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Forbes
3 days ago
- Business
- Forbes
Sorry, DevOps: Garbage Data Can Only Generate Garbage AI Outcomes
Savinay Berry is the Executive Vice President and Chief Product Officer for OpenText. As artificial intelligence (AI) continues to evolve, we've seen more and more of its capabilities and limitations. We've witnessed AI perform tasks once deemed futuristic, reminiscent of scenes from sci-fi pop culture, such as Hanna-Barbera's iconic 1960s cartoon, The Jetsons. In this animated series, nearly every aspect of life is automated, from housework and meal prep to fashion, depicting a world where AI plays a central role in daily activities. While exaggerated, the show prompted me to contemplate exactly what role AI can—and should—play in helping product leaders deliver the next generation of innovation. Specifically, I began to wonder: How can AI be integrated into DevOps strategies as more than just a tool, but as a strategic ally—an extension of software development teams. The benefits of AI in DevOps—from automating testing and deployment to improving resource management and enhancing security—are driving increased investment. The "2024 Developer Survey" from Stack Overflow revealed that 76% of developers are using or planning to use AI tools, up from 70% last year. Notably, 81% cited productivity gains as the biggest benefit, while 62% valued accelerated skill development. As an innovator, I've already seen AI refine operations, simulating human intelligence across workflows. AI and automation offer unparalleled opportunities to reimagine software delivery. It streamlines resource-intensive areas such as testing, code-writing and deployment, all while ensuring compliance and security. AI and automation can also autogenerate test scripts, adding ready-to-go test scenarios to plans in a single click, as well as creating anticipatory project reports to pinpoint potential risks that could jeopardize software quality. And this is only scratching the surface of what is possible. So, What's The Issue? The risks of not adopting AI are significant and go beyond the DevOps community—it is a larger CIO issue. According to a recent survey from OpenText, 96% of respondents are using, testing, or planning to explore AI across their organization. Moreover, 78% believe failing to leverage internal data effