Let’s start with the obvious. No, you cannot actually cheat your way through an Orion Innovation interview. The title is sarcastic, of course. The real message is this: companies used to hire people who could code. Now, we hire people who can think. If you’re looking for a shortcut, here it is. Think better, think deeper, and think clearly. That’s the only strategy that works.
Orion Innovation is the company I work for, so – Just Kidding 😊
AI Skills Are Not Optional Anymore
It is no longer enough to say “I used ChatGPT” or “we integrated OpenAI APIs.” Everyone is doing that. What sets candidates apart is their ability to think with AI, to architect smarter solutions using the capabilities of large language models (LLMs), Retrieval-Augmented Generation (RAG), and intelligent agents. Whether it’s building a contextual chatbot using vector embeddings and Azure OpenAI, or designing a lightweight agent workflow for orchestrating tasks across APIs, these patterns are slowly becoming core competencies.
For programmers, this means AI API integration is becoming baseline knowledge, not a differentiator. If you are building a web app, can you inject AI-powered search that uses cosine similarity and FAISS? If you’re designing a helpdesk, can you explain the trade-offs between using an LLM agent vs. fine-tuned intent classification? We expect you to go beyond just calling .generate() on an API. We want to know how you handle token limits, prompt chaining, retry strategies, and context window constraints.
One solid example came from a candidate who used GitHub Copilot to scaffold a set of microservices, then built a debugging assistant powered by LangChain agents that could trace logs, match error patterns, and suggest fixes in real-time. That’s not “AI for show” – that’s strategic use of AI to deliver engineering velocity.
AI is becoming your second brain. The interviewers are watching how well you train it to think with you, not for you.
Productivity Gain
We are no longer impressed just because someone used AI in their project. What we look for is how they used it. Did you rely on GitHub Copilot to write boilerplate, or did you fine-tune it to accelerate solutioning? Do you just paste prompts into ChatGPT, or do you refine and iterate based on what you get? A smart candidate once described how they used GitHub Copilot to scaffold a REST API interface in minutes, but then used it further to auto-generate unit tests based on edge cases they had in mind. That wasn’t just about speed. It showed foresight, clean separation of logic, and the ability to design testable code using AI as a strategic partner, not a typing assistant.
Programming Fundamentals Still Matter
You might think, “Why learn sorting algorithms when AI can do it for me?” Fair question. But in interviews, what matters is how you apply logic. Can you decide when to use a hash map instead of a tree? Can you explain the difference between asynchronous and event-driven workflows? Do you know how to secure an API or how to apply design patterns like Circuit Breaker in a microservices architecture? AI can help you code, but it cannot help you reason (yet) if your fundamentals are weak. One candidate lost momentum in a senior round because he could not map his solution to any known enterprise integration patterns. The answers were technically right, but architecturally lost.
Be Memorable, Not Predictable
Want to stand out in an interview? Be the person who adds something unexpected. One candidate casually mentioned he used the Well-Architected Framework Security pillar to benchmark a customer’s PaaS platform. He didn’t just throw jargon. He broke down the implementation, his approach to monitoring, and how the team handled policy violations. That level of depth makes you memorable. It is not about being flashy. It is about being grounded and precise in what you bring to the table.
Use ‘We’ for Projects, ‘I’ for Ownership
In any project story, you need both perspectives. Say “we” when talking about what the team achieved. Say “I” when explaining your personal contribution. For instance, “We built a digital claims platform on Azure using event-driven design. I worked on designing the claims validation engine using Durable Functions and Cosmos DB change feed to maintain eventual consistency.” This balance shows collaboration and accountability.
Speak the Language of the Interview
Technical interviews often become cloud/AI-centric. When that happens, don’t just say you deployed something on Azure (eg.). Say you designed for high availability using Azure Front Door, or you followed the Performance Efficiency pillar of the Well Architected Framework to optimize your workloads. Using the right language shows maturity. It signals that you understand cloud not just as a deployment platform, but as an architectural ecosystem.
The Format is Changing. Expect Scenarios, Not Questions
If you are just starting your career, someone might ask “What is a binary tree?” But that will likely be the only basic question. Everything that follows will revolve around your past work or applied thinking. You will hear questions like “How would you design a rules engine for dynamic pricing?” or “What trade-offs did you consider in your API rate limiting strategy?” Interviewers are not interested in your textbook memory. They are interested in how you approach open-ended, real-world problems.
JD is Not Just a Checklist. It’s Your Script
Most candidates treat the Job Description like a box-ticking exercise. That is not enough. Read it carefully. Ask yourself where you align. Then prepare to sound like someone already doing that job.
If the JD asks for coding skills, then speak like a coder. Use class names, method signatures, filenames, packages, and module references in your answers. For example, “I handled logging by injecting a custom middleware in our app.module.ts that extended NestJS’s built-in LoggerService.” That’s a sentence only a real hands-on developer would say. And it makes all the difference.
You need to transform your storytelling to match the role you are interviewing for. Interviewers can feel it when you do.
AI is Already in the Interview Panel
The interview process is evolving. Many companies are testing AI-based interview assistants to conduct screening rounds or even full technical interviews. These tools analyze tone, clarity, response structure, and confidence. They may ask standard questions, but they are also learning to adapt. Don’t take it personally if your round feels mechanical. Instead, treat it as a challenge. Can you stay calm and clear even when the other side is not human? That resilience will matter.
No Nonsense, Just This
There is no hack, no prompt, no smart shortcut to crack an interview if you cannot think. But if you can think: clearly, logically, and with awareness of the tools and technologies around you, then you are already ahead of the curve.
Just prepare like someone who already does the job. Let your stories, your thinking, and your language do the rest.
