A Year of Growth and AI Innovation

While taking time to rest and recharge (🏔️ 🚴 🏃‍♂️) during the holidays, it's also a good opportunity to reflect on what we've accomplished. This year has been marked by significant growth and learning. While I anticipated continued success, the business has actually exceeded expectations, and our team has grown substantially. As an engineering manager, my priorities are building a strong team, developing employee skills, supporting career advancement, and delivering excellent results.

Sharing Knowledge with the Community

I presented at FinOpsX and the HAProxy Conference, sharing best practices and insights into how our team at Liftoff Mobile solves complex technical challenges. We're committed to contributing to the community and welcome feedback that helps us build more reliable and scalable systems.

The AI Shift

Generative AI has been a major topic in the tech industry this year. I'd like to share what it has actually delivered for us and what we're planning for the future.

At first, I used AI for simple, everyday tasks. Then I discovered an AI-powered coding tool that changed the way I work. I realized I could use AI as a constant assistant to accomplish much more.

I learned about the Model Context Protocol, a system that lets AI connect with the business tools and services companies already use. This opened up new possibilities—you can set up these connections in just a few hours.

I spent two weeks intensively studying this system and how to use it. I created several free, publicly available tools that others can now benefit from.

Building an Enterprise AI Team

While hobby projects are valuable, real impact comes from testing solutions at scale. With strong support from my leadership, I formed a team focused on emerging technology.

Like any new team, we're looking for the right partner and project to help us grow. We want to work with someone who has real challenges we can solve together—this gives our team a meaningful first project to tackle.

We found an internal partner willing to work with us. This project gave us the opportunity to test all the key components of an AI-powered application, including data retrieval systems, text processing, prompt design, and performance monitoring.

Beyond that initial project, we explored how AI could help our engineers work more efficiently. We noticed that managing task lists was taking up valuable time, so we built a workflow that reads technical documents and automatically suggests action items.

The results have been impressive. Team leads and managers can now create tasks much faster than before—what used to require manually translating documents into action items now happens automatically. This frees them up to focus on making sure each task is clear and well-defined.

Added to that, We also work with one of our top analysts on a new frontier project. We gave them access to our latest AI workflow to see how it could satisfy their needs.

A key part of this project is democratizing the outcomes where users can actually tap into valuable insights with fewer dependencies on technical counterparts, which also frees up their partners so that they can use that valuable time to enhance the quality of the service itself.

Market Leader

In the fast-moving field, everyone tries to move quickly from concept to completion. A strong workflow is essential—it helps people identify promising ideas, track their progress, and deliver results efficiently. Claude has become our primary tool for generating code.

The Anthropic ecosystem continues to grow more valuable. More companies are adopting these tools and processes, recognizing their benefits. The number of available integrations and capabilities increases regularly. This creates real value: we can build a solution once and reuse it multiple times across different projects.

Looking Forward

Here are my predictions for trends that will likely shape 2026 and beyond, based on this year's progress:

• The focus of AI applications will shift away from the model itself. Instead, what truly matters is how you organize your tools, structure your workflows, and design your overall system.

• Additionally, AI services will become cheaper, while the intelligence of AI systems will improve. This is happening because companies are finally seeing returns on their infrastructure investments and finding ways to make AI training and operation more efficient. These improvements will lead to better prices for customers, and the money saved can go toward developing even smarter AI systems.

• Finally, human connection will become increasingly valuable in an AI-driven world. As AI-generated content becomes more common, people will likely place greater value on human interaction and service. There's something irreplaceable about talking with someone you trust, someone you can meet face-to-face. This is a natural human need, and it will help balance out our reliance on AI. Rather than replacing humans, AI should be a tool that helps people live better lives.