At Tesla’s bustling Nevada Gigafactory, engineers huddle around sleek, futuristic car designs. Amid the flurry of activity, a silent partner operates in the background, enhancing every decision and innovation: artificial intelligence (AI).

In this real-world crucible of innovation, AI isn’t just a tool; it’s a catalyst that transforms visions into reality. At Tesla, AI powers everything from predictive maintenance to optimizing manufacturing processes, embodying the cutting-edge of product engineering. This isn’t just about faster production; it’s about reimagining what’s possible, making cars safer, more efficient, and more in tune with the driver’s needs than ever before.

But how exactly does AI achieve this? Which tools are behind these groundbreaking advancements? In this blog, we’ll delve into the role of AI in product engineering, highlighting its impact at every stage of the product lifecycle, from initial concept to final rollout.

The Role of AI in Product Engineering

AI has brought about remarkable changes in the product development lifecycle. Today, product developers employ AI-driven technologies to solve complex problems with maximum efficiency and precision, in a fraction of the time.

Incorporating AI into the engineering process offers an array of benefits. For example, with the help of AI, developers can analyze data faster and more accurately, helping them make more informed decisions.

Unlocking Creativity and Efficiency: AI in Product Development

There are several stages in product development, and AI can be utilized in each. Here’s how:

1. Ideation and Conceptualization

The first step is brainstorming sessions where stakeholders put forward their ideas. Some of these are taken forward based on market trends. In this stage, AI analyzes the variables to help teams identify gaps in the market and develop products to plug them.

2. Design and Prototyping

During this stage, Generative AI provides a range of design variations. With the help of virtual prototyping that mimics real-world scenarios, testing and validation can be conducted without having to develop physical prototypes.

3. Testing and Quality Assurance

When the product is taken forward for testing, AI helps by generating testing frameworks and setting up predictive analytics. By learning patterns of behavior, AI models can detect anomalies before they happen, enabling early detection of potential issues.

4. Manufacturing and Production

AI can be employed to optimize the manufacturing process. AI analyzes real-time data to isolate inefficiencies in the manufacturing process. The right tools can also keep an eye on inventory levels, triggering supply increases or pauses as needed to keep the supply chain intact.

5. Maintenance and Lifecycle Management

After the product is manufactured and released, it all comes down to periodic maintenance. Many AI tools help developers predict issues and assist with overall application lifecycle management.

AI Tools to Enhance Each Product Engineering Stage

Miro Assist: Ideation and Conceptualization

Miro Assist is a whiteboard tool that helps teams in the early stages of product development, when stakeholders are discussing ideas. It enhances each brainstorming session and fills the gaps with AI.

What it offers

  • Sticky notes to summarize discussions
  • Text-to-visual converter
  • User story mapping through user personas
  • Sequence diagrams for an overview of the main idea
  • Code block generation with its natural language processing abilities

Why you should consider it

User-friendliness: Miro’s intuitive interface and simple layout make it easy to use even by a first-timer without extensive training.

Better collaboration: Miro’s collaboration features include integrated video chat and screen sharing to improve remote working.

Affordability: Miro is suitable for smaller businesses and startups, thanks to its free plan. The tool also offers premium features at different pricing plans

Who’s used it

When Karma Bot was being developed, the entire team was working remotely. Launching a product was no walk in the park! However, the founders of Karma bot used Miro Assist to make their brainstorming sessions more productive. After numerous such brainstorming sessions, they were able to get a visual overview of the product and the entire creation on the board.

The success of Karma was huge for their team which motivated them to publish Karma on the Slack app directory and the Product Hunt platform. Later, they also launched the product on MS Teams and Telegram. Today, more than one million users take advantage of the features of Karma and experience an improved work environment overall. And it all began on Miro Assist.

What else is out there

  • Brainstormer
  • Ideate
  • Conceptboard
  • Microsoft Whiteboard
  • ClickUp

Uizard: Design and Prototyping

Uizard helps teams to build interactive prototypes for software applications. With its pre-made templates, it’s easy to become inspired and create better designs. With its simple drag-and-drop function, users can easily begin designing.

What it offers

  • Auto-designer tool to create editable UI components
  • Scribble scanner to convert your hand-drawn sketches to editable UI mockups
  • Ability to extract colors from any image or screenshot and use them in your mockups
  • AI-generated insights that help improve the design
  • Interactive user experience elements that simplify your workflow

Why you should consider it

Time and cost savings: By automating several design processes and streamlining the workflow, Uizard saves teams significant time and money.

Quick iterations: Uizard lets designers iterate their designs instantly and endlessly. Designers can experiment with several different ideas, resulting in a much-improved design process.

Seamless cooperation: Designers can accept the changes as they are passed by the stakeholders and start working on the newly curated ideas right away.

Who’s used it

Care Technologies was creating a prototype for a mobile application to monitor heart activity. Since Care Technologies is a small startup, there were no designers on the team.

Since Uizard is extremely user-friendly, the team was able to prepare a 23-screen prototype of the software application. Care Technologies was hence able to gather the insights and proceed to the next stage of the application development.

