AI for Engineering Teams. Part 0 — Embarking on Our Journey

Here at Akvelon, we are constantly exploring ways to be the best engineering partners and provide the utmost value. We are top-class engineers, and this is why our clients love working with us.

In today’s rapidly advancing technological landscape, AI (Artificial Intelligence) and LLM (Large Language Models) have quickly become game-changers for software engineering teams, providing:

• Boosted Efficiency: AI and LLM automate repetitive tasks, help write the code, and accelerate product development (check the full survey results >).
• Improved Code Quality: AI-driven tools proactively detect potential issues and help ensure best engineering practices.
• Augmented Creativity: LLMs assist in everything from brainstorming to documentation, making developers happier (check survey results).

Using AI for software engineering is the new norm everyone will need to adopt to stay in the market. Nowadays, I see it as important as the adoption of the version control system (git), and other default engineering practices.

Lately, I’ve been tasked with driving Akvelon teams toward becoming a fully AI-turbocharged company, and I’m eager to share our journey with you. The endeavor promises to be both interesting and challenging, given our extensive team of more than 1,200 engineers spanning diverse technologies and profiles, working with different clients, ranging from small start-ups to established global Fortune 500 corporations.

Over the next few months, I’ll be sharing our real and truthful experience that will include approaches and procedures, main challenges, and insights backed up by cases and data from our real projects.

Interested in getting regular insights on the Akvelon team’s AI-powered journey?

Also, feel free to suggest a question you want us to uncover in the comments section.