Skill: conn-ho/startup-risk-radar (version 1.0.0)

--- name: startup-risk-radar description: Evaluate startup ideas, business models, and product strategies against the 7 deadly failure antipatterns extracted from 1,749 dead startups that burned $535B+. Use when the user is evaluating a startup idea, planning a new product, reviewing a business model, assessing competitive positioning, checking unit economics, or asking "will this work?" Also trigger when the user mentions startup risk, failure patterns, competitive moat, unit economics, burn rate, market need validation, regulatory risk, founder conflict, product-market fit concerns, or pivot decisions. Provides structured risk assessment, red flag identification, and actionable recommendations based on real failure data. --- # Startup Risk Radar — Failure Pattern Analysis Framework from 1,749 dead startups and $535.4B burned capital. Source: loot-drop.io ## The 7 Antipatterns | # | Antipattern | Emoji | Deaths | Capital Burned | Median Life | % of All | |---|-------------|-------|--------|---------------|-------------|----------| | 1 | The Hallucination (No Market Need) | 🔮 | 203 | $14.9B | 3 yr | 11.6% | | 2 | The Bonfire (Ran Out of Cash) | 🔥 | 205 | $285.0B | 4 yr | 11.7% | | 3 | The Civil War (Founder Conflict) | ⚔️ | 13 | $2.5B | 4 yr | 0.7% | | 4 | The Crushed (Competition) | 🏴 | 901 | $43.5B | 3 yr | 51.5% | | 5 | The Lemon (Product/Tech Failure) | 🍋 | 70 | $15.7B | 5 yr | 4.0% | | 6 | The Outlaw (Legal/Regulatory) | ⚖️ | 86 | $67.9B | 7 yr | 4.9% | | 7 | The Math Problem (Unit Economics) | 📉 | 269 | $105.8B | 5 yr | 15.4% | ## How to Use This Skill ### When evaluating a startup idea or business model: 1. Read `references/antipatterns.md` for detailed pattern descriptions, mechanics, cognitive traps, and red flags 2. Read `references/chain-reactions.md` for how antipatterns cascade into each other 3. Score the idea against all 7 antipatterns using the assessment questions below 4. Identify the most likely failure cascade 5. Provide actionable recommendations ### Quick Assessment (7 Questions) For each antipattern, evaluate the startup on a 3-point scale: 🟢 Low risk / 🟡 Medium risk / 🔴 High risk 1. **🔮 Hallucination**: Do potential customers pull out their wallets unprompted, or just say "sounds interesting"? 2. **🔥 Bonfire**: If fundraising stopped tomorrow, could you reach profitability in 6 months? 3. **⚔️ Civil War**: Do co-founders have a clear decision-making process for disagreements? 4. **🏴 Crushed**: Is your roadmap driven by unique customer insights or by matching competitor features? 5. **🍋 Lemon**: Can your core tech deliver at production scale without manual intervention? 6. **⚖️ Outlaw**: Would full regulatory compliance destroy your unit economics? 7. **📉 Math Problem**: At current fully-loaded costs + 25% improvement, do margins exceed 20%? ### Output Format Structure your analysis as: ``` ## Startup Risk Assessment: [Name/Idea] ### Antipattern Scorecard [Score each of 7 antipatterns: 🟢/🟡/🔴 with brief justification] ### Primary Risk: [Most dangerous antipattern] [Detailed analysis of the most likely failure mode] ### Cascade Risk: [Chain reaction path] [How the primary risk could trigger secondary failures] ### Red Flags Detected [List specific red flags from the antipattern framework] ### Recommendations [Actionable steps to mitigate identified risks] ``` ### Key Statistics by Sector Most dangerous sectors (by total failures): - Communication Services: 444 failures - Consumer: 414 failures - Information Technology: 402 failures - Financials: 156 failures Most common cause of death: - Competition (51.5%) — over half of all startups die from being outgunned - Unit Economics (15.4%) — the math never worked - Ran Out of Cash (11.7%) — spending as if revenue is a formality - No Market Need (11.6%) — building for a customer that doesn't exist

path: references/chain-reactions.md
content: # Antipattern Chain Reactions

Antipatterns are not isolated — they form a system. One failure mode triggers another.

## The 3 Deadly Cascades

### 1. The Hallucination Spiral
🔮 Hallucination → 📉 Math Problem → 🔥 Bonfire

You built something nobody wants. To manufacture demand, you pour money into customer acquisition. CAC climbs while LTV stays flat. You're bleeding cash to acquire customers who don't really want what you're selling. The cascade ends when capital and narrative credibility are exhausted simultaneously.