What else is out there

  • Autofill by Figma
  • Maze
  • UserTesting
  • INVision
  • Marvel

Functionize: Testing and Quality Assurance

Functionize supports teams in their testing phase by letting developers execute self-healing tests. This also enables teams to test code faster and improve the overall quality of the CI/CD pipeline. This automation saves testers a lot of time and reduces expenses.

What it offers

  • Self-healing tests that are cloud-scalable
  • Automated testing and lower costs
  • Increased automation with integration into the DevOps cycle
  • Cross-browser and device testing
  • Collaboration tools and reporting features

Why you should consider it

Simplified testing: With NLP, Functionize lets anyone create a test by writing in plain English.

Rapid test creation: Functionize lets you write the biggest tests in the least time. It employs a cloud-based approach so you can execute hundreds and even thousands of tests simultaneously.

No need for test maintenance: With Functionize, you can reduce and almost eliminate the need for such a task, as Functionize’s Root Cause Analysis runs checks and suggests fixes.

Who’s used it

In 2017, Agvance decided to replace their Windows suite with a cloud-based application. They relied on a test suite that did catch bugs, but was brittle. Any minor change in screen size or migration from one Windows version to another caused many test failures.

Agvance chose Functionize, which facilitated easy testing with a point-and-click interface. The tool’s inbuilt smart DOM selection logic provided Agvance with a stable, robust, and automated testing solution.

What else is out there

  • LambdaTest
  • SmartBear
  • Testsigma
  • TestRail

Tabnine: Manufacturing and Production

Tabnine helps developers by predicting the code and providing code completion. With the help of ML, it learns the existing code and predicts the next lines of code, generates code snippets, and even creates classes.

Tabnine is especially helpful if you write code in JavaScript and Python as it makes faster and more accurate predictions in these two languages.

What it offers

  • Automatic creation of code, snippets, and even entire classes
  • Translation of natural language into code
  • Seamless integration with 15+ IDEs
  • Support for 30+ languages
  • SOC-2 compliance to ensure security and privacy

Why you should consider it

Faster delivery: By employing automation, Tabnine helps you develop code faster, increasing overall software delivery speed while simplifying testing and maintenance.

Reduced cost: Tabnine doesn’t just create code faster but also identifies bugs and issues and resolves them right away.

Seamless onboarding: Tabnine integrates an AI assistant to guide new developers in joining up. It explains the existing code, refines their skills, and makes recommendations.

Who’s used it

Nilesh, a technical blogger, shared his experience of using this tool during his coding sessions and how the tool helps him code faster. As Tabnine integrates flawlessly with a wide array of Integrated Development Environments (IDEs) and supports numerous modern programming languages and frameworks.

Even though Markdown and Powershell were not included in Tabnine’s list of supported languages, the tool took care of the context and provided recommendations with around 80% accuracy. This led him to save a significant amount of time, streamlining the workflow.

What else is out there

  • Codeium
  • TabbyML
  • Cursor
  • CodeGeeX
  • Cody

Jira Software: Maintenance and Lifecycle Management

Jira from Atlassian is another extremely useful tool that incorporates AI and ML to serve as an amazing lifecycle management tool. It’s an issue-tracking tool in Agile project management.

What it offers

  • Reports that provide statistics throughout the product lifecycle
  • Varied permission settings to allow and restrict access as needed
  • 800+ add-ons & plugins in the Atlassian Marketplace
  • Customizable dashboard to display preferred apps and gadgets
  • Roadmaps to showcase tasks based on priorities and urgency

Why you should consider it

Ease of use: Jira provides an intuitive interface where each user is presented with a dashboard and elements based on their acquired permission level.

Quick integration: Other tools from Atlassian – including Confluence, Bitbucket, and Bamboo – can be integrated seamlessly as per the requirement.

Atlassian community: Another benefit of using Jira is its community where you can post your queries and get them answered by other users.

Who’s used it

Twitter back in 2013 had a sudden increase in number of employees and was struggling with team communication due to an overwhelming flood of requests. With Atlassian’s Jira, Twitter gained an intuitive and scalable customer portal solution.

The effect was immediate. Everyone loved using Jira, and the IT team started getting fewer emails and tickets. Since the Jira service desk contained all the information, everything was easy to track and routed to the right people. In 2014, other teams at Twitter also recognized the efficiency of Jira and adopted it.

What else is out there

  • Asana
  • Trello
  • Zendesk
  • Basecamp
  • ServiceNow

What’s Next? AI’s Future in Product Engineering

It’s no secret that AI is the future. That’s true in product engineering too. Here’s a glimpse at the potential of this sector:

  • The global AI market is expected to reach $1345.2 billion by 2030.
  • McKinsey reports that AI technology has led businesses to an average reduction of 30% in the product development cycle time.
  • Gartner estimates that about 80% of enterprises will be using Generative AI APIs and models by 2026 in production environments.

From ideation to execution, AI helps product engineering teams deliver software applications and updates faster. For every stage of product development, an array of AI tools is available, some of which we’ve discussed above.

Choosing the right tools and optimizing their use can be difficult. The assistance of experts ensures that you integrate AI into your systems effectively. With years of experience and a passion for what we do, Ziffity prepares businesses for futuristic product engineering, harnessing cutting-edge technologies and driving success.

Contact us today to elevate your product engineering and stay ahead of the competition.