Vertical Series No. 01 · For business majors, all concentrations

This is not an AI course with business examples. It's an analyst engagement.

Eight weeks. One real company. You produce the research, the verified financials, the customer insight, the campaign, and a working automation — then defend your recommendation to a panel at Demo Day. No coding required.

Business students reviewing AI-built dashboards and market analysis together, with a panel presentation underway

Walk into your internship already
knowing how to do the job.

In week one you pick a real company — a public company you'll research deeply, or a live local business as your client. Everything you build for eight weeks compounds on it.

By Demo Day you don't have eight exercises. You have one coherent engagement: an intelligence system, verified analysis, customer insight, a campaign, an automation with production data — and a recommendation you can defend under questioning.

01 · The rule

AI use is unlimited — and fully disclosed. The graded skill is direction and verification, not typing.

02 · The ratio

20% instruction, 70% building, 10% presenting. Every session opens with a business problem, never a concept.

03 · The standard

Every number traced to a source. Every claim cited. Every limitation disclosed. Like the job.

Six deliverables that stack.

One portfolio, one real business — each deliverable builds on the last, which is why Demo Day feels like one engagement instead of eight assignments.

Week 1 · The foundation

Research Assistant + Engagement Charter

Before the deliverables: build your Market Research Assistant, learn why a blank chatbot fails, and pick the real company your whole engagement will run on. Everything below stacks on this choice.

1
Week 2

Company Intelligence Copilot

An AI system grounded in your company's real documents — filings, transcripts, reviews — that answers questions with citations, and says so when the answer isn't in the sources.

2
Week 3

Verified Financial Analysis Memo

AI reads the statements; you check the math. Two pages, a ratio panel, three flagged risks — every figure footnoted to its source, with a verification log.

↳ Built on the copilot's document base
3
Week 4

Customer Insight Dashboard + Data Story

Hundreds of reviews and survey responses turned into an honest dashboard and an 800-word insight narrative — including one finding that contradicts the obvious take.

↳ Cross-checked against the financials
4
Week 5

Brand-Voice System + Campaign Kit

Not ten generic AI posts — a reusable voice system derived from the company's real materials, executing a full campaign: ads, social, landing page, email, measurement plan.

↳ Aimed at the customer insight you just found
5
Weeks 6–8

Business Automation, in Production

A guarded automation that runs live for the final two weeks of the course. You present measured impact data — time saved, with the run log to prove it.

↳ Automating the workflow your engagement exposed
6
Week 8 · Demo Day

The Recommendation, Defended

A two-page recommendation memo answering your engagement's business questions — presented at a public Demo Day and defended in live Q&A before a panel that includes a business owner and someone who hires.

↳ Everything above becomes your exhibits

Eight weeks, week by week.

One 2.5-hour session per week plus ~2 hours of independent build time. Click any week.

Week 01

The Analyst's Copilot

+

"You have a case interview tomorrow: should Chipotle launch breakfast?" Learn why a blank chatbot fails, then build a reusable Market Research Assistant encoding real frameworks — and pick your focus company.

ShipsWorking research assistant + engagement charter
Week 02

Company & Competitive IntelligenceGraded audit №1

+

Ground AI in your company's real filings and transcripts. Then the first graded audit: classify ten AI "findings" as supported, distorted, or fabricated — with the source passage as proof. Build a cited competitive positioning table.

ShipsCompany Intelligence Copilot v1 + positioning table
Week 03

Financial Analysis, VerifiedGraded audit №2

+

AI narrates the 10-K; your spreadsheet checks it. Find five seeded errors in an AI-written financial summary — wrong growth rate, mixed fiscal years, invented segment figure. Then write your own memo where every number traces.

ShipsFinancial analysis memo + verification log
Week 04

Customer & Market InsightGraded audit №3

+

"The owner says people love us but complain about price. Is that what the data says?" Theme-code real review data with AI, hand-audit its coding, then catch a peer's AI-assisted analysis overclaiming — in writing.

ShipsInsight dashboard + data story draft
Week 05

Marketing & Brand Systems

+

Why ten AI posts in ten minutes are generic garbage — and what a professional builds instead: a brand-voice system derived from the company's real materials, executing a full campaign with a measurement plan that says what would kill it.