**Example arc**: Build product → polite interest but no urgency → spend heavily on sales/marketing to create demand → unit economics worsen → burn through cash → die.

### 2. The Siege
🏴 Crushed → 📉 Math Problem → 🔥 Bonfire

You launched into a market that looked open but was a killing field. To survive competition, you drop prices, offer custom features, spend heavily on marketing. Competitors do the same — race to the bottom. Gross margins compress, sales cycles lengthen. You're losing the competitive battle while burning cash to stay in the fight.

**Example arc**: Enter market → underestimate competition → price war → unit economics destroyed → cash depleted → die.

### 3. The Slow Bleed
⚖️ Outlaw → 🔥 Bonfire → ⚔️ Civil War

You built in a regulated industry. The 7-year median lifespan means years of grinding regulatory war. Legal fees and compliance infrastructure consume cash instead of product and growth. Burn rate becomes unsustainable. In the final stage, founders fracture over whether to pivot, fight, or shut down.

**Example arc**: Regulatory ambiguity → grow → regulatory pressure → legal costs drain cash → co-founders disagree on response → team fractures → die.

---

## Connection Map (All Pairwise Relationships)

### 🔮 Hallucination triggers:
- → 🔥 Bonfire: No market need is a slow-burning fuse to cash depletion. Without genuine demand, you burn reserves manufacturing traction that never materializes organically.
- → 📉 Math Problem: When solving a problem people don't urgently need, CAC skyrockets while LTV craters. You end up paying to convince people they have a problem.
- → 🏴 Crushed: Building for a theoretical customer while competitors iterate with real users. By the time you recognize the real problem, they own the solution space.
- → 🍋 Lemon: Without real market feedback, product development becomes unmoored. Features built on assumptions rather than usage data.

### 🔥 Bonfire triggers:
- → 🔮 Hallucination: Aggressive spending masks lack of product-market fit. When spending millions on sales/marketing, you can't tell if customers buy because you solved a real problem or because you made it cheap enough to say yes.
- → 📉 Math Problem: You know unit economics are broken but convince yourself scale will fix it. Cash runs out before the math starts working.
- → 🏴 Crushed: You see competitors raising large rounds, so you match their burn rate. Mutual assured destruction where everyone spends unsustainably.
- → ⚔️ Civil War: When runway gets short, founders split between cutting burn vs. spending aggressively. Financial pressure reveals fundamental strategic disagreements.

### ⚔️ Civil War triggers:
- → 🔥 Bonfire: Duplicated efforts, contradictory initiatives, executive paralysis. Runway disappears while you fight internally.
- → 🔮 Hallucination: Internal warfare blinds you to market signals. Optimizing for winning internal arguments rather than serving customers.
- → 🏴 Crushed: While consumed by internal conflict, competitors execute with unified focus. Best talent leaves for sane work environments.
- → 🍋 Lemon: Competing technical visions lead to architectural inconsistency. Engineering receives contradictory priorities.

### 🏴 Crushed triggers:
- → 🔥 Bonfire: Competition forces escalating spending on customer acquisition, feature parity, and market defense.
- → 📉 Math Problem: Competitive pressure compresses prices, increases CAC, prevents operational leverage. Competition ensures you never reach profitable scale.
- → 🔮 Hallucination: What appears as competition failure often masks market need failure. When customers easily switch, the underlying issue may be insufficient urgency.
- → 🍋 Lemon: Must simultaneously match competitors, maintain quality, and innovate — with limited resources. Forces technical debt and quality compromises.

### 🍋 Lemon triggers:
- → 🔮 Hallucination: When tech can't deliver, you reframe as "customers don't understand the value." Blame market education rather than admitting technical impossibility.
- → 🔥 Bonfire: Each failed attempt to fix core product requires another engineering cycle, another rebuild, another 6 months of runway.
- → ⚔️ Civil War: Team splits between those who see technical reality and those who can't admit it. Engineers want to pivot; founders want one more attempt.
- → 📉 Math Problem: Workarounds to make broken product function (manual processes, custom solutions per customer) destroy cost structure.

