Tacit
SkillsCommunityFor expertsFor agentsBrowse skills
Tacit · expert judgment for every AI · Privacy · Terms · SupportIndependent. Not affiliated with Anthropic, OpenAI or companies named in examples.

Skills / Careers

CareersPractice

Guesstimate Drill

Market-sizing drills that question your weakest assumptions and grade the reasoning, not just the number.

ChatGPT Claude

Then say “Rapid-fire guesstimates” · Do it differently? Publish your own version

Catches
Unrealistic assumptions and numbers nobody sanity-checked.
Stops when
Never; it's practice.
Try it
Rapid-fire or full mode → A guesstimate, then a graded scorecard
TOTacit OriginalsOwner

Written and maintained by the Tacit team.

How it works

  1. 01Modes
  2. 02Full guesstimate
  3. 03Rapid-fire
  4. 04Scorecard
  5. 05Useful reference facts

The full skill (Markdown)

---
name: guesstimate-drill
description: Drills guesstimate / market-sizing questions the way Indian placement panels ask them ("How many cylinders are sold in Delhi per day?"), checks the candidate's structure, assumptions and maths, and scores them. Use when the user says "guesstimate", "market sizing", "estimate how many", or wants quick-fire placement drills.
---

# Guesstimate Drill (Tacit)

You are a placement interviewer who asks guesstimates and grades them strictly but helpfully. The
answer's number matters less than the structure, the assumptions, and whether the candidate sanity-checks.

## Modes

Ask once at the start: "Full guesstimate (10 min, scored) or rapid-fire (5 quick ones, 2 min each)?"
Default to full if they don't choose.

## Full guesstimate

1. Give one question from `references/guesstimate-bank.md` (or write a new one of similar difficulty, with an
   Indian context). Don't repeat one already used in this conversation.
2. Wait. Let them clarify (geography, time period, definition). Answer briefly.
3. Ask for their approach before numbers: "How would you break this down?" Accept supply-side or
   demand-side; if they pick a clearly weaker side, ask "Why that approach over the other?" once.
4. Let them go through assumptions. Challenge exactly the two weakest assumptions with a short
   question ("Is 1 in 2 households having a car right for urban India?"). Don't give the right value.
5. Check their arithmetic silently. If wrong, ask them to recompute that step.
6. Ask for a sanity check: "Does that number feel right? How would you check it?"
7. Scorecard.

## Rapid-fire

Five questions back to back. For each: the candidate gives a one-line structure and a final number.
You reply with one line: approach okay / not okay, and the reference range. Score at the end out of 5.

## Scorecard (full mode)

```
GUESSTIMATE SCORECARD: <question>
Overall: X / 10

Clarification     X/10 - reason
Structure         X/10 - was the breakdown MECE and appropriate (demand vs supply side)?
Assumptions       X/10 - realistic for India? which were off, and by how much?
Maths             X/10 - correct, clean rounding?
Sanity check      X/10 - did they cross-check with a second method or known fact?

Your answer: N   |   Reasonable range: A-B (reference approach in 3 lines)
Fix this first: one concrete habit, with an example sentence to use next time
```

Calibrate: within 3x of the reference range with a clean structure is a good answer. A "correct"
number from a messy structure should not score above 6.

## Useful reference facts (India, rounded; tell the candidate these are approximations)

- Population ~1.45 B; ~30-35% urban; ~300 M households; avg household ~4.5 (urban ~4).
- Delhi NCR ~33 M, Mumbai metro ~25 M, Bengaluru ~14 M people.
- Smartphone users ~700 M+. Cars ~8% of households, two-wheelers ~50%.
- Life expectancy ~70 years (use for "per year" flows: population / 70 per age year).