ShipsBrand-voice system + campaign kit
Week 06

Business Automation

+

Audit the workflows, pick the target, and launch a guarded automation — live before you leave the room, because it needs two full weeks of production runtime before Demo Day. Draft-don't-send is a hard rule for anything customer-facing.

ShipsLive automation + run log (clock starts now)
Week 07

Assemble & Harden

+

Everything becomes one engagement package, led by a two-page recommendation memo. Then real user testing — your client, or a peer playing the skeptical executive: "show me where that number comes from." Fix, guard, or disclose.

ShipsCapstone package v1, user-tested
Week 08

Demo Day

+

Seven minutes, then three of panel Q&A — with your copilot answering a panel question live and your automation's real production data on screen. The panel includes a business owner, faculty, and someone who hires.

ShipsFinal portfolio + "How I Built This" + AI-use disclosure

You are graded on catching AI's mistakes
because that's the skill employers can't find.

Three formal audits, spaced across the course. Each one plants real AI failures in front of you and scores whether you find them.

Audit №1 · Week 2

The Citations

Ten AI-generated findings about a real document set. Which are supported, which distorted, which entirely fabricated? Prove it with the source passage — or its absence.

Audit №2 · Week 3

The Math

An AI-written financial summary of a real filing with five seeded errors. Find the wrong growth rate, the mixed fiscal years, the invented figure — and correct them against the filing.

Audit №3 · Week 4

The Analysis

Swap datasets with a peer, run the same analysis, and identify where their AI-assisted conclusions overclaim what the data can support. Adjudicated by the instructor.

Try it now: one of these findings is fabricated.

An AI summarized the annual report of Cascade Coffee Co. (a practice company from the course). Two findings below are supported by the report. One is entirely invented. Click the fake.

Résumé bullets with receipts.

Excerpt · After completing AI for Business

Selected Experience

  • Built a document-grounded AI research copilot for [company], answering diligence questions with citations across 10-K filings and earnings transcripts.
  • Produced a verified financial analysis — ratio panel and risk flags with every figure traced to source — and a customer-insight dashboard from 300+ reviews.
  • Shipped a guarded LLM automation that ran in production for 2 weeks, saving [X] hrs/week — impact data logged and presented to a business panel.
  • Delivered and defended a growth recommendation before a panel including the business's owner.

A case-interview story that's true

The Demo Day memo is a ready-made "walk me through an analysis you've done" answer — with exhibits.

Claims you can defend live

Panelists ask "where does that number come from?" — and tracing it on the spot is part of your grade. Interviews feel familiar after that.

Every concentration

The engagement flexes to your focus:

ManagementMarketingFinanceAccountingEntrepreneurshipSupply ChainBusiness Analytics

If you can build a slide deck, you can take this course

No coding, no CS prerequisite. An optional Builder Track rebuilds your copilot and automation in Python for those who want the technical depth.

One curriculum, four formats.

FormatDurationScope
Weekend Intensive2 daysResearch copilot + competitive intelligence + a compressed campaign sprint
Analyst Core4 weeksWeeks 1–4: copilot, verified financials, insight dashboard
Full Engagement8 weeksThe complete arc as described, with production automation and Demo Day
Semester Elective14–16 weeksFull engagement + a second client cycle and deeper Builder Track

Frequently asked

No. The default path is entirely no-code — assistants, projects, spreadsheets, Looker Studio, and Zapier free tiers. The optional Builder Track rebuilds your copilot and automation in Python for students who want it, framed as "rebuild it properly."

Our rule is the inverse of most classrooms: AI use is unlimited and fully disclosed. What's graded is direction and verification — three of your grades come specifically from catching AI being wrong. An undisclosed fabricated figure is an integrity failure; a disclosed limitation is professionalism.

Any public company with deep documentation works — you'll research it like a diligence analyst. Where possible we pair students with live local or campus businesses, whose owners join Demo Day as your client.

Analytics is one week of this course. The engagement spans research, financial analysis, customer insight, marketing systems, and automation — the actual breadth of a junior business role — with AI as the through-line and verification as the standard.

Founding-cohort pricing and the first calendar are being finalized now. Requesting a seat puts you first in line and includes an invite to a free AI Career Copilot mini-workshop.

Run your first engagement.

Request a seat for the founding cohort — the calendar is announced to this list first. Priority goes to students who tell us the company they'd want to analyze.