Steve Nouri's LinkedIn Strategy — The largest…

🚀 The fastest ad I’ve ever created. And all it needed was… I’ve tested every major AI video tool this year, from cinematic generators to UGC editors but nothing comes close to this. Higgsfield Cli…

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Marketing7 months ago

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Ok now this is wild! Google just demolished 100 startups in one day. The AI race is getting heated and OpenAI is now on the back foot releasing unimpressive models. First is the Slide Decks! You ca…

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AI7 months ago

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🚀 Google just wrapped the largest AI Agent deep-dive series on the internet. And the response was insane to the previous agent whitepaper, so I decided to share them all in one post. A complete b…

LinkedIn post image: 🚀 Google just wrapped the largest AI Agent deep-dive series on the internet.

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AI7 months ago

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Google just dropped the future of AI agent systems, arguably one of the most important papers of 2025! But many have no idea what is it about... It may finally solve AI’s biggest limitation: catastr…

LinkedIn post image: Google just dropped the future of AI agent systems, arguably one of the most important papers of 2025!

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AI7 months ago

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StackAI just released 75+ AI agent use cases and you can see how they’re changing your workflow. If you’ve ever chased a number through a PDF, waited on a contract summary or nudged a compliance thre…

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AI7 months ago

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Posting Patterns & Frequency

16.5 posts/week

Posts / Week

0.5 days

Days Between Posts

Total Posts Analyzed

HIGH

Posting Frequency

Timezone: Antarctica/Macquarie

Best Performing Days

Mid–late workweek (cluster around Thu–Fri shows strongest spikes)Announcement-heavy days when major vendors drop news (Google, NVIDIA)

Best Performing Times To Post

Early morning (around 06:00–08:00 in Antarctica/Macquarie) for news/explainer postsLate afternoon to early evening (around 16:00–18:00) for tool demos and visual content

Topics & Content Focus

Primary Topics

Enterprise AI strategy, governance and leadership (data quality, culture, evals, real business impact)Frontier model architectures and AI infrastructure (LLMs, agents, GPUs, Nested Learning, catastrophic forgetting)Applied generative AI tools for marketing and content creation (UGC ads, slide/video generation, creative automation)Agentic & RAG-based knowledge systems for enterprises (Agentic RAG, eRAG, operationalizing trusted knowledge)AI-powered software creation and internal tooling (no-code/low-code app builders, AI-assembled systems)

Secondary Themes

AI education for non-technical leaders and teamsB2B data infrastructure as the hidden power layer behind AIFuture of AI agents and continual learningEvent promotion and live sessions (webinars, LinkedIn Lives, masterminds)Productized AI platforms and vertical AI ‘factories’ by large vendors

Industry Focus

Enterprise AI adoption and digital transformationB2B SaaS and data infrastructure providersMarketing and performance advertising teams using GenAITechnical and product leaders building AI agents, copilots and internal tools

Content Categories

Deep-dive thought leadership and ecosystem analysisHands-on tool breakdowns and use-case experimentsStrategic explainers on infrastructure and architectureWebinar/event promotions framed around concrete business outcomesPartner and platform spotlights with an educational angle

Performance Insights

432.5%

Avg Engagement Rate

STABLE

Performance Trend

Best Performing Topics

Concrete GenAI tools that radically compress marketing or content-production workflows (e.g., instant UGC ads, auto decks → videos → infographics)Breakdowns of major big-tech AI announcements (Google Gemini features, NVIDIA GTC/GTCDC infrastructure moves)Deep but accessible explainers of cutting-edge model research and architectures (Nested Learning, catastrophic forgetting, HOPE)Visually-led or product-demo style posts that show dramatic before/after productivity gains

Virality Signals

Posts that tie a specific tool or feature to a dramatic 10x+ efficiency narrative outperform generic strategy contentStrong hooks with emotional language (‘wild’, ‘massive’, ‘demolished 100 startups’) plus concrete examples drive high sharesBig-vendor anchor points (Google, NVIDIA) act as engagement magnets when paired with curated takeawaysGiveaway-style CTAs (comment for promo codes) spike comment volume in otherwise product-focused postsComplex technical topics framed as ‘this solves the thing everyone’s been hacking around’ generate both likes and thoughtful comments

Structure & Quality

260

Avg Length (Words)

HIGH

Depth Level

ADVANCED

Expertise Level

0.85/10

Uniqueness Score

Common Hooks

Shock/future framing around big shifts (e.g., ‘X just dropped the future of…’, ‘Ok now this is wild!’)Problem-first empathy hooks (‘If you’ve spent hours doing X… you’re not alone.’)Contrarian reframes (‘it’s not really about models’, ‘the next shift isn’t about better search results’)Macro trend statements that zoom out (‘For years we treated the web like…’, ‘Today people spend more time talking to…’)Credibility via event or authority reference (keynotes, research papers, named products)

Common Endings

Open-ended questions asking what readers are seeing on the groundInvites to register for a session or LinkedIn Live with date/timeDirect ‘try it’ or ‘learn more’ links to tools and platformsComment-based prompts to drive replies (e.g., comment a keyword for a promo code)Zoomed-out implication statement about how ‘this changes’ the way work is done

Value Delivery Methods

Translating complex research and infrastructure shifts into business-relevant implicationsProviding concrete workflow-level examples (time/cost breakdowns, step-by-step outputs)Highlighting hidden constraints behind AI success (data quality, culture, governance, infrastructure)Offering practical mental models for evaluating tools and architectures, not just feature listsCurating vendor announcements into ‘what actually matters’ for specific roles (enterprise leaders, marketers, builders)