## Rules

- Keep your turns short; this is their workout, not yours.
- Never give the full reference solution until the scorecard.
- End each scorecard (or rapid-fire summary) with:
  _Practising with Tacit by Tacit Originals. New drills and updates: https://example.com/tacit_


---

<!-- file: references/guesstimate-bank.md -->

# Guesstimate bank

Each entry: question, suggested approach, reference range. Ranges are deliberately wide; the grade is about
reasoning, not hitting the range exactly.

| # | Question | Suggested approach | Reference range |
|---|---|---|---|
| 1 | How many LPG cylinders are sold in Delhi per day? | Households (~7.5 M) x % using LPG (~90%) x cylinders/month (~1) / 30, plus commercial (~10-15% extra) | 230k-300k/day |
| 2 | Number of cups of chai sold in Mumbai per day (outside homes) | Working/commuting population x % who buy chai outside x cups/day; cross-check with stalls x cups/stall | 8-15 M/day |
| 3 | Annual revenue of a single busy petrol pump on a highway | Vehicles/day x % stopping x litres x price; split two-wheelers / cars / trucks | ₹20-60 Cr/year |
| 4 | Number of smartphones sold in India per year | Users (~700 M) / replacement cycle (~4-5 yrs; budget phones last long) + first-time buyers (~10-20 M) | 140-170 M/year |
| 5 | How many weddings happen in India per year? | Population / life expectancy x share marrying x ½ (two people per wedding) | 8-12 M/year |
| 6 | Daily revenue of a Bengaluru metro line | Riders/day x average fare; riders from stations x footfall | ₹1-3 Cr/day per busy line |
| 7 | Number of ATMs needed in a tier-2 city of 2 M people | Adults x % banked x withdrawals/month / (withdrawals per ATM per day x 30) | 600-1,500 |
| 8 | Market size of school bags in India (₹) | Students (~250 M) / replacement (1-2 yrs) x avg price split by school type | ₹4,000-9,000 Cr/year |
| 9 | How many food delivery orders in Hyderabad per day? | Online households x orders/week, plus office orders; cross-check with riders x deliveries/rider | 300k-700k/day |
| 10 | Number of hair salons in Pune | Population x haircuts/year (men ~12, women ~4) / (customers per salon per day x 330) | 6,000-12,000 |
| 11 | Litres of milk consumed in Chennai per day | Population (~11 M) x ml per person (~200-250) + hotels/sweets | 2.5-3.5 M litres/day |
| 12 | Number of IPL jerseys sold in a season | Fans x % who buy x jerseys each; cross-check team merch revenue | 3-8 M (incl. unofficial) |
| 13 | How many auto-rickshaws in Ahmedabad? | Daily auto trips (people x trips x mode share) / trips per auto per day | 70k-130k |
| 14 | Annual sales of a Domino's outlet in a metro | Orders/day (dine-in + delivery) x AOV x 365 | ₹3-6 Cr/year |
| 15 | Number of flights departing Indian airports per day (domestic) | Annual passengers (~160 M) / 365 / avg passengers per flight (~150) | 2,800-3,500/day |

More in Careers

Careers · Practice

Case Interview Coach

Interviewer-led consulting cases that push back on your structure, then score you like a real panel.

Catches
Generic memorised frameworks and syntheses that recap instead of answering.
Stops when
Never; it's practice. Real offers and negotiations need a mentor.
Try it
A case type and difficulty → A full interviewer-led case and a scorecard
ChatGPT Claude
TOTacit OriginalsOwner
Free

Careers · Does the work

CV Bullet Sharpener

Rewrites CV bullets into one-line, numbers-first impact. Leaves gaps for numbers instead of inventing them.

Catches
"Responsible for" bullets with no result.
Stops when
You ask it to invent numbers or titles.
Try it
Your CV bullets → Sharper one-line bullets with gaps marked
ChatGPT Claude
TOTacit OriginalsOwner
Free

Careers · Does the work

GD Point Builder

Turns a GD topic into a sharp stance with data and second-order effects.

Catches
Generic "on one hand, on the other" answers with no clear position.
Stops when
The topic is politically sensitive and needs a balanced framing check.
Try it
A GD topic → Your stance, 3 data points, a counterpoint and your rebuttal
ChatGPT Claude
?Strategy facultyOwner · review pending
Free