You're probably wasting 80% of your time on the wrong AI-assisted writing tasks. This single mindset shift will unlock more growth than you thought possible. Let me explain.
For the past few years, the internet has been screaming about AI writing. One camp says it’s the messiah for content creators. The other says it’s a soulless robot apocalypse for art and authenticity. They’re both wrong. The gold rush for generic, AI-puked content is over. That game is dead, and anyone still playing it is about to get left in the dust.
I’ve seen this movie before. I saw it when we were building MovieLaLa, trying to predict what movie fans wanted to see next. I saw it again with RemoteTeam, figuring out how to build a global company culture before it was the default. And I see it now in the pitches I get every single day as an investor. The pattern is always the same: a powerful new technology emerges, and 99% of people use it to do the same old things, just a little bit faster. The 1% who win use it to do entirely new things.
AI-assisted writing isn’t dead. But your approach to it probably is.
The Great Content Delusion: Why More and Faster is a Losing Game
When tools like GPT-3 first dropped, the mandate was simple: scale. Everyone got obsessed with churning out hundreds of blog posts, social media updates, and email newsletters. The logic was seductive. If content is king, then more content must make you a bigger king, right?
Wrong. It just made you a bigger contributor to the internet’s landfill.
I fell for it, too. In the early days, I experimented with generating massive amounts of content. We spun up articles, landing pages, ad copy. The output was… fine. It was grammatically correct. It was keyword-rich. It was also completely forgettable. It had no soul, no opinion, no story. It was the content equivalent of a stock photo. Our engagement rates flatlined. No one was sharing it. No one was talking about it. We were just adding to the noise.
This is the trap of what I call "superficial automation." It’s using a brilliant tool for a dumb task. The real magic of AI isn’t in writing a generic 500-word blog post on "The Top 5 Benefits of X." A human can do that, and frankly, a mediocre human can do it with more flavor than a generic AI prompt. The real magic is in using AI to augment the parts of the writing process that are genuinely inhuman.
Stop Using AI as a Writer, Start Using It as a Co-Pilot
The shift that changed everything for me was when I stopped treating the AI as a junior copywriter and started treating it as a ridiculously fast, infinitely knowledgeable research assistant, data analyst, and sparring partner.
Here’s what that looks like in practice. Forget "write me a blog post about…" and start thinking in terms of specific, high-leverage tasks.
1. The Idea Generation Machine
I used to spend hours brainstorming angles for a single topic. Now, I feed a core idea into a model and ask for 50 different angles.
- Bad Prompt: "Write about the future of AI in gaming."
- Good Prompt: "I 'm an investor who has funded 3 AI gaming startups. My thesis is that AI will kill traditional game design by enabling fully procedural, player-driven narratives. Give me 20 contrarian blog post titles based on this. For each title, provide a one-sentence hook. Frame it for an audience of indie game developers.'
See the difference? I’m not asking it to write. I’m asking it to think. To explore the possibility space. 90% of the output might be garbage, but the 10% that isn’t is pure gold I wouldn’t have found on my own. This is how I found the core thesis for this very post.
2. The Unfair Research Advantage
Remember spending days gathering stats, finding sources, and pulling quotes? Your AI co-pilot can do that in seconds.
When I was writing my book, Becoming Top 1%, I needed data. Lots of it. I needed to know the average funding for a Series A in 2023, the failure rate of SaaS companies in their first five years, the most common reason for startup pivots.
- Old way: Dozens of Google searches, digging through reports, compiling spreadsheets. A week of work, easily.
- New way: A single, precise query to a model connected to a real-time data source. "Pull the latest data on the top 5 reasons for startup failure, citing sources from CB Insights, PitchBook, and the Small Business Administration. Present it as a Markdown table."
This isn’t about replacing the writer’s critical thinking. It’s about supercharging it. The AI fetches the raw materials; I, the human, provide the insight, the narrative, and the conclusion. It’s the difference between digging for gold with a shovel and using a state-of-the-art ground-penetrating radar.
3. The Personalization Engine
One of the biggest mistakes I see is people using AI to write for their audience instead of to their audience. Generic content gets generic results. The money is in personalization at scale.
Let’s say you have a newsletter with 10,000 subscribers. They’re not a monolith. They’re founders, VCs, engineers, marketers. Why are you sending them all the same email?
With AI, you can draft a core message and then instantly create variations tailored to each segment.
- Core message: Announcing my new post on AI-assisted writing.
- Founder segment prompt: "Rewrite this announcement for a founder who is struggling to scale their content marketing. Focus on the ROI and efficiency gains. Use a direct, no-nonsense tone."
- VC segment prompt: "Rewrite this for a VC. Emphasize the market trends and the investment implications of this shift in content strategy."
This is how you build a real connection. It’s how you make people feel seen. It’s work that was impossible to do manually, but it’s trivial with the right AI workflow.
My $1 Million AI Writing Stack (It’s Simpler Than You Think)
People love to complicate things. They buy a dozen different AI tools, each with a monthly subscription, and get lost in the complexity. My stack is brutally simple.
- A Powerful Core Model: I use a mix of models from OpenAI, Anthropic, and a few specialized open-source ones for specific tasks. The key is not the brand, but the capability. You need a model that can reason, follow complex instructions, and access real-time information.
- A "Second Brain": All my notes, thoughts, and research live in a single place (I use Notion, but it could be anything). This is my personal knowledge base. When I work with an AI, I’m not just using its generic knowledge; I’m feeding it my own unique context. This is my secret weapon. I can ask it to "write in the style of my notes on fundraising," and it knows exactly what I mean.
- A Human in the Loop: Me. Always. The AI is a force multiplier, not a replacement. I’m the editor-in-chief. I set the strategy, I ask the questions, I challenge the outputs, and I weave it all together into a final product that has my voice, my opinions, and my stories.
That’s it. That’s the whole stack. It’s not about the tools; it’s about the workflow. It’s about moving from being a content creator to being a content architect.
The Future is Not Written, It's Assembled
So, is AI-assisted writing dead? The generic, low-effort, soulless version of it? Yes. And good riddance. It was a dead end from the start.
But the intelligent, strategic, human-centric version is just getting started. It’s about to unlock a level of creativity and efficiency we’ve never seen before. The winners of the next decade won’t be the fastest typists or the most prolific publishers. They will be the best question-askers, the sharpest editors, and the most creative collaborators with their AI partners.
Stop trying to get the AI to write for you. Start forcing it to think with you. The results will speak for themselves. It’s how I built a business, wrote a book, and manage a portfolio of over 200 companies. It’s not a shortcut. It’s a supercharger. Now go build something that matters.
Frequently Asked Questions
Do all experts agree with this view?
No, and that's fine. The best ideas in business are often contrarian. I share my perspective based on my experience and data, but I encourage you to seek out opposing viewpoints and form your own conclusions.
What's the most common pushback you get on this?
People often push back by citing exceptions or edge cases. And they're usually right that exceptions exist. But building a strategy around exceptions rather than patterns is a losing game for most founders.
What experience informs this perspective?
This perspective comes from over a decade of building companies in Silicon Valley, two successful exits (RemoteTeam to Gusto, MovieLaLa to Gfycat), and investing in 200+ startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.