In an AI-driven world, an engineer who can write 10x more code is less valuable than an engineer who can decide which 90% of that code shouldn’t be written in the first place.

Engineering leaders want strong software engineers who are also good communicators. People who can really dig into the actual problem and explain the solution in a way that resonates with everyone.

Focus is a competitive advantage these days. With so many distractions, and especially context-switching that comes with AI-assisted engineering. If you can focus on what you want to accomplish, that's really valuable these days in my opinion.

As an engineering leader, fix "organizational friction" first, hire second. The goals should be clear, priorities, and ownership as well. Good leadership should come first, hiring after. If you just blindly hire new people, they won't be closely as productive as they could be.

Great chatting yesterday with Eric Sammer, Distinguished Engineer at Redis (formerly CEO Decodable).

The role of a manager is to make their team better, not to be the best coder on the team.

Everyone says managers should be more hands-on. I believe the biggest impact of a manager is to enable others to do their best work.

A lot of engineers are slowed down because of bad processes, useless meetings, and unclear goals. Especially these days, when you can use AI to move faster. So, a person that can improve the “organizational friction” is extremely highly worth in my opinion these days.

Sponsorship slots on the Engineering Leadership newsletter are now fully booked till the end of this year.

Great engineers 10 years ago were masters of 1 programming language and framework. Great engineers today are tech-agnostic leaders with good problem-solving abilities and people skills.

It happens 🤷‍♂️

Your expertise as an engineer is worth more as helping others than it is at solving your own tasks. Being a multiplier in your team is what really makes you a 10x engineer.

For Engineering Managers: A lot of people may feel overwhelmed, or burned out due to so much uncertainty, therefore it’s even more important to be a good manager and a leader for your people at this time.

The recording of my talk at the TechLead conference in Amsterdam is now available. I gave a talk titled: Why Engineers Must Become Multipliers in the AI Era. I talked about the 6 trends, which are:

You can do the best work in the world, but if nobody knows about it, it won't be perceived that way. Just doing good work is unfortunately not enough. Making it visible is equally important.

The good ol' days 😄 Happy Friday and have a great weekend!

Most tech hiring processes act like engineers don't use AI at work. Then at the same time, these same companies expect everyone to use AI in their day-to-day work, and be good at it. Don't get the logic.

Your engineering team doesn't have an execution problem. You don't need another agile framework or daily standup metric. They just don't have a technical vision clear enough to make focus effortless. You haven't built a product trajectory so compelling that distraction becomes boring.

The most expensive sentence in engineering: "Because that's how we've always done it."

“It has worked well for me for 10-15 years, why would I change?” This is a very problematic mindset, and can really hold you back on learning new things and improving. My advice: Combine your good understanding of your craft with curiosity to keep on improving.

Great engineer 10 years ago: Knowing 1 programming language and framework. Great engineer today: A tech-agnostic tech lead with good problem-solving abilities and people skills.

How to do spec-driven development? 1. Start with a spike first 2. Promote the spike to reference implementation 3. Write the spec 4. Write/adjust the test plan 5. Create the implementation plan 6. Implement

I am happy to share that I will be a judge at the Ready, Spec, Ship Hackathon with Kiro. There is a $9,600 prize pool available for the top 3 submissions.

The new "building is on fire, commit all the code" meme!

Interestingly, OpenAI doesn't ask data engineers to build a new dashboard anymore. Instead, they simply ask a data agent that's connected to all their data to create it.

My advice to junior engineers: Actively work on demonstrating what you can build, instead of waiting for a job to "come up".

Talking with different companies, one thing I am sure of: Nobody has figured out the perfect process for AI-assisted engineering, we are all learning and adjusting on the fly.

Since token cost just keeps increasing, I am seeing spec-driven development becoming more and more popular. It's a lot more efficient if you build a spec using a higher-tier LLM and implement it with a lower-tier LLM than just infinitely prompting.

With the flood of AI-generated text everywhere, human, thoughtful writing is becoming more important than ever. Clear writing is a superpower in the AI era, in my opinion.

The speed of writing code has never been an issue. You can write 10,000 or 20,000 lines of code, but if you are building the wrong thing for the user, it means nothing. Once you know you’re building the right things, then you can bring in AI tools to speed up the delivery.