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David ten Have

David ten Have

LinkedIn Content Strategy & Writing Style

What do I have to do to ship?

New Zealand
36 Viral ScoreView on LinkedIn

0 people tracking this creator on ViralBrain

Warm Analysis

David ten Have positions himself as a pragmatic, battle-hardened technologist who prioritizes the ethics of "shipping" over the hollow hype of Silicon Valley. His content strategy centers on a cynical deconstruction of AI leadership, where he uses his background in building machine learning tools to expose the gap between corporate valuation and actual utility. He is notable for his refusal to engage in tech-optimist tropes, instead offering a sharp-tongued critique of "misanthropic" AI development and regulatory capture. By blending deep technical literacy with moral urgency, David creates an intersection where product engineering meets social accountability, calling out industry giants for prioritizing desperation-led innovation over human safety.

Performance Overview

Followers

2.4K

Connections

2.3K

Avg. Engagement

7

Engagement Rate

Posts/Week

7.9

Viral Score

36

Posts Analyzed

1

Top Posts by Engagement

"When a company that raised $40 billion last year and is now valued at $500 billion suddenly announces they’re “exploring” ads, that’s not innovation - that’s desperation wearing a press release."

182011 viral
Advertising Strategy9 months ago
View on LinkedIn

This reminds me of MS with XML... "if it's not working, use more of it"

5409 viral
Software Development9 months ago
View on LinkedIn

"Musk can claim that Optimus will justify Tesla’s insane valuation and become the most valuable product in the world all he wants. But when the guy who was supposed to make that happen leaves to work…

4015 viral
Tech Industry Analysis9 months ago
View on LinkedIn

When I got into tech we had "Think Different". Now we've got "I couldn't imagine raising a kid without ChatGPT" and "what happens when we realize we were just stochastic parrots all along?" The AI lea…

5104 viral
AI Ethics9 months ago
View on LinkedIn

"97% of respondents said that AI tools shouldn’t be allowed to generate sexually explicit content of children" Please, by all means, report this post again... Grok generates CSAM and it does it at an…

6003 viral
AI Safety9 months ago
View on LinkedIn

Y'all shot for regulatory capture by telling us ghost stories (coz you really had no moat), shitting the nest for all of us and *now* you're "It's not useful". Genuine thanks to Jensen for calling it…

2103 viral
AI Policy & Regulation9 months ago
View on LinkedIn

Posting Patterns & Frequency

7.9 posts/week

Posts / Week

1 days

Days Between Posts

1

Total Posts Analyzed

HIGH

Posting Frequency

Timezone: Pacific/Auckland

Best Performing Days

MondayTuesday

Best Performing Times To Post

16:00-17:3019:00-20:00

Topics & Content Focus

Primary Topics

Skeptical analysis of AI narratives and the cultural ideology of AI leadershipBig Tech business-model shifts (monetization, ads) framed as weakness rather than innovationTech hype vs. execution reality using historical/engineering analogies

Secondary Themes

Tesla/Elon Musk valuation storytelling vs operational signals (talent exits, product credibility)Autonomy/computer-vision reliability critique (safety and real-world adequacy tests)Media/press-release rhetoric and narrative manipulation in tech

Industry Focus

AI platforms and foundation-model companiesSilicon Valley/Big Tech corporate strategy and commsEV/autonomy and robotics (Tesla ecosystem)Tech media discourse and investor narrative cycles

Content Categories

Contrarian industry commentaryNarrative/PR deconstructionHype-to-reality skepticism checksQuote-and-react micro-editorialsCultural critique of tech ideology

Performance Insights

6.625%

Avg Engagement Rate

STABLE

Performance Trend

Best Performing Topics

Big Tech monetization/ads framed as strategic weaknessTech-industry narrative/PR takedownsHistorical analogies that mock product/process dogma

Virality Signals

Shares are rare; reach is driven more by debate-triggering statements than repostabilityPosts that attach a strategic interpretation to a headline outperform pure quote commentaryNumbers/scale anchors correlate with higher likes (signals authority and stakes)

