1. What are the three tools that make up Nia's minimum viable AI stack, and what is the combined monthly cost?
Right — ChatGPT Plus for content and communication, Tidio free for customer interaction automation, Canva free AI for visual assets. $20/month total. The lesson uses Nia's setup as the definition of minimum viable.
The lesson walks through Nia's stack specifically: ChatGPT Plus at $20/month, Tidio on the free tier, and Canva's free AI features. Total: $20/month. One Sunday afternoon of setup, all three pillars covered.
2. Jordan's most valuable realization while using AI to prepare for Amara's feedback conversation was:
Right. The AI didn't generate that insight. Writing the situation out honestly forced Jordan to examine his own framing.
The key insight was Jordan's own — surfaced by the process of articulating the situation, not generated by the AI. That's the real use case: AI as a forcing function for clearer thinking.
3. Under GDPR, what triggers the requirement for a Data Processing Agreement?
Any time EU personal data is shared with a third-party processor — including AI vendors — a DPA is required under GDPR. The data's geographic path is less relevant than the act of sharing it with a third party.
GDPR's DPA requirement is triggered specifically by the act of sharing personal data with a company that processes it for you. The AI vendor that handles your EU customer inputs is a data processor under this definition.
4. A pilot ends with the team reporting they "never really used it." The tool performed well in the few cases where it was used. The business owner asks you to explain what went wrong. Your honest answer is:
This is the most common pilot failure mode, and the lesson names it clearly. If the tool works when used but isn't being used, the problem is adoption — insufficient training, no structured encouragement to change habits, no one accountable for making the new workflow normal.
If the tool performed well in the cases where it was used, it's not a tool, scope, or process failure. The failure is adoption — which is a human change management problem, not a technology problem. Different tool, same outcome without the human dynamics addressed.
5. What does "feature inflation" describe in the AI vendor market?
Feature inflation means the label "AI-powered" now appears on tools ranging from genuinely sophisticated LLM integrations to basic autocomplete. The term has been diluted to near-meaninglessness in marketing contexts.
Feature inflation is specifically about how the "AI" label gets applied to tools that may not meaningfully use AI — because the label itself increases marketing conversion rates.
6. What is the primary reason AI tools have narrowed the content marketing gap between small businesses and larger competitors?
Correct. The volume gap — not the quality gap — is what AI primarily closes. A solo founder with AI tools can now match the content output of a small team, which changes the competitive dynamic for organic marketing.
The lesson is explicit: quality still matters, and human creativity still wins on originality. What AI closes is the volume gap — the ability to produce consistent content without a team.
7. A small business owner calculates that an AI tool saves 8 hours per month, their time is worth $25/hour, the subscription costs $60/month, and setup takes 10 hours amortized over 12 months ($208/year ÷ 12 = ~$17/month). What is the monthly net value?
8 hours × $25 = $200 value created. Minus $60 subscription and minus ~$17 amortized setup cost = $123 net monthly value. This is the TCO calculation in action — always include setup cost amortized over expected use period.
Run the full calculation: time value minus subscription minus amortized setup. All three inputs belong in the math. The answer that includes all three costs correctly is $123.
8. Which type of AI hiring tool carries the highest bias risk and why?
Correct. Scoring communication style, tone, and demeanor introduces cultural and socioeconomic bias — and employers typically can't inspect the scoring rubric.
Conversational AI screeners evaluate subjective personality signals — communication style, demeanor, tone — that carry significant cultural variation and bias risk. And you usually can't see how they're scored.
9. What is the primary purpose of the Day 2 "no prompt adjustment" rule in the 5-day trial protocol?
Day 2 is your baseline. Day 3 is your optimized performance. The delta between the two tells you how much the tool depends on your prompt skill versus its own underlying capability — both useful data points.
The protocol is designed to generate two distinct data points: how the tool performs by default, and how it performs after tuning. You can't get both if you optimize on Day 2.
10. A business's workflow map shows that "supplier reorder emails" score 5/5 on repeatability and 1/5 on relationship sensitivity. What does this mean for AI prioritization?
Right. Maximum repeatability + minimum relationship sensitivity is the sweet spot. This is exactly the kind of task that frees up human time without any meaningful risk to relationship quality. It should be at the top of the priority stack.
