- The same feedback, from the other side
- A conversation in the forest
- What those thirty minutes actually meant
- More room to build the business
- I talked through the story too
A few years ago, a client gave me feedback that stuck with me:
You need to improve your leadership skills.
At the time, I was primarily a software developer. I focused on writing good code, solving technical problems, and delivering what was requested. I cared about doing my work well, but I still had a lot to learn about taking responsibility for the decisions around that work.
A few years later, I worked with the same client again. This time, I approached the work differently. I challenged decisions, identified risks, proposed alternatives, and took more responsibility for outcomes. I also stopped chasing technically perfect solutions and started paying more attention to what mattered to the business.
I believe I had become a much stronger technical leader.
The same feedback, from the other side
Today, as the founder of WideFix, I find myself giving my engineers almost exactly the same feedback I received years ago.
I want them to take ownership, think independently, challenge requirements, communicate risks, and care about business outcomes. Completing a ticket matters, but so does understanding whether it solves the right problem.
I have written before about understanding the what and why in software development. That lesson applies to leadership too. A developer needs enough context to recognize when the requested implementation will leave the business problem unresolved.
Receiving that feedback and later giving it to others made me realize I had come full circle. It also raised a harder question: how do I turn these expectations into a system that works without my constant involvement?
Telling someone to improve their leadership skills leaves a lot open to interpretation. I needed to make my expectations concrete enough for engineers to use in their daily work.
A conversation in the forest
During a walk through the forest, while picking mushrooms, I started discussing this with ChatGPT. I shared the client’s old feedback, explained how my approach had changed, and described what I now expected from my team.
In roughly thirty minutes, the conversation connected several things I had been thinking about separately:
- My own journey from implementing tasks to taking responsibility for outcomes.
- The ownership and communication I wanted to see from WideFix engineers.
- A practical engineering code of conduct and an action plan for introducing it to the team.
- The way our website explained our value to clients.
The last point surprised me. Reviewing the WideFix website brought a gap in our positioning into focus. We were selling technical expertise, but we were not clearly communicating our value as a long-term technical partner.
That connected directly to the leadership discussion. If I expect engineers to understand business goals, communicate risks, and help clients make decisions, our website should explain that part of our work too.
We developed a landing page around WideFix as a technical partner for Ruby on Rails applications. While the conversation continued, I asked ChatGPT to implement the page in our GitHub repository. The implementation got underway, and I started dictating the story behind this article.
One conversation had moved from reflection to team principles, business positioning, and implementation.
What those thirty minutes actually meant
Getting to that point through separate engagements could have involved a leadership coach, a marketing strategist, and a developer. Each person would need context, and I would need to connect their work and coordinate the next steps.
In my draft, I estimated that this might represent nine to sixteen hours of professional work and $750 to $2,300 in external costs. Those were rough guesses, not measured savings or quotes for equivalent work. I cannot claim that a thirty-minute conversation replaced all of those services.
The implementation still needed review. The team principles still needed to be introduced and tested in everyday work. A clearer landing page still needed to communicate something that clients recognized as valuable.
What I could see was that we had reached the planning and implementation stage quickly. I had a clearer explanation of the problem, concrete material to work with, and a change underway. That was useful progress on something I might otherwise have kept postponing.
More room to build the business
The biggest realization was about where I could put my attention.
As a developer, I created value through my own work. After founding a company, I started scaling that work through other engineers. Now AI is helping me delegate parts of research, analysis, planning, writing, and implementation as well.
That gives me more room to work on the company itself: improving our engineering culture, developing people, finding opportunities, and deciding where the business should go.
There is still work for me to do in every one of those areas. I need to provide context, question the suggestions, choose a direction, and review the result. AI does not automatically make me a better leader. Judgment and responsibility still belong to me.
But the distance between noticing a problem and doing something about it is getting shorter. During a single walk, I could explore a leadership challenge, turn it into a plan, connect it to our positioning, and initiate a website change.
My limitation is gradually shifting from how much work I can personally accomplish to how effectively I choose what deserves my attention.
I talked through the story too
The original draft of this article was written by ChatGPT. I did not sit down and type a carefully structured account. I talked, shared memories, gave rough instructions, changed direction a few times, and explained what I wanted to communicate. ChatGPT turned those thoughts into a draft, which was then adapted for this blog.
That happened alongside the leadership discussion and the work on our website. The writing captured the same thinking that was helping me make decisions about the company.
A few years ago, I was learning how to become a better technical leader. Today, I am learning how to build a company where every engineer can become one. AI is helping me turn that intention into concrete work faster.
AI is changing what I can afford to focus on. For me, that may be its greatest value.
