questions from a set of team documents, a policy assistant, or a research assistant grounded in a body of material. | Context engineering, custom AI assistant development, RAG, eval design, AI testing |
| 5Workflow automation and AI agentsTake a manual recurring process, automate it, and explain the difference between a prompt, an assistant, and an agent. | The weekly report someone currently exports and emails by hand, a request intake that routes and notifies, or a recurring data pull that cleans and summarizes itself. | Workflow automation, AI agents, agentic workflows, data analysis with AI, automated reporting |
| 6Vibe coding: ship your first working toolScope and build a working app with AI, and read the code well enough to change it on purpose. | A tracker replacing a spreadsheet too many people now depend on, a team dashboard, a request and approval tool, or a handoff log. You keep this project through Week 7. | Vibe coding, AI-assisted development, code comprehension, product scoping, rapid prototyping, debugging with AI |
| 7Integrations, MCP, and shipping itConnect an AI tool to real data, put it in front of people, and say how it should improve. | Your Week 6 tool, connected to live data and running somewhere people can actually use it. | API integration, MCP (Model Context Protocol), deployment, feedback loop design |
| 8Portfolio, demo, and your AI playbookShow your work and describe it in the words employers and clients actually use. | Your five projects, written up with metrics, example resume updates, a three-minute demo, and your AI use policy. | Technical documentation, project storytelling, data storytelling, presentation skills, responsible AI, AI governance, AI risk assessment |
| Every weekAI governance practiceSay where you draw the line on AI, and why. | A running set of decisions that becomes your AI use policy. | Responsible AI, AI governance, AI risk assessment, data privacy, ethical decision-making |
1
Prompt engineering as a professional skill
Write structured, reusable prompts and explain why one works better than another.
A status update three audiences will read, meeting notes turned into action items, or a first-pass reply to a request that comes in every week.
Prompt engineering, system prompt design, few-shot prompting, prompt chaining, LLM fundamentals
2
AI-powered research and knowledge systems
Run AI research and check it well enough to put your name on it.
A competitor or vendor comparison, a background brief before a decision meeting, or a long report summarized for several audiences.
AI-assisted research, source verification, information synthesis, knowledge management
3
AI-assisted writing that still sounds like you
Draft faster with AI without it reading like AI wrote it.
A dense internal doc rewritten for a general audience, a project update email, or documentation for a process only one person knows.
AI-assisted writing, content editing, voice and tone control, AI disclosure
4
Build your own AI assistant: context engineering and evals
Build an assistant grounded in a real document set and test whether it actually works.
An onboarding assistant that answers new-hire questions from a set of team documents, a policy assistant, or a research assistant grounded in a body of material.
Context engineering, custom AI assistant development, RAG, eval design, AI testing
5
Workflow automation and AI agents
Take a manual recurring process, automate it, and explain the difference between a prompt, an assistant, and an agent.
The weekly report someone currently exports and emails by hand, a request intake that routes and notifies, or a recurring data pull that cleans and summarizes itself.
Workflow automation, AI agents, agentic workflows, data analysis with AI, automated reporting
6
Vibe coding: ship your first working tool
Scope and build a working app with AI, and read the code well enough to change it on purpose.
A tracker replacing a spreadsheet too many people now depend on, a team dashboard, a request and approval tool, or a handoff log. You keep this project through Week 7.
Vibe coding, AI-assisted development, code comprehension, product scoping, rapid prototyping, debugging with AI
7
Integrations, MCP, and shipping it
Connect an AI tool to real data, put it in front of people, and say how it should improve.
Your Week 6 tool, connected to live data and running somewhere people can actually use it.
API integration, MCP (Model Context Protocol), deployment, feedback loop design
8
Portfolio, demo, and your AI playbook
Show your work and describe it in the words employers and clients actually use.
Your five projects, written up with metrics, example resume updates, a three-minute demo, and your AI use policy.
Technical documentation, project storytelling, data storytelling, presentation skills, responsible AI, AI governance, AI risk assessment
Every week
AI governance practice
Say where you draw the line on AI, and why.
A running set of decisions that becomes your AI use policy.
Responsible AI, AI governance, AI risk assessment, data privacy, ethical decision-making
If you are working now, you bring the work. If you are not, you build against a supplied case company in the industry you are targeting.
How to start
$900 a month for two months.
That is $1,800 total for the full eight weeks. If you continue into a Code Certificate or a Design Certificate, the full amount is credited toward it. You are not paying twice to keep going.
Employers:you can sponsor a seat and be invoiced for it.
If cost is a barrier:talk to us. We will tell you what is possible.
Ready to register?
Join the next cohort of AI in the Workplace. Eight weeks, five projects, and the work to prove it. Seats are limited.
Register
Tell us a bit about you. We will follow up with everything you need to get started.
AI in the Workplace at a glance
- Program
- AI in the Workplace
- Length
- Eight weeks, fully online, two live sessions a week
- Built for
- Early career professionals who are neurodivergent, including adults experiencing autism
- Cost
- $900 a month for two months, credited toward a Code or Design Certificate if you continue
- Leads into
- Code Certificate, Design Certificate
Fidgetech was founded for adults experiencing autism. We are expanding to welcome the broader community of neurodivergent learners. AI in the Workplace was built for you from the start.