CTO | Author of Engineering Leadership newsletter (65k+ subscribers) - Helping you become a great engineering leader!

I am an engineering leader with a passion for solving complicated problems with innovative concepts. I love learning about new technologies, sharing my knowledge and teaching others. 

I have a proven record of successfully managing Agile teams, setting the correct direction and culture as well as creating right processes and continuously improving them. I have overseen hiring and building up the teams as well as have strong emphasis on coaching and mentoring to direct reports.

You can reach me at info@gregorojstersek.com.

"When you move to the Tech Lead position you get a lot less things done".

Well, this is the perception because you have a lot less time for coding. But, let me tell you that the time you spend "not coding" is the time that is much more valuable.

You are focusing on:
- mentoring and helping others level up,
- doing good code reviews,
- unblocking the team with planning and creating tech specs.

By doing this, you are making the whole team better and faster as well!

Learn more in this Engineering Leadership article: https://lnkd.in/eKeXRZFJ

Gregor Ojstersek

I am an engineering leader with a passion for solving complicated problems with innovative concepts. I love learning about new technologies, sharing my knowledge and teaching others. 

I have a proven record of successfully managing fully remote Agile teams, setting the correct direction and culture as well as creating right processes and continuously improving them. I have overseen hiring and building up the teams as well as have strong emphasis on coaching and mentoring to direct reports.

You can reach me at info@gregorojstersek.com.

CTO | Founder of Engineering Leadership newsletter (184k+ subscribers) - Helping you become a great engineering leader!

Software engineering is becoming position-less.

For years, our industry relied on clearly defined roles: frontend, backend, QA, DevOps, manager, and architect.

Titles were clear, and responsibilities (depending on the company) have been decently defined.

But that clarity is now fading.

Today, companies care less about titles and more about the impact.

- Engineers are expected to think about the product and business.
- Managers are expected to be more hands-on.
- Architect, EM, and Staff Engineer roles are getting closer together.

The boundaries are blurring more and more.

With better tools, AI-assisted engineering, and smaller teams, versatility is becoming more and more expected.

Learn more in the latest Engineering Leadership article: https://lnkd.in/dg3yh8AR

CTO | Founder of Engineering Leadership newsletter (183k+ subscribers) - Helping you become a great engineering leader!

My TOP 3 traits for recognizing the potential in engineers.

It has nothing to do with where an engineer currently stands technically. What truly matters is their attitude and mindset.

These are the 3 traits I look for:
- sense of ownership and responsibility,
- drive and motivation for improving,
- team player and making others around them better.

With these 3 traits, an engineer has the foundation to become a great one. And more importantly, I believe they can excel at anything they commit to.

Saying "I don't know" is a sign of seniority for me.

It’s impossible to know all of the things, especially in Software Engineering. So not knowing something is no issue at all.

On the contrary, it shows me that you are self-aware and confident in yourself by saying that.

The same is true with admitting mistakes. It's a lot better when you acknowledge that you've been wrong as soon as you know.

And not try to hide it and hope that nobody will find out.

Nobody is perfect, we all make mistakes. Admitting them builds trust.

Learn more in this Engineering Leadership article: https://lnkd.in/erdeDUXM

Advice for engineering leaders building AI-native engineering teams.

1. Don't focus too much on code generation and metrics like lines of code produced by AI

Instead, look for the real bottlenecks, as more code won’t solve the problem. The bottleneck might be code review, planning, or system design, especially as engineers become much more productive.

2. Let engineers experiment

Give teams a generous, sometimes unlimited, token budget and the freedom to experiment. Encourage people to explore without pressure or fixed expectations about what success should look like.

Where this breaks down is when leadership has a very rigid idea of how AI should be used and forces that approach onto teams.

3. Look for people who are excited about AI

Do you already have people who are excited about AI and noticeably more productive? If so, help them spread what they’re learning.

Create space for sharing: internal hackathons, demo sessions, and dedicated channels where people can exchange tips and workflows.

