Across the industry, one thing is becoming increasingly evident: Artificial Intelligence (AI) is reshaping how software is delivered. Going beyond changing development workflows, AI is transforming how technology teams generate value and how organisations build for the future.
At Innominds, we’ve been working closely with our customers to adopt AI throughout the Software Development Lifecycle (SDLC). Our customers have begun seeing significant, measurable improvements in their product delivery and operational efficiency.
Traditional SDLC models, while mature, come with inherent challenges:
These challenges not only slow down innovation but also dilute the strategic potential of technology teams.
By adopting AI through tools like GitHub Copilot and our internally developed AI accelerators, we’re enabling our customers to rethink and modernize their entire software development process. The impact has been significant leading to:
These gains are not theoretical, but are indeed being realised by teams using our AI-augmented approach across our customers’ projects.
The true power of AI lies not in the tools alone, but in how we use them. A key enabler of success in our journey and one we emphasise with every customer is prompt engineering.
Prompt engineering is the discipline of crafting inputs that guide AI tools toward precise, relevant, and high-quality outputs. At Innominds, we apply advanced prompt engineering techniques such as:
These techniques ensure the outputs from tools like Copilot, and our internal GenAI agents, are:
Here are simplified examples:
| Few-shot Prompting for Test Case Generation | |
|---|---|
|
You are a QA assistant. Generate JavaScript unit test cases using Jest. Example 1: test('adds two numbers', () => {
expect(add(2, 3)).toBe(5);
});
Example 2: test('checks if number is even', () => {
expect(isEven(4)).toBe(true);
expect(isEven(3)).toBe(false);
});
Now generate test cases for: |
test('multiplies two numbers', () => {
expect(multiply(2, 3)).toBe(6);
expect(multiply(-1, 5)).toBe(-5);
expect(multiply(0, 10)).toBe(0);
});
|
| Meta Prompting for API Design | |
|
You are an API design assistant. Based on the business requirement below, generate a RESTful API specification in JSON format using OpenAPI 3.0. Business Requirement: |
{
"paths": {
"/register": {
"post": {
"summary": "Register a new user",
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"type": "object",
"properties": {
"fullName": {
"type": "string",
"description": "User's full name"
},
"email": {
"type": "string",
"description": "User's email address"
},
"password": {
"type": "string",
"description": "User's password"
},
"phone": {
"type": "string",
"description": "User's phone number (optional)"
}
},
"required": ["fullName", "email", "password"]
}
}
}
}
}
}
}
}
|
| Reasoning-Based Prompting for Impact Analysis | |
|
You are a software architect. A developer is proposing to remove the |
Step 1: Identify direct dependencies - User analytics module - Session management logic - Audit logging reports Step 2: Identify indirect dependencies - WAU (Weekly Active Users) metric - Admin dashboard widgets Step 3: Impact summary - Removing "last_login" would break analytics, session timeout rules, and dashboards. Step 4: Mitigation steps - Deprecate in schema v2 while keeping v1 - Use login events for session tracking - Update reports to use new tracking Risk Level: High Recommendation: Do not remove without a backward-compatible migration plan. |
Through our work with customers, we’ve built internal expertise in this area, developed domain-specific prompts, and created best practices that significantly improve AI output quality and consistency.
By adopting AI into the SDLC, we’re helping customers shift from reactive development to predictive, intelligent delivery. With AI taking care of SDLC tasks, teams can now focus on:
At Innominds, we help customers not just use AI, but apply it effectively across the full lifecycle—from design and development to testing, deployment, and beyond.
Software development is going to be intelligent, contextual, and faster than ever before. The organizations that will lead in this new landscape are those that not only adopt AI tools, but understand how to integrate them meaningfully into their software lifecycle.
At Innominds, we’re proud to be enabling that journey for our customers. Whether it’s AI-driven design, faster development, intelligent testing, or empowering teams through AI tools and prompt engineering, we’re focused on delivering results that matter. With the right strategy and the right partner, the results can be transformative.
Let’s build smarter, together.