### ⚖️ Outlaw triggers:
- → 🔥 Bonfire: Legal fees, compliance costs, and frozen operations drain capital. Impossible to raise new funding once investigations become public.
- → 📉 Math Problem: Unit economics that only work through regulatory arbitrage. Compliant version reveals the business was always The Math Problem in disguise.
- → 🏴 Crushed: Incumbents lobby regulators to shut down threatening startups. Compliance weaponized as competitive moat.
- → ⚔️ Civil War: Founders fracture over whether to pivot to compliance, fight regulators, or shut down. Existential stress of potential criminal charges.

### 📉 Math Problem triggers:
- → 🔥 Bonfire: Broken unit economics makes cash burn terminal. Without sound economics, you must raise perpetually until capital markets close.
- → 🔮 Hallucination: Negative unit economics often signals customers don't value your solution enough to pay what it costs to deliver.
- → 🏴 Crushed: When competitors also have broken economics, sector enters subsidy war. Company with most capital wins temporarily but nobody achieves sustainable profitability.
- → ⚔️ Civil War: As math problem becomes undeniable, founders fracture between those who want radical restructuring and those who believe one more quarter of optimization will work.


path: references/antipatterns.md
content: # The 7 Startup Failure Antipatterns — Detailed Reference

## Table of Contents
1. [The Hallucination — No Market Need](#1-the-hallucination--no-market-need)
2. [The Bonfire — Ran Out of Cash](#2-the-bonfire--ran-out-of-cash)
3. [The Civil War — Founder Conflict](#3-the-civil-war--founder-conflict)
4. [The Crushed — Competition](#4-the-crushed--competition)
5. [The Lemon — Product/Tech Failure](#5-the-lemon--producttech-failure)
6. [The Outlaw — Legal/Regulatory](#6-the-outlaw--legalregulatory)
7. [The Math Problem — Unit Economics](#7-the-math-problem--unit-economics)

---

## 1. The Hallucination — No Market Need
🔮 203 startups | 11.6% of failures | $14.9B burned | 3yr median lifespan

### The Pattern
Building for a customer that does not exist. You solve a problem that sounds important in pitch decks but generates no urgency in the real world. The median 3-year lifespan reveals the insidious nature: you can raise money, build product, hire teams, and operate for years while the fundamental truth remains hidden — nobody actually needs to change their behavior to adopt what you've built.

### The Mechanics
- **Stage 1 — Validation Illusion**: Customer interviews where people nod along. Politeness mistaken for demand. Letters of intent that require no behavior change.
- **Stage 2 — Launch Paradox**: Initial signups feel encouraging but activation rates are puzzling. Users don't come back. You blame messaging, pricing, features — anything except the core hypothesis.
- **Stage 3 — Pivot Carousel**: Changing everything around the solution already built. Each pivot buys another 6 months of runway and hope.
- **Stage 4 — Terminal**: Capital and narrative credibility exhausted simultaneously. Quibi burned $1.75B in 2 years.

### The Cognitive Trap
Confirmation bias is primary. Once committed, every ambiguous signal gets interpreted as validation. Sunk cost fallacy compounds: the more you've built, the harder to admit the foundation is wrong. Solution-oriented thinking, celebrated in engineering culture, becomes toxic — so focused on building something elegant that you never verify whether its absence causes anyone pain.

### Red Flags
- Customer interviews end with "sounds interesting, let's stay in touch" but nobody asks when they can start or pulls out a credit card
- More slide decks explaining why the problem matters than users who changed their workflow
- Sales pipeline full of eternal pilots — prospects willing to test but never to buy
- Constantly explaining the problem before pitching the solution
- User activation and retention metrics are dismal but you blame onboarding friction
- When you lose deals, the objection is "timing" or "priority" (polite ways of saying it doesn't matter enough)
- Team debates what the product should do more than analyzing what users actually do with it

---

## 2. The Bonfire — Ran Out of Cash
🔥 205 startups | 11.7% of failures | $285.0B burned | 4yr median lifespan

### The Pattern
Spending as if the money will never run out. Venture capital creates a buffer that insulates from market feedback. Confusing capital in the bank with product-market fit. The pattern is especially deadly in Consumer (58 failures), Communication Services (34), and Industrials (27).

### The Mechanics
- **Stage 1 — Honeymoon**: Large round closed, hire aggressively, lease premium office, launch in multiple markets. Each expenditure feels justified in isolation.
- **Stage 2 — Treadmill**: Growing, but not as fast as burn rate. Revenue increasing, but so are costs. Managing to runway rather than profitability.
- **Stage 3 — Scramble**: 6-12 months of cash left, funding environment shifted. Layoffs, spending cuts, extending runway while trying to show growth.
- **Stage 4 — Terminal**: 3-6 months left, down-round negotiations, every conversation about survival. Cost structure can't be unwound fast enough.