4. Stay close to technical details

As a leader, it’s more important than ever to stay close to the technical details. At the same time, it’s critical to empower your team to make decisions.

That means optimizing how decisions get made: clear ownership, clear escalation paths, and minimal friction.

To learn more, read this Engineering Leadership article: https://lnkd.in/d5ambTDW

First, build the RIGHT things. Second, build the things RIGHT.

It can be the difference between a successful and an unsuccessful project.

You can do the best work in the world:
- write the simplest code,
- add all the tests,
- create all the documentation.

But if you are building the wrong things for the users, it won't be perceived this way.

To learn more, read this Engineering Leadership article: https://lnkd.in/eJgJpbmS

Engineering Leadership

Dominika Rogala

Just asking for a friend :)

Happy Friday and have a great weekend!

I can tell a lot about engineer's seniority by the way they approach solving problems.

Here are 5 indicators that tell me if the engineer has a Senior mindset:

1. They ask all the right questions before they start solving the problem.

2. They REALLY take care of the problem, not just try to quickly patch it and leave it for others to deal with.

3. They focus on simplifying the solution as much as possible.

4. They know when the solution is good enough or when to optimize further.

5. They are self-aware and self-confident enough to admit when they don't know something.

To learn more, read this Engineering Leadership article: https://lnkd.in/eSHCwymt

Software engineering roles are getting closer together.

This is what I am seeing happening across the industry:

1. EM, Staff Engineer, and Architect roles are getting closer together

For middle managers, e.g., (Sr.) Engineering Managers, it’s becoming more and more common to be expected to take on Staff Engineer roles if needed, and Staff+ Engineers taking on manager hats if needed.

And the same for Architects as well → taking on a Staff Engineer role or manager role if needed.

2. Similar trend for PMs and Engineers

The role “Product Engineer” is getting more and more popular, and being product/business-minded is just going to be more and more important for all engineering roles.

Good examples are companies like OpenAI and Lovable, both of which look for their engineers to own projects end-to-end: the what, why, when, and also the how.

To learn more, read this Engineering Leadership article: https://lnkd.in/dg3yh8AR

When you are leading projects as an engineer, this is very important to keep in mind:

Make sure that the expectations from the stakeholders are clear and that you thoroughly understand them.

It can be a difference between a successful and not successful project.

You can do the best work in the world:
- write the most simple code,
- add all the tests,
- create all the documentation.

But if the expectations and perceptions from the stakeholders are not managed properly, it won't come across that way.

To learn more, read this Engineering Leadership article: https://lnkd.in/er_2xD9m

Top 4 traits startups should look for in engineers:

1. Comfort with ambiguity
This is the single biggest predictor of startup success. Can this person function, and actually enjoy functioning, when the requirements are vague, the priorities shift, and nobody has the answer?

2. Low ego and willingness to do nonengineering work
That includes writing docs, talking to customers, debugging a front-end issue even though they’re a back-end engineer, setting up the billing integration, and sometimes just answering support emails.

3. Speed over perfection
You don’t want someone who ships garbage. But you absolutely need someone whose instinct is to get something working and iterate rather than spend two weeks architecting the “right” solution.

4. Self-direction
Can the candidate figure out what to do next without being told? At a large company, there’s always a manager, a project manager, or a sprint board telling you the priority. At a startup, especially in the first 10 hires, there often isn’t.

These are the insights from Neil Matthams, who has been a guest author on the latest Engineering Leadership article.

Read it here: https://lnkd.in/d4dAuQv6

OpenAI recently started with a new type of interview that has been very successful for them.

They describe it as a combined product and technical deep dive.

In this interview, candidates are given a problem that is mostly an AI-first, AI-native problem.

They are asked to think about the problem and how they would approach building a product around it. There is no prework required.

During the interview, the candidate and interviewers work through the problem together. They discuss what the product specification might look like and what kinds of systems and architectures would be needed to build it.

This format has proven to be a very high signal for them.

It helps evaluate a candidate’s intuition about AI models, their ability to collaborate, and their engineering judgment when designing systems and solutions.

