Reid Hoffman
Co-Founder, LinkedIn, Manas AI & Inflection AI. Founding Team, PayPal. Author of Superagency. Podcaster of Possible and Masters of Scale.
Reid Hoffman uses LinkedIn to collapse the distance between AI theory and creative experimentation, teaching founders and builders how to think about AI adoption through concrete stories and counterintuitive arguments. His most distinctive move is anchoring abstract AI concepts to specific, playable examples (like a Pi Day music video made entirely with AI) that make the idea immediately actionable.
2.6/wk
11 posts in 30d
551
avg per post
18%
comments / total
4.8%
reposts / total
problem-solution
Sun · 1 PM CET
Voice & tone
Hoffman writes like a thoughtful founder who's genuinely curious about how things work, not a pundit declaring winners. He uses phrases like 'I find most exciting about this moment' and 'one of the more grounded questions' to signal intellectual humility. He avoids hype and instead asks readers to think alongside him, which creates intimacy at scale.
Signature phrases
- “I find most exciting about this moment in AI is that it collapses the distance between an idea and a creative artifact”
- “Like a muscle, agency weakens when it isn't used”
- “The bottleneck isn't 'can we build it?' anymore. It's 'what should we build?'”
- “using AI to build in an unfamiliar domain is one of the best ways to learn both the craft itself and the capabilities”
- “One of the more grounded questions is”
Top 3 posts, dissected
Their highest-engagement posts, broken down line by line. Steal the structure.
I sang a song and produced a music video for Pi Day. Everything, including the music, video, and my voice, was created using AI. Here’s how we made it happen, and what we learned: One of the things I find most exciting about this moment in AI is that it collapses the distance between an idea and a creative artifact. You can have a strange, specific idea—“what if we made a Pi Day music video?”—and instead of letting it die as a joke with friends (or in your head), you can actually make the thing. Not every use of AI has to be a coding agent sprint on an application that instantly generates millions in revenue. Some of the most important breakthroughs happen when people play—when they pick up the tools and build something just because it sounds fun. This project was very much in that spirit: an experiment that turned into a real test of a new kind of creative stack (shared below). The result is weird, fun, and very much an experiment. Exactly what it should be. I learned a lot from this process. More than anything, this reinforced something I keep coming back to: using AI to build in an unfamiliar domain is one of the best ways to learn both the craft itself and the capabilities of the tools. I’m not a songwriter. I’m not an animator. But working through this process taught me more about music production, animation pipelines, and creative AI workflows than any demo or keynote could. Today, it’s a music video about a mathematical constant. Tomorrow, this capability will power new businesses, new art forms, and new ways for people to share their ideas with the world. Let me know what you think—and happy Pi Day. — Here are the tools we used and how the pieces fit together: - Suno for music generation. - Kits.AI to transform the AI vocals into my voice. - Anthropic's Claude Cowork for planning, songwriting, and lyrics. - Logic Pro for audio editing. - Final Cut Pro for video editing. - Runway and Google's Nano Banana for image generation. - HeyGen IV for video generation of "Animated Reid". And for the lyrical animations, we used fal.ai’s Whisper model to generate timestamped transcriptions of the music track. Then we passed the transcripts to GPT-5.2 to generate video prompts. From there, we used an image-to-video model to create each snippet. After each one was generated, we extracted the last frame as an image and passed it into the video model with the next prompt. Then repeated that process across the full sequence.
The hook works because it's absurdly specific and playful ('I sang a song and produced a music video for Pi Day') while immediately signaling this is a teaching post ('Here's how we made it happen, and what we learned'). The specificity stops scroll; the promise of learning keeps readers reading.
Story-driven with embedded teaching. Opens with the bold claim, then moves into philosophy ('collapses the distance between an idea and a creative artifact'), then justifies why this matters ('Some of the most important breakthroughs happen when people play'), then delivers the learning ('using AI to build in an unfamiliar domain is one of the best ways to learn both the craft itself and the capabilities'). Closes with reflection on the experiment itself.
- Specificity before abstraction — starts with the weird Pi Day video, then zooms out to philosophy
- Permission-giving language — 'Not every use of AI has to be a coding agent sprint' gives readers permission to experiment without ROI pressure
- Embedded teaching — the learning is woven into the narrative, not listed separately
- Honest assessment — 'The result is weird, fun, and very much an experiment. Exactly what it should be' shows comfort with imperfection
No explicit CTA. Instead, the post ends with a learning insight that makes readers want to comment with their own experiments or ask follow-up questions. The implicit CTA is 'go try something weird with AI.'
Lead with the specific, playful artifact first, then zoom out to the principle it teaches. This makes abstract ideas concrete and gives readers permission to experiment without perfect ROI.
