Gixer stories

Adapting Our Talent Accelerator for an AI World - AI in Training

gixer stories

What I love most about being a mentor is watching younger tech professionals grow. By incorporating AI into our training curriculum, we are helping them become more capable and confident even faster.

Adapting Our Talent Accelerator for an AI World - AI in Training - hdr image

Alongside other team members, I have been a trainer and mentor in CoStrategix’s Talent Accelerator program for 3 years now. This program transforms recent university graduates with minimal work experience into skilled technology professionals in our engineering office in Bangalore. We recruit candidates based on potential rather than existing expertise, focusing on individuals who demonstrate strong analytical thinking and a passion for tech.

Most recently, we added a crucial new layer to our traditional skill-building program. We integrated an AI-driven mindset into our learning program from the very start.

How We Embedded AI in Our Training Program

AI is no longer a future trend. It’s already a core enabler of modern software development – from code generation and testing to system design and documentation. Tools like GitHub Copilot, ChatGPT, and other integrated AI assistants are already a part of our developers’ everyday toolkit. The Software Development Life Cycle (SDLC) is transforming in many ways, for example:

  • AI pair-programming tools enhance our speed and collaboration in development
  • Context-aware AI-powered suggestions speed up our issue resolution in testing and debugging
  • Auto-generated suggestions based on the context provide more accurate authoring in documentation

In short, AI is not replacing our engineers – it’s amplifying and empowering them to be more agile and efficient.

Likewise, AI in training isn’t checking a box – it’s truly revolutionizing our learning and development process.

We train recent grads who are eager to start their careers in Data Analytics. Previously, we helped develop a structured, three-month training path including skills such as:

  • Software Engineering best practices
  • Hands-on Python & SQL Programming
  • Data Engineering
  • Data Analysis
  • Data Visualization using Power BI

Our new curriculum incorporates hands-on and situational learning that promotes AI-first thinking:

Prompt Engineering Learning Modules

We introduced the basics of prompt engineering as a part of the learning program, teaching candidates how to communicate effectively with AI tools like ChatGPT and Gemini to get accurate, useful, and structured responses for coding, analysis, and documentation tasks.

GitHub Copilot in Practice

Through GitHub Copilot, candidates learn how to:

  • Generate boilerplate code in Python
  • Accelerate SQL query writing
  • Refactor and improve existing logic
  • Auto-generate docstrings and comments

AI-Assisted Problem Solving

During data engineering, data analysis, and visualization assignments, we encourage candidates to use AI to:

  • Brainstorm data model designs
  • Design ETL Pipelines using prompts
  • Create transformation logic by using natural language inputs

How It's Working

What we’ve found is that leveraging AI in training has accelerated the learning curve. Our trainees grasp complex concepts faster. When a mentor isn’t immediately available, they can ask the AI to explain a concept in various ways until they understand.

We can tell that our newest trainees perform better at problem-solving. Instead of getting stuck and frustrated, they learn to collaborate with the AI to explore optimal solutions. Because of this, we have noticed that trainees feel empowered to tackle more complex tasks with AI support.

By adopting an AI-driven approach in our Technology Accelerator program, we aimed to develop forward-thinking data professionals who actively integrate AI tools into their daily work. This isn’t just a change in the curriculum – it’s truly a shift in mindset.