What if I told you the key to unlocking massive productivity with AI onboarding was actually doing less? It sounds crazy, but the results speak for themselves.
Everyone thinks they know AI onboarding. They see it as a way to automate the boring stuff, the paperwork, the endless checklists. And sure, it can do that. But that’s like using a Ferrari to drive to the grocery store. You’re missing the real power.
I’ve seen it firsthand. After two successful exits and investing in over 200 companies—including AI leaders like Anthropic, OpenAI, and Scale AI—I get a front-row seat to what actually works. And it’s not what the pundits are selling you.
They're not just automating tasks. They're using AI to create a deeply personalized, human-centric onboarding experience that makes new hires feel like they belong from day one. And it's giving them a massive competitive advantage.
In this article, I’m going to pull back the curtain on the one secret that separates the top 1% from everyone else. This might be controversial, but the data doesn't lie. And if you're serious about building a world-class team, you need to hear this.
The Big Mistake Everyone Makes with AI Onboarding
When most companies think about AI onboarding, they get dollar signs in their eyes. They see all the time and money they can save by automating everything. So they go out and buy the fanciest AI onboarding tool they can find, plug it in, and expect magic to happen.
But it never does. Why? Because they're focusing on the wrong thing. They're so obsessed with automation that they forget about the most important part of onboarding: the human connection.
Think about it. What’s the number one reason new hires leave a company? It’s not the pay. It’s not the perks. It’s that they don’t feel like they belong. They feel like just another cog in the machine.
And when you automate the entire onboarding process, you’re just reinforcing that feeling. You’re sending a clear message to your new hires: “Welcome to the company. Here’s a robot to show you around.”
I saw this happen at a promising SaaS company I invested in. Let's call them 'Innovatech'. They were scaling fast, hiring dozens of engineers a month. To cope, they bought a top-of-the-line AI onboarding system. On paper, it was flawless. Automated checklists, virtual office tours, AI-generated welcome messages from the CEO. The works. But their six-month retention rate for new engineers fell off a cliff, dropping by almost 30%. A disaster for a company whose lifeblood is talent.
Why? Because the new hires felt completely disconnected. They never had a chance to build real relationships with their manager or their teammates. They were just shuffled from one automated task to the next.
It was a classic case of focusing on the technology instead of the people. And it was a costly mistake.
My “Less is More” Approach to AI Onboarding
After seeing what happened at that portfolio company, I started to develop my own approach to AI onboarding. I call it the “less is more” approach. And it’s based on a simple but powerful idea: use AI to augment, not replace, human interaction.
Here’s what that looks like in practice. We use AI for the grunt work. The soul-crushing, administrative tasks that burn out HR and managers alike. Think automated W-9s, provisioning access to 50 different SaaS tools, and answering the same five questions about the 401k plan over and over. AI is brilliant at that.
This frees up humans to do what they do best: be human. It gives a manager back 5-10 hours in a new hire's first week. That's time for an extra one-on-one, a longer team lunch, or a deep-dive into the codebase. It’s time to build trust and psychological safety, the bedrock of any high-performing team.
We also use AI to create a more personalized onboarding experience. For example, we use an AI-powered tool to create a custom onboarding plan for each new hire based on their role, their experience, and their learning style. This ensures that they get the information they need, when they need it, in a way that works for them.
But here’s the key. We don’t just hand them the plan and walk away. We use it as a starting point for a conversation. The manager sits down with the new hire and goes over the plan together. They talk about the new hire’s goals, their concerns, and how the team can support them.
It’s a small thing, but it makes a huge difference. It shows the new hire that we see them as an individual, not just another number. And it sets the tone for a relationship built on trust and mutual respect.
How to Implement the “Less is More” Approach
So how can you implement the “less is more” approach in your own company? Here are a few practical tips:
Start with the human connection. Before you even think about technology, map out the ideal human-centric onboarding experience. What are the key touchpoints where a new hire should interact with their manager, their teammates, and other people in the company? Make those touchpoints the foundation of your onboarding process.
Use AI to automate the boring stuff. Once you have a solid human-centric onboarding process in place, you can start to look for opportunities to use AI to automate the administrative tasks. But be ruthless about it. If a task can be done by a human in a way that builds a relationship, don’t automate it.
Personalize the experience. Use AI to create a personalized onboarding plan for each new hire. But don’t just hand them the plan. Use it as a tool to facilitate a conversation between the new hire and their manager.
Get feedback and iterate. The best onboarding processes are never finished. They’re constantly evolving based on feedback from new hires. So make sure you have a system in place for collecting feedback and using it to improve your process over time.
The Future of AI Onboarding
I believe that the “less is more” approach is the future of AI onboarding. As AI becomes more and more powerful, it’s going to be tempting to automate everything. But the companies that resist that temptation and focus on the human connection are the ones that are going to win.
Looking ahead, I see AI's role evolving from a simple task-master to a personalized 'onboarding concierge'. Imagine an AI that doesn't just answer questions, but anticipates them. It could analyze a new software engineer's GitHub activity and suggest relevant internal projects or subject matter experts to connect with. It could notice a new sales hire is struggling with the CRM and proactively serve up micro-trainings. This isn't science fiction; the building blocks are already here.
But even in that world, the human connection will still be the most important thing. The AI buddy will be there to augment, not replace, the relationships that the new hire builds with their manager and their teammates.
The Bottom Line
AI is a powerful tool, but it’s just that: a tool. It’s not a silver bullet. And it’s not a substitute for human connection.
If you want to build a world-class team, you need to create an onboarding experience that makes new hires feel like they belong from day one. And that means using AI to augment, not replace, human interaction.
It’s a simple idea, but it’s one that most companies get wrong. And it’s the one secret that separates the top 1% from everyone else.
So, are you going to keep chasing the false promise of total automation? Or are you ready to try the 'less is more' approach? It might feel counterintuitive, but for the companies in my portfolio, it's the only thing that's delivering real results.
Frequently Asked Questions
How has this view evolved over time?
My thinking on most topics has changed significantly over the years. Early in my career, I held many conventional views that experience proved wrong. I try to update my beliefs when the evidence changes.
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 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.
How can I apply this thinking to my own situation?
Start by identifying the core principle behind the opinion, not the specific example. Then ask yourself: does this principle apply to my context? If yes, test it in a small, low-risk way before going all in.