Marina Leivald
CMO/Tech Strategist
Everyone Lies, the Data Doesn’t
Founders lie. Investors lie. Governments lie. Everyone lies. They don’t call it lying — they call it storytelling, positioning, thought leadership. Re-framing. The only thing that doesn’t lie? The data. Commit history, patent filings, payroll records, shipping logs. The boring breadcrumbs that hype can’t fake for long.
The battlefield is littered with the wreckage of companies that sold a narrative, raised on it, lived off it — then collapsed when reality refused to cooperate.
If you want to survive chaotic markets, you need to stop reading the headlines and start doing narrative forensics. Trace the signals, follow the money, map the hype back to its origin. If you want bedtime stories, go read TechCrunch. If you want survival, learn how to spy.
Capital hunts velocity, not fundamentals. Zero-interest money is gone. Investors need to believe in inevitability now, not in five years. Narratives deliver velocity.
Regulation is asymmetric. What’s licensed in Singapore is banned in Brussels. Founders are stuck threading a needle through hostile bureaucracies. Narratives create political cover.
Platforms extract rent. Distribution is captured by Google, Meta, OpenAI. If your narrative doesn’t surface in their algorithms, you don’t exist.
Noise scales faster than signal. One staged demo on X can move billions in capital overnight. Meanwhile, proof takes years.
Mechanics: Scraping Signals (The Crypto version)
Narrative forensics is about ignoring the smoke machines and wiring up an OSINT dashboard of ugly truths. Tools like Nansen and TwitterScore show how this looks in practice — scraping on-chain activity and social chatter to separate actual traction from hype theater.
Adoption curves → In crypto, adoption isn’t WAU/MAU on a product dashboard. It’s on-chain wallet activity. Nansen clusters wallets by behavior: are addresses active users, liquidity farmers, or bots chasing incentives? A token with thousands of “new users” may just be mercenary wallets cycling through an airdrop. Nansen flags whether usage is sticky or synthetic.
Capital flows → Forget the press release about a “strategic round.” Look at real capital movement. Nansen tracks wallet inflows/outflows to centralized exchanges, DeFi pools, and treasuries. You can see which funds are actually buying and whether insiders are quietly exiting while retail is told to “HODL.” Signal: long-term stakers accumulating. Noise: insiders dumping while narratives scream “community growth.”
Builder velocity → Open repos still matter, but in crypto, many projects stage commits or fork libraries. The OSINT angle is to cross-reference commits with wallet-funded grants. If GitHub velocity is low while the multisig treasury pays mostly for marketing, you’ve got noise.
Regulatory chatter → AML filings, SEC cases, FATF lists. Narrative might say “global adoption,” but one enforcement action in Singapore or Brussels can choke liquidity. Tools like Dune dashboards often show compliance metrics (e.g., stablecoin whitelists).
Cultural uptake → Enter TwitterScore and similar analytics. These tools don’t just measure followers; they quantify narrative velocity.
Who’s tweeting about the token? Are they real accounts or farmed bots?
How fast is the meme spreading across Telegram/Discord/WeChat groups?
Example: during the NFT boom, TwitterScore flagged that only ~50 influencers drove the bulk of “organic hype” for several projects. That wasn’t cultural adoption — it was amplification theater.
Rule of thumb: When three or more of these metrics align (wallet activity + capital inflows + cultural chatter), you’ve got signal. When only one glows — especially if it’s capital alone — you’re staring at noise dressed as inevitability.
Narrative Forensics: Tracing Origins
Hype cycles don’t happen spontaneously. They’re seeded, engineered, and amplified. If you can trace who lights the fuse, you can decide whether to jump in or get out.
Which funds? → The same cyber VCs push “next-gen XDR” every year. If they’re back, it’s not innovation — it’s recycling.
Which insiders? → Retired generals on drone boards, ex-regulators hyping AML startups. They’re not validators; they’re amplifiers.
Which leaks? → A “stealth” vulnerability disclosure conveniently timed before a funding round? That’s not serendipity. That’s pretext.
For over a decade, the narrative about self-driving cars was “any day now.” Billions flowed. Cities wrote future mobility plans. But narrative forensics showed a different story: engineering headcount flatlined while PR teams ballooned. Patents stalled. Adoption metrics were contrived. Signal said “not ready.” Noise said “inevitable.” The noise won the funding, but the signal had the last laugh.
Tradecraft: From Spycraft to Startup Craft
Narrative forensics borrows directly from intelligence tradecraft. What spies do to spot deception, founders should do to decode markets.
Pretexting → In espionage, it’s the cover story. In startups, it’s the leaked deck or staged demo. Always ask: who benefits from this timing?
Deception detection → In spywork, it’s reading tells. In AML, it’s claims of “real-time AI detection” with no regulatory filings. Real growth is messy; fake growth is linear.
Pattern recognition → Hype cycles rhyme: insider seeding → amplification → capital cascade → copycat flood → correction. If you know the rhythm, you don’t get burned.
In case of AML AI Platforms the decks screamed “AI compliance at scale.” Narrative forensics revealed no licenses, no STR filings, and teams skewed to sales over data science. When enforcement hit, the vapor poisoned the entire subsector.
Mapping the Market in Motion
Industries aren’t static; they’re moving graphs of relationships: startups, incumbents, regulators, creators — constantly reconfiguring. To run narrative forensics, map the market in layers:
Cultural mapping: Detecting micro-signals in memes, aesthetics, values.
Technical mapping: Tracing patents, repos, infrastructure dependencies.
Capital mapping: Following funds, grants, and investor theses.
Stack the layers and you get foresight. Ignore them and you drown in noise. Here’s a simple framework for narrative forensics: The Residue Test. Ask: what remains after the hype fades? Signal leaves residue. Patents, commits, licenses, STR filings, logged hours. Noise evaporates. Decks, demos, hashtags, hype videos.
If there’s no residue, there’s no signal. Don’t invest, don’t build, don’t bet.
Case Files: Signal vs. Noise
Next-Gen XDR (2019–23): Noise = AI buzzwords. Signal = patch velocity and SOC deployments. Residue: vendor churn, recycled CVEs.
Drone Swarms (2018–25): Noise = staged demos. Signal = logged flight hours, procurement hesitation. Residue: frameworks, no mass adoption.
AML AI (2020–25): Noise = real-time compliance decks. Signal = licenses and filings. Residue: incumbents still dominate.
OSINT Tools (2022–25): Noise = slick dashboards. Signal = GitHub repos, adoption by law enforcement. Residue: a few survivors in gov; enterprise shelfware.
Field Note Final: In 2025, paranoia isn’t a bug. It’s a feature. The minute you stop questioning, you become the product. Treat paranoia as infrastructure.
