Is Your AI Email Assistant Actually Making You Less Productive?

Published 2024-11-19 · Updated 2026-05-23 · 6 min read · AI Productivity and Workflow · By Sahin Boydas

The market is flooded with AI scheduling tools claiming to be the best. I spent 16 months and over $10000 testing the top contenders. This is my brutally honest, data-backed review of which tools are worth your time and money.

During the MovieLaLa days, we learned something about is your ai email assistant actually making you that I still apply to every investment I make.

The market is flooded with AI scheduling tools claiming to be the best. I spent 16 months and over $10000 testing the top contenders. This is my brutally honest, data-backed review of which tools are worth your time and money.

The Framework That Actually Works

I'm going to share the exact framework I use when evaluating is your ai email assistant actually making you. It's not complicated, but it requires discipline.

Step 1: the data tells a different story than your gut This is where most people go wrong. They skip this step entirely and jump straight to execution. Don't do that.

Step 2: most founders overthink this and underspend on execution Once you have the foundation right, this becomes much easier. I've watched founders struggle with this for months when the answer was staring them in the face.

Step 3: Iterate relentlessly Nothing works perfectly the first time. The companies in my portfolio that nail is your ai email assistant actually making you are the ones that treat it as an ongoing process, not a one-time project.

The Counterintuitive Truth

Here's what surprised me most about is your ai email assistant actually making you: the best practitioners do less, not more.

When I was building MovieLaLa, we tried to do everything at once. We had the best technology, the smartest team, and we still almost failed because we spread ourselves too thin.

The lesson I took from that experience, and from watching hundreds of other companies, is that timing is everything in this game. It sounds simple. It's incredibly hard to execute.

What I Tell Founders

When a founder in my portfolio asks me about is your ai email assistant actually making you, I usually start with three questions:

  1. What's your timeline? Because the right approach for a company with 6 months of runway is very different from one with 3 years.
  2. What have you already tried? Most founders have tried something. Understanding what didn't work is often more valuable than knowing what might.
  3. Who on your team owns this? If the answer is "everyone" or "no one," that's your first problem to solve.

These questions seem simple but they reveal a lot about where a company actually stands.

This connects to broader themes around AI personal assistant, AI automation, AI email, AI writing tools that I've been thinking about a lot lately.

What's Next

The world of is your ai email assistant actually making you is moving fast. What worked last year might not work next year. That's both the challenge and the opportunity.

My advice: stay curious, stay humble, and stay close to the people who are actually doing the work. Read less thought leadership and do more experiments. Talk to fewer consultants and more practitioners.

And if you're a founder building in this space, remember that the best time to get is your ai email assistant actually making you right is before you need to. Don't wait for a crisis to force your hand.

I'll keep sharing what I learn. This stuff matters too much to keep to myself.

Frequently Asked Questions

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.

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.

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