### The Cognitive Trap
Sunk cost fallacy married to optimism bias. Spent $50M building team and product, so cutting burn feels like admitting failure. The VC model reinforces this: investors funded you to be aggressive, and pivoting to capital efficiency feels like breaking the social contract. Spending feels like progress.

### Red Flags
- Can articulate monthly burn rate instantly but need to check dashboard for last month's revenue
- Financial planning organized around fundraising milestones rather than profitability
- Hired multiple people for roles only necessary at 10x current scale
- Board meetings focus on metrics needed for next round rather than sustainable unit economics
- Cut runway estimate twice in past 6 months without changing spending trajectory
- When someone suggests cutting costs, immediate response is it would "slow growth"
- Spending on brand marketing, office perks, conference sponsorships while CAC payback exceeds remaining runway

---

## 3. The Civil War — Founder Conflict
⚔️ 13 startups | 0.7% of failures | $2.5B burned | 4yr median lifespan

### The Pattern
The company becomes a battleground for competing visions, egos, and control. Two co-founders who complemented each other in early days discover fundamentally incompatible views once real money enters the picture. What made you a great founding team in a garage becomes toxic in a 50-person company with $20M in the bank.

### The Mechanics
- **Stage 1 — Silent Divergence**: Co-founders stop finishing each other's sentences. Decisions that once took minutes now require days.
- **Stage 2 — Shadow Organization**: Each founder builds their own faction. Two competing strategies executed simultaneously.
- **Stage 3 — Breaking Point**: Critical decision forces conflict into the open. Legal letters drafted, equity disputes surface.
- **Stage 4 — Terminal**: Board forces someone out, but damage is done. TuSimple burned $1B over 9 years; Bitmain destroyed $750M over 11.

### The Cognitive Trap
Fundamental attribution error: attribute co-founder's changed behavior to character flaws rather than changed context. Commitment bias keeps you fighting. Sunk cost of the relationship makes walking away feel like admitting failure.

### Red Flags
- Same strategic argument for the third time this quarter with no resolution
- Started selectively sharing information with co-founder
- Employees asking which founder to listen to
- Board meetings require pre-meetings to negotiate united front
- More time thinking about co-founder's motives than thinking about customers
- Key hires quit citing "cultural issues" or "lack of direction"
- Consulted a lawyer about founder equity or control issues

---

## 4. The Crushed — Competition
🏴 901 startups | 51.5% of failures | $43.5B burned | 3yr median lifespan

### The Pattern
The single deadliest antipattern — over half of all failures. Not about competitors existing, but fundamentally misunderstanding your competitive position. Especially lethal in Communication Services (257) and Information Technology (251) where network effects create winner-take-most outcomes. 3-year median lifespan: long enough to raise multiple rounds, not long enough to achieve needed scale.

### The Mechanics
- **Stage 1 — Competitive Underestimation**: Identify a wedge, build it, get early traction, raise capital.
- **Stage 2 — Environment Shifts**: Incumbent bundles your feature at zero marginal cost, or better-funded competitor launches with your roadmap plus $50M in marketing.
- **Stage 3 — Response Phase**: Accelerate development, match features, increase marketing. Playing their game on their terms. Burn rate increases while differentiation decreases.
- **Stage 4 — Terminal**: War of attrition you cannot win. Competitors outspend you indefinitely.

### Key Insight
"If your competitive advantage requires you to execute perfectly while competitors execute poorly, you do not have an advantage."

### Red Flags
- Product roadmap primarily reactive — matching competitor features rather than unique insights
- Celebrate winning individual deals but win rate is declining and each deal requires more discounting
- More time in competitive analysis meetings than talking to customers about unsolved problems
- Customers evaluate you and competitors as interchangeable, deciding on price or existing relationships
- CAC increasing quarter over quarter fighting better-funded competitors
- Pivoted positioning multiple times in response to competitive pressure
- Defensibility answer relies on "execution speed" rather than structural advantages (network effects, switching costs, proprietary data)

---

## 5. The Lemon — Product/Tech Failure
🍋 70 startups | 4.0% of failures | $15.7B burned | 5yr median lifespan

### The Pattern
Promising what the technology fundamentally cannot deliver. Not about missing features or bugs — about core technical impossibility masked by optimism. Early prototypes work under controlled conditions, giving just enough evidence to believe the next iteration will solve fundamental constraints.