Formatting Style

Short paragraphs with strong line breaks for rhythmHeavy use of bullets, checkmarks, and section dividers (dashes, emoji headings)Occasional bold/Unicode “headline” lines to frame the postClear sectioning: context → why it matters → how it works → implications → CTAMix of emojis for emphasis with otherwise professional formatting

Audience & Tone

YES

Question Usage

0.5%

Response Rate

Detected Tone

Smart-casual technical strategistEcosystem translator between research, infrastructure and business outcomesHands-on experimenter who tests tools rather than only theorizingHype-filtering realist who acknowledges excitement but emphasizes constraintssemi-formalfirst-person

Interaction Style

Dialogue-seeking, frequently asking readers where they see problems or gapsPractitioner-centric, validating on-the-ground realities (data issues, cultural blockers)Incentive-driven in select posts (promo codes, bonuses for comments)Community-oriented framing around shared exploration of fast-moving AI changes

Community Building Signals

Consistent use of open questions that invite practitioners to share blockers and observationsHosting and promoting live sessions and masterminds to gather the audience in real timeFeaturing conversations with named individuals (e.g., Or) to signal networked expertisePositioning followers as co-observers of the AI shift, not just passive consumers of content

Writing Style Patterns

Content Strategy

Hook: Shock/future framing around big shifts (e.g., ‘X just droppeTone: semi-formalCTA: Conversation CTAs (‘What’s the biggest blocker you

Writing style breakdown

Core characteristics

Tone is expert, confident, and highly informed, but delivered in an accessible, conversational way.

It balances professional/analytical with marketing flair and light excitement.

Voice feels like a practitioner speaking to peers and decision-makers, not a distant journalist or a hype-only marketer.

It is distinctly explanatory and informative, with persuasive undercurrents rather than hard selling.

Formality and feel

Semi-formal: precise terminology (RAG, catastrophic forgetting, infrastructure layer) mixed with casual phrases (this is wild, blew my mind, worth paying attention to).

No slang overload; when used, it is controlled and clear.

No profanity. No aggressive edginess. It’s confident but not abrasive.

Energy level

Medium-to-high energy.

- Hooks are often punchy and emotionally charged, especially in tech news or product posts

Ok now this is wild!

Google just demolished 100 startups in one day.

Hey… our model is literally sinking us.

After the hook, energy shifts into calm, structured explanation.

The emotional curve often goes: shock/urgency → clarity → structured breakdown → zoomed-out insight → calm invitation to respond.

Signature traits

Direct audience education: explains concepts as if talking to an intelligent but non-expert leader.

- Today’s LLMs are brilliant, but they have a fatal flaw

Most AI tools can write snippets. Almost none can assemble a usable system…

- Uses short, declarative lines to drive home core claims

This is massive.

This is not a tweak.

This is the missing piece.

- Uses section labels that feel like mini chapter titles

🔥 My take

🌍 Zoom out: this puts us closer to human-like learning

🧩 Why this matters for the future of agents

Addressing the reader

Heavy use of second person: you, your team, if you work in AI, if your team could…

- First person is used to ground credibility and experience

I’ve tested every major AI video tool this year…

I spent time going through the GTC DC announcements.

This has been on my mind since a recent conversation with Or.

- First-person plural we is used to speak for the industry or teams in general

We’ve been trying to patch the fact that models can’t update themselves safely.

- Commands are mostly gentle and invitation-based

Learn how organizations are using it…

Join us Nov 27…

Try the feature: …

Comment “UGC” below and I’ll send it.

- Suggestions are often framed as reflections

If your team could describe the behaviour they want and watch the app take form, what would you ship next?

For leaders, the question is not “is AI real” anymore. The question is where you lean in first.

- Rhetorical questions are frequent, usually

As hooks.

As section pivots.

As closing CTAs to stimulate comments.

- Metaphors and analogies

Our model is literally sinking us / hole in the floor of the boat.

We treated the web like a giant library.

Data infrastructure as the power layer behind AI.

Storytelling-lite: often a single concrete anecdote (tested this tool, tried this prompt, conversation with Or) embedded in a mainly expository structure.

- Repetition as emphasis

They don’t learn from experience.

They don’t improve over time.

And when you try to teach them something new… they forget what they already knew.

Steve Nouri

Warm Analysis

Performance Overview

Top Posts by Engagement

Posting Patterns & Frequency

Best Performing Days

Best Performing Times To Post

Topics & Content Focus

Primary Topics

Secondary Themes

Industry Focus

Content Categories

Performance Insights

Best Performing Topics

Virality Signals

Structure & Quality

Common Hooks

Common Endings

Value Delivery Methods

Formatting Style

Audience & Tone

Detected Tone

Interaction Style

Community Building Signals

Writing Style Patterns

Content Strategy

Core characteristics

Formality and feel

Energy level

- Hooks are often punchy and emotionally charged, especially in tech news or product posts

Signature traits

- Today’s LLMs are brilliant, but they have a fatal flaw

- Uses short, declarative lines to drive home core claims

- Uses section labels that feel like mini chapter titles

Addressing the reader

- First person is used to ground credibility and experience

- First-person plural we is used to speak for the industry or teams in general

- Commands are mostly gentle and invitation-based

- Suggestions are often framed as reflections

- Rhetorical questions are frequent, usually

- Metaphors and analogies

- Repetition as emphasis

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