The two-axis framework gives a clear answer here: 5/5 repeatability and 1/5 relationship sensitivity is an ideal AI candidate. Revenue, company size, and workflow complexity don't change that fundamental score.
11. Why is safety stock sized to lead time variance rather than lead time mean?
Exactly. Safety stock is insurance against the unexpected. If you only plan for the average, you'll be fine on average and out of stock whenever actual lead time exceeds the mean — which happens regularly with high-variance suppliers.
Safety stock exists to protect against the times things don't go as expected. The mean tells you the expected case. Variance tells you about the bad cases — exactly the scenarios safety stock is designed to absorb.
12. Which of these job description requirements is most likely to function as credential inflation?
Right. A degree requirement for a barista role has no demonstrated connection to performance — it's a credential that filters by background, not ability.
The bachelor's degree requirement for a barista is the textbook example of credential inflation — an arbitrary requirement that screens by background rather than predicting actual job performance.
13. You're preparing to terminate an employee after three documented performance warnings. Which use of AI is appropriate?
Right. Preparation — structure, anticipating questions, reviewing documentation — is the appropriate lane for AI in termination. The decision and the conversation are yours.
AI is appropriate for preparation: drafting the conversation structure, anticipating likely questions, reviewing your documentation. It cannot make or validate the termination decision.
14. Which content zone represents the highest volume multiplier for small business operators?
Yes. Zone 3 is where one blog post becomes seven pieces of content across formats. That's the multiplier — not generating from scratch, but reformatting existing content for each platform's grammar.
Zone 3 — repurposing — is where the volume multiplier is greatest. One blog post can become five captions, an email subject line, a TikTok script, and a Pinterest description. That's the 1-to-7 ratio described in the lesson.
15. Priya's chatbot achieved 68% containment but created a new problem. Which of the following accurately describes what happened?
Right. Partial automation can shift — not just reduce — problems. Priya's situation shows why good escalation design matters even when containment rates are high.
Priya's issue was specifically about escalation experience quality, not about accuracy or whether automation was net-negative overall.
16. Which of the following is NOT one of the five components recommended for a strong AI cash flow prompt?
Credit score and borrowing history aren't part of a cash flow projection prompt — they're relevant for loan applications, not forward-looking cash analysis. The five components are: starting balance, expected income with timing, known expenses with timing, outstanding receivables, and upcoming irregular expenses.
Credit score is relevant for financing decisions, not cash flow projections. The five prompt components are: current balance, expected income with timing, known expenses with timing, outstanding receivables and due dates, and upcoming irregular or large expenses.
17. What does the rule of thumb "track the work, not the person" mean for employee GPS monitoring?
Correct. The principle distinguishes legitimate work coordination from continuous surveillance — the latter being both a legal issue and a trust violation.
"Track the work, not the person" means GPS is appropriate during work hours for coordination — not running continuously including off-shift hours.
18. Priya didn't read the terms of service for her AI tool and discovered her mental health community's posts may have been used for model training. What category of data use does this describe?
Training data use means content is contributing to improving or retraining the AI model — distinct from simply processing an input to generate a response and then discarding it.
These three categories are meaningfully different. Content being used to improve the model itself is training data use — separate from how the model uses your input in real time to generate an output.
19. A business pays $20 flat shipping per order and orders $60 worth of product each time. What is their shipping cost as a percentage of order value, and what strategy might reduce it?
Right. $20 / $60 = 33.3%. That's an enormous overhead per order. EOQ analysis would almost certainly recommend much larger, less frequent orders to spread that fixed cost over more units.
$20 ÷ $60 = 33%. Every order carries a 33% shipping tax. EOQ would likely recommend consolidating into larger orders — the ordering cost is high relative to order size, which pushes the optimal quantity up significantly.
20. What is value-based pricing, and how does it differ from cost-plus pricing?
Right. Cost-plus is internally driven (your costs + markup). Value-based is externally driven (what does the customer gain from this?). For a funded startup client, a logo that builds credibility and drives users could be worth $5,000 even if it costs you $400 in labor. Value-based pricing captures that gap.
The fundamental difference is the starting point. Cost-plus: start with what it costs you, add margin. Value-based: start with what it's worth to the customer. In service businesses especially, the customer's value from the outcome can be far higher than your cost to produce it, creating room for much higher prices.