To learn more, read the full Engineering Leadership article on OpenAI: https://lnkd.in/dNgFuDYr

“My work speaks for itself”

If you find yourself in the words above, there’s a good chance you haven’t been communicating your impact well.

And it’s time to make some adjustments.

There are 2 things I like to say.

1. You can do the best work in the world, but if the expectations are not managed correctly, it will not be perceived that way.

2. Doing great work is only half of the work, making sure that everyone knows about it is the other half. You need to do both.

Assuming that everyone knows that you are doing good work is in most cases, going to be a wrong assumption.

You need to actively ensure that people know that you are doing good work.

To learn more, read this Engineering Leadership article: https://lnkd.in/ek8cafxG

Waiting for some pokemon AI tools to put it in the list :)

Happy Friday and have a great weekend!

200+ resources to become a great engineering leader in 2026!

I've been curating these resources for 5+ years, and my goal is to help you grow in your career as an engineer/engineering leader.

In the list, you'll find my recommended:
- books,
- newsletters & articles,
- people and more.

Topics span from software engineering, system design, data engineering, leadership, management, and all the way to AI and product and business.

Here is the list: https://lnkd.in/eRMgZ9Ee

First, build the RIGHT things. Second, build the things RIGHT.

This is more important than ever.

AI makes output cheap, impact becomes rarer. So, anyone can "ship more code", while business impact becomes that much more important.

And that's where the focus on building the RIGHT things is crucial.

To learn how software engineering productivity has evolved over the years, read the latest Engineering Leadership article we did together with Francisco Manuel Soto Ramírez here: https://lnkd.in/d9KqCUPs

SDE2 @Amazon | Author of 19,000+ subs Newsletter (strategizeyourcareer.com)

AI tools are the onboarding buddy for AI-native engineering teams.

At OpenAI’s Codex team, the onboarding buddy is Codex. If you’re building AI-native engineering teams in your organization, it can be something else.

Here is an example that Thibault Sottiaux, Engineering Lead for OpenAI's Codex team, shared in our recent conversation:

"Codex walks new hires through onboarding, sets up their entire computer, and helps them understand the codebase, projects, and existing features. It basically acts like a highly skilled engineering mentor.

From initial setup to being productive, most of the onboarding process is handled by the AI tool. As a result, onboarding is much faster than it used to be."

At OpenAI, they also have a strong culture of shipping on day one, and that’s recommended for AI-native engineering teams as well. It’s really important for every engineer to provide value as soon as possible.

Normal traditional teams have the goal to ship code to production within the first week. In AI-native engineering teams, that should be on the first day.

Learn how to build AI-native engineering teams in this Engineering Leadership article: https://lnkd.in/d5ambTDW

How do the teams behind ChatGPT actually work?

I recently had the pleasure of speaking with Sulman Choudhry, Head of Engineering, ChatGPT.

The organization is much smaller and operates very differently from most traditional tech companies.

Teams are highly technical, roles often overlap, and many ideas start from the bottom up rather than from top-down.

At the same time, engineers frequently own problems end-to-end, research and product development happen side by side, and experimentation is a core part of their process.

Learn more about OpenAI's engineering culture in the latest Engineering Leadership article: https://lnkd.in/dJCFKQ2C

Sponsorship slots on the Engineering Leadership newsletter are now fully booked 4 months in advance.

Just a couple of slots left are either in discussions or semi-available.

Honorable mention: Larridin, Inc. has recently become a sponsor of the newsletter by booking 5 slots. They are working on some great things regarding measuring AI adoption in organizations.

And I like how CTO Ameya Kanitkar is building the teams inside their org. Fully AI-native teams, with the focus on building good systems for verification.

Here are some of his beliefs:
- Small teams tend to work better
- Test-driven development is non-negotiable
- Treat teammates like artists: get them into flow, keep them in flow, help ideas ship

I'll be sharing more about their AI-native development workflow in a future article. Stay tuned for that!

taplio

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