Notion’s Founder, Ivan Zhao, says you shouldn’t try to save costs or predict ROI when you’re implementing AI. In fact, it’s the easiest way to lose the race. A lot of companies are trying to “control spend” by rationing tokens and putting guardrails around how much experimentat…
The hook inverts reader expectations by attributing a counterintuitive claim ('don't try to save costs') to a credible founder, then immediately raises the stakes ('it's the easiest way to lose the race'). The phrase 'lose the race' creates urgency and FOMO.
Argument format with three-part logic. Part 1: The contrarian claim and why it's wrong to do the opposite. Part 2: The mechanism (companies are rationing tokens and creating 'artificial ceilings'). Part 3: The reframe (the bottleneck has shifted from 'can we build it?' to 'what should we build?'). Closes with a stakes statement.
- Mechanism explanation — 'that creates artificial ceilings on what's possible' shows the reader exactly how the wrong move backfires
- Bottleneck reframe — 'The bottleneck isn't can we build it anymore. It's what should we build?' is a memorable inversion that changes how readers think about resource allocation
- Scarcity language — 'Judgment and taste become scarce resources' elevates the conversation from cost-cutting to strategy
- Closing stakes — 'you're volunteering to fall behind' makes the cost of inaction explicit
Ends with a stakes statement ('you're volunteering to fall behind') that doesn't ask for action but creates enough discomfort that readers want to comment, debate, or share with their leadership team.
When making a counterintuitive argument, explain the mechanism (why the conventional move backfires) before restating the claim. This makes the argument feel earned, not just contrarian.
I asked Notion’s Ivan Zhao a question: Notion is one of the few scaled software companies that’s genuinely making the transition from SaaS-native to AI-native, and doing it in public. How? Ivan’s answer was blunt: it’s very difficult, and almost no one has done it well. His edge…
The hook uses specificity and a genuine question to create intrigue. 'Notion is one of the few scaled software companies that's genuinely making the transition from SaaS-native to AI-native, and doing it in public' narrows the scope (not all companies, just Notion), raises the stakes (doing it in public = high visibility), and creates a mystery (How?).
Question-answer format that mirrors a podcast or interview. Opens with the question, then immediately signals the answer will be blunt and honest ('Ivan's answer was blunt: it's very difficult, and almost no one has done it well'). This sets up reader expectation for candor. Closes with a teaser for more detail.
- Credibility signal — naming Ivan Zhao and Notion specifically makes the question feel grounded, not hypothetical
- Honesty about difficulty — 'it's very difficult, and almost no one has done it well' builds trust by not overselling
- Competitive edge reveal — 'His edge, he argues, is that Notion already has practice reinventing itself' gives readers a framework for thinking about their own situation
- Teaser close — 'More on how Ivan is transforming Notion for the AI age' creates a reason to click or follow for the full answer
Implicit CTA through teaser. Readers want to know the full answer, so they click, comment asking for more, or follow Hoffman for the continuation.
Use question-answer format to create a conversation feel. Lead with a specific, high-stakes question, then promise an honest (even blunt) answer. This builds trust and makes readers want to engage.
What drives their engagement
Hoffman's posts drive comments by ending with either a reframe that makes readers want to debate it (like the bottleneck shift from 'can we build it' to 'what should we build') or by leaving a gap in the narrative that readers want to fill (like asking how Notion is doing the transition). Comments are highest when the post challenges conventional wisdom without being dismissive.
Reposts happen when the post contains a quotable insight or a specific framework that feels useful to share with others. The 'agency is like muscle' analogy and the 'bottleneck has shifted' reframe are both repost-worthy because they're memorable and applicable to many contexts.
Low. Hoffman optimizes for reach and conversation, not for reference material. His posts are meant to be read, discussed, and shared in the moment, not bookmarked for later. The 18% conversation index (comments as percentage of engagement) shows he's building discussion, not a knowledge base.
Content pillars
AI as Creative Tool
32%Stories and experiments showing how AI collapses the distance between idea and artifact, teaching builders to play and learn through making.
AI Adoption Strategy
26%Counterintuitive arguments about how companies should approach AI implementation, focusing on judgment and taste as the new bottleneck.
Human Agency in AI Age
21%Analogies and frameworks exploring what humans keep and what changes when machines do cognitive work, using historical parallels.
Founder Interviews & Insights
15%Q&A format extracting specific, blunt advice from scaled founders (like Ivan Zhao) about navigating AI transitions.
Market Recalibration
6%Precise corrections to false narratives about dying categories (SaaS, etc.), using data to reframe what's actually changing.
Hook patterns
Intriguing Question + Specificity
Ask a narrow, high-stakes question about a specific company or trend, then promise to answer it
“I asked Notion's Ivan Zhao a question: Notion is one of the few scaled software companies that's genuinely making the transition from SaaS-native to AI-native, and doing it in public. How?”