Structure & Quality

170

Avg Length (Words)

MEDIUM

Depth Level

ADVANCED

Expertise Level

0.78/10

Uniqueness Score

Common Hooks

Quote-first hook (pull quote, then judgment)Historical analogy hook (past tech pattern → current AI behavior)"When X happens..." framing to set up a critiqueValuation/scale anchor (big numbers) followed by a contrarian interpretation

Common Endings

Hard label/diagnosis (e.g., calling motives or character)Implication close ("it tells you a lot") rather than explanationPunchline-style reframing (innovation → desperation)

Value Delivery Methods

Reframes headlines into incentives and power dynamics ("what this really means")Uses credibility-by-pattern-recognition (history repeats) rather than how-to instructionProvides social permission for skepticism toward dominant AI narratives

Formatting Style

Single-paragraph micro-postsHeavy use of quotation marks to stage a claim then rebut itCompressed, punchy sentences with a final kicker

Audience & Tone

YES

Question Usage

0%

Response Rate

Detected Tone

Contrarian analystCynical-but-literate tech criticCompressed editorialistAnti-hype narrative breakerCultural commentator with engineering sensibilitiessemi-formalmixed

Interaction Style

Audience is pulled into agreement/disagreement cycles (polarizing claims)Comments likely come from challenging the framing rather than asking for tactical detailsEngagement is driven by identity alignment (anti-hype, anti-PR) more than problem-solving

Community Building Signals

Positions the creator as a reliable skeptic/critic rather than a teacherBuilds a "we remember how this goes" in-group through shared tech-history referencesCreates conversation via moral/character judgments of leadership and incentives

Writing Style Patterns

Content Strategy

Hook: Quote-first hook (pull quote, then judgment)Tone: semi-formalCTA: No explicit CTA; relies on provocation to spark re

Writing style breakdown

The author’s voice is terse, high-signal, and culturally literate, with a strong preference for compression over exposition. The default posture is critical and diagnostic: they look at a statement, product move, or industry narrative and then translate it into a blunt underlying motive (for example, reframing “exploring ads” as “desperation wearing a press release.”). The style is professional in knowledge base (tech, funding, valuation, regulation, AI/ML), but conversational in delivery: contractions are common (“wouldn’t,” “they’re,” “we’ve got”), slang appears when it sharpens the jab (“Y’all,” “coz,” “moat”), and profanity is used strategically rather than constantly (“shitting the nest”).

Energy is medium-high: not breathless motivational hype, but quick acceleration into a verdict. The tone leans sardonic and skeptical, with occasional moral gravity (notably around child safety). The author switches cleanly between humor and severity without changing the underlying cadence: a snarky one-liner can sit right next to a serious boundary statement.

Signature traits include

Quotation-as-targeting: the author frequently embeds short quoted phrases to mock, distance, or highlight corporate/ideological language (examples: “exploring” ads; “Think Different”; “I couldn’t imagine raising a kid without ChatGPT”; “It’s not useful”.)

The “translation move”: corporate euphemism is translated into a sharper noun (“innovation” becomes “desperation”; a “press release” becomes a costume).

Punchline-by-contrast: the author sets up a scale or expectation (money raised, valuation, “DMV vision test”) and then snaps to a deflating comparison.

Moral line in the sand when needed: the author will explicitly state acceptability boundaries (“It is not acceptable to generate sexualized images of children.”)

Reader address varies. Much of it is third-person commentary (“When a company… announces…”) or collective “we” to mark a generational shift (“When I got into tech we had…”). Direct second-person appears mainly as accusation/diagnosis aimed at an implied group (“Y’all shot for regulatory capture…”). Commands are rare; the author prefers declarative judgments and rhetorical framing over “do this” imperatives.

1. A referent or quoted line (sometimes entirely as a standalone paragraph).
1. 0 blank lines allowed before the first visible character.
1. The longest hyphen lines (Line 1 and Line 4 types) represent compound paragraph blocks: multiple logical beats are written continuously as one visual paragraph.

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