### The Mechanics
- **Stage 1 — Promising Prototype**: Demo works in the lab with curated data or manual intervention. Raise on the promise.
- **Stage 2 — Scaling Hell**: System breaks at volume, accuracy degrades, unit costs make profitability impossible. Hire more engineers, refactor.
- **Stage 3 — Admission Spiral**: Best engineers say the core approach is flawed. You replace or ignore them.
- **Stage 4 — Terminal**: Run out of runway, technical pivots, and investor patience simultaneously.

### Key Insight
"A demo that works in the lab is not a product that works at scale; the gap between them is where most technical founders die."

### Red Flags
- Best engineers proposing fundamental architecture rewrites rather than feature additions
- Customer pilots succeed only when your team is heavily involved
- Constantly moving goalposts on core performance metrics
- Product roadmap in "almost ready for scale" mode for over a year
- Pivoted to different use cases because the technology keeps failing original requirements
- Demos require specific conditions to work; actively avoid showing edge cases
- Gap between marketing claims and actual product delivery keeps widening

---

## 6. The Outlaw — Legal/Regulatory
⚖️ 86 startups | 4.9% of failures | $67.9B burned | 7yr median lifespan

### The Pattern
Building in regulatory gray zones, betting you can become too big to shut down. The longest median lifespan (7 years) — you invest prime career years building something regulators will eventually erase. The larger you grow, the bigger target you become. Most vulnerable sectors: Financials (20), Communication Services (15), Consumer (14).

### The Mechanics
- **Stage 1 — Honeymoon**: Launch in regulatory ambiguity. Nothing happens. Silence interpreted as permission.
- **Stage 2 — Warning Shot**: Regulator sends inquiry, competitor gets shut down elsewhere. You tell yourself your situation is different.
- **Stage 3 — Siege**: Formal investigations, subpoenas. Media shifts from fawning profiles to exposés. Management bandwidth consumed by legal defense.
- **Stage 4 — Terminal**: Cease-and-desist orders, asset freezes, criminal charges.

### Key Examples
Wirecard ($28B), Ezubao ($7.6B), Thodex ($2B), FTX ($1.8B) — even massive scale provides no immunity.

### Red Flags
- Pitch includes "regulatory arbitrage" or "deal with regulation once we have scale" as core strategy
- Legal bills growing faster than revenue
- Operating in multiple jurisdictions specifically because you got shut down in original market
- Compliance team reports to growth team rather than independently to board
- Cannot explain regulatory status without "it's complicated"
- Received inquiry letters and response strategy is to delay or obfuscate
- Compliant version of product would have 50%+ worse unit economics

---

## 7. The Math Problem — Unit Economics
📉 269 startups | 15.4% of failures | $105.8B burned | 5yr median lifespan

### The Pattern
Losing money on every transaction, believing scale will fix it. Growth masks the underlying disease. Revenue doubles year-over-year so it feels like progress. Consumer companies especially vulnerable (101 failures). The median 5-year lifespan means founders spent half a decade genuinely believing the next quarter would be the inflection point.

### The Mechanics
- **Stage 1 — Rationalization**: Series A deck shows path to positive unit economics at scale with plausible assumptions. Hit growth targets, raise strong Series B.
- **Stage 2 — Optimization Theater**: Hire specialists to fix specific components. COGS reduced 8% but support costs rise 12%. Improve retention, but that means losing money on each customer for longer.
- **Stage 3 — Scale Trap**: Too big to pivot, too unprofitable to survive. WeWork reached $22B before the math became undeniable.
- **Stage 4 — Terminal**: Gap between current and required unit economics is so large no plausible improvement can close it.

### Key Insight
"If your path to profitability requires changing customer behavior, market conditions, and your cost structure simultaneously, you do not have a business model."

### Red Flags
- Board decks show improving efficiency metrics but actual dollars lost per transaction stayed flat or increased for over a year
- Can explain why unit economics improve at 10x scale, but already scaled 5x and metrics went wrong direction
- Finance team produces multiple versions of unit economics depending on what costs you include
- Hired three consecutive heads of operations, each promising to fix cost structure
- CAC decreased only because you shifted to lower-quality channels with worse retention
- Celebrate revenue milestones publicly while privately watching runway shrink faster than growth
- Path to profitability requires three independent variables to all move in your favor simultaneously


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