→ Specificity (Notion, Ivan Zhao, SaaS-native to AI-native) makes the question feel urgent and answerable, not abstract.
Bold Claim + Immediate Reframe
State a surprising fact or action, then immediately explain why it matters or what it reveals
“I sang a song and produced a music video for Pi Day. Everything, including the music, video, and my voice, was created using AI. Here's how we made it happen, and what we learned:”
→ The claim is weird enough to stop scroll, but the promise of 'what we learned' signals this is a teaching post, not just bragging.
Statistic Shock + Inversion
Lead with a number that contradicts the narrative, then flip the reader's assumption
“People say SaaS is dead, slain at the hand (neural network?) of Artificial Intelligence. Clearly, though, the $400b+ market hasn't disappeared, but it is changing.”
→ The $400b+ number proves the narrative wrong immediately, creating cognitive tension that makes readers want to understand what's actually happening.
Borrowed Authority + Contrarian Insight
Attribute a bold claim to a credible founder, then explain why conventional wisdom gets it wrong
“Notion's Founder, Ivan Zhao, says you shouldn't try to save costs or predict ROI when you're implementing AI. In fact, it's the easiest way to lose the race.”
→ The founder's name adds credibility, but the 'easiest way to lose the race' creates urgency and stakes.
Analogy as Hook
Open with a memorable metaphor from a credible source, then unpack its implications
“Ivan Zhao of Notion has a good line about AI: agency is like muscle. It can be built, but it can also atrophy.”
→ The metaphor is instantly graspable and memorable, making readers want to see how it applies to their own situation.
Paradox Resolution
State a contradiction or debate, then offer a grounded third way
“A lot of the debate around AI is stuck between utopianism and panic. But one of the more grounded questions is 'what happens to people when a machine starts doing more of the cognitive work?'”
→ Readers feel seen (the debate IS stuck), and the 'more grounded question' positions Hoffman as the adult in the room.
Top-performing hooks
“I sang a song and produced a music video for Pi Day. Everything, including the music, video, and my voice, was created using AI. Here’s how we made it happen, and what we learned:”
→ The post showcases a unique and creative application of AI, making it inherently interesting. By detailing the tools and process, it provides value and inspires others to experiment with AI in their o
“Notion’s Founder, Ivan Zhao, says you shouldn’t try to save costs or predict ROI when you’re implementing AI. In fact, it’s the easiest way to lose the race.”
→ The post presents a contrarian view on AI investment, which is inherently engaging. It leverages a well-known figure (Ivan Zhao) to add credibility and provides a clear, actionable takeaway for tech c
“I asked Notion’s Ivan Zhao a question: Notion is one of the few scaled software companies that’s genuinely making the transition from SaaS-native to AI-native, and doing it in public. How?”
→ The post leverages a recognizable figure (Ivan Zhao) and a popular product (Notion) to address a timely and relevant challenge (AI transformation). The question-answer format provides immediate value
“Ivan Zhao of Notion has a good line about AI: agency is like muscle. It can be built, but it can also atrophy.”
→ The post uses a compelling analogy (agency as a muscle) to frame the complex issue of AI's impact on human capabilities. It provides historical context and encourages readers to reflect on how to leve
“People say SaaS is dead, slain at the hand (neural network?) of Artificial Intelligence. Clearly, though, the $400b+ market hasn’t disappeared, but it is changing.”
→ The post uses a contrarian hook to grab attention and then offers a nuanced perspective on a relevant industry shift. This positions the author as a thought leader with unique insights.
“Despite this week’s positive overall job print, last month was the worst January for job-cut announcements since the Great Recession. U.S. companies announced over 100,000 cuts. Hiring intentions dropped to their lowest level since 2009.”
→ The post uses a startling statistic to grab attention and then immediately addresses a common misconception (AI as the sole villain). This positions the author as insightful and encourages viewers to
“Netflix co-founder and Anthropic board member Reed Hastings thinks the coming AI transition will be tumultuous—and that the people who navigate it best won't be the most technically sound. They'll be the most emotionally fluent.”
→ The post leverages the authority of Reed Hastings and Anthropic to discuss a timely and relevant topic (AI transition). The hook is a contrarian take, suggesting emotional intelligence is more importa
“Don’t put yourself in a box… unless it’s a Proto Hologram Box! We wanted to keep experimenting at the cutting edge of AI tech, so we turned ReidAI into a hologram.”
→ The post leverages the novelty of holographic AI to capture attention and sparks interest by highlighting the improved user engagement. It also positions the author as a thought leader in the emerging
“AMD CEO Lisa Su has one piece of advice for all tech companies: Decide what you’re the best at.”
→ The post leverages a well-known CEO's advice, lending immediate credibility. It offers a clear, actionable principle (focus) that resonates with business leaders and entrepreneurs, making it easily sh
“The simple story about AI adoption within larger organizations is that it's all about saving time. That's not necessarily the whole story, though.”
→ The post uses a contrarian hook to grab attention and challenges a common misconception about AI. It teases a deeper discussion, encouraging engagement and positioning the author as a thought leader.
What works
- Intriguing questions as hooks drive 927 average engagement (2 posts), 68% higher than the average. Example: 'I asked Notion's Ivan Zhao a question: Notion is one of the few scaled software companies that's genuinely making the transition from SaaS-native to AI-native, and doing it in public. How?' The specificity (company name, founder name, exact transition) makes the question feel urgent.
- Statistic shock hooks (5 posts, 657 avg engagement) work by contradicting the narrative immediately. Example: 'People say SaaS is dead...Clearly, though, the $400b+ market hasn't disappeared.' The number proves the narrative wrong in one sentence.
- Short posts under 80 words drive 559 average engagement and account for 44% of output. These work because they're punchy enough to read in a feed scroll and leave room for reader interpretation, which drives comments.
- Problem-solution format (38% of posts, 541 avg engagement) is Hoffman's workhorse. It works because it mirrors how founders think: here's the broken assumption, here's the reframe. Example: 'Companies are rationing tokens and creating artificial ceilings. But the bottleneck has shifted from can we build it to what should we build.'
- Borrowed authority (attributing claims to Ivan Zhao, Notion founders, etc.) adds credibility without requiring Hoffman to be the expert. This makes counterintuitive claims feel safer to share and more likely to be believed.
- Closing with stakes or reframes (not CTAs) drives engagement. Example: 'you're volunteering to fall behind' or 'Like a muscle, agency weakens when it isn't used.' These make readers want to comment or debate, rather than just like and scroll.
Steal this for your own LinkedIn
- Start your next post with a specific, playful artifact or claim before zooming out to the principle. Example: instead of 'AI is changing how we think about creativity,' try 'I made a Pi Day music video where everything—music, video, my voice—was AI-generated. Here's what I learned.' Specificity stops scroll.
- Use the 'bottleneck reframe' pattern when arguing against conventional wisdom. Identify what people think is the constraint, then flip it. Example: 'People think the bottleneck is cost. Actually, it's judgment.' This makes your argument feel like a discovery, not just opinion.
- End posts with a stakes statement or a question that makes readers want to comment, not a CTA asking them to do something. Example: 'The question we must all ask is how to use AI in a way that makes our agency muscle stronger' invites debate rather than demanding action.
- Attribute bold claims to credible founders or experts, even if you agree with them. This adds credibility and makes the claim feel less like self-promotion. Example: 'Notion's Founder, Ivan Zhao, says...' instead of 'I believe...'
- Keep most posts under 180 words. Use short posts to raise questions or share insights, and reserve long posts (350+ words) for major ideas or experiments. The data shows short posts get consistent engagement; long posts are rare but drive 3x engagement when used strategically.
- Lead with the weird or counterintuitive part of your idea, then explain why it matters. Example: 'Don't try to save costs on AI implementation' (weird) followed by 'because it's the easiest way to lose the race' (why it matters). This pattern stops scroll and creates curiosity.
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Posting patterns
Hoffman posts 2.6 times per week with 11 posts in the last 30 days, showing consistent but not daily presence. This cadence allows each post to get full attention without audience fatigue.
Sunday at 12 UTC performs best. This timing likely catches readers during weekend browsing when they have time to read longer posts and engage in comments.
Short posts (30-80 words) perform best with 559 average engagement, followed closely by medium (80-180 words) at 537 engagement. Posts under 180 words account for 79% of his output and drive consistent engagement. Very long posts (350+ words) are rare (3%) but when used, they drive 1560 average engagement, suggesting they're reserved for high-stakes announcements or deep dives. The data suggests: keep most posts short and punchy, but occasionally go long for major ideas.
Engagement by day
Content mix
avg 541 engagements per post
avg 560 engagements per post
avg 822 engagements per post
avg 571 engagements per post
avg 613 engagements per post
avg 619 engagements per post
Hoffman's 38% problem-solution format works because his audience (founders and builders) think in terms of broken assumptions and reframes. His 21% story format works because stories make abstract AI concepts concrete and memorable. Together, these two formats (59% of his content) teach through narrative and reframe, not through lists or frameworks. The remaining 41% (argument, analogy, Q&A) provides intellectual depth and credibility, showing he's not just telling stories but thinking rigorously about the implications of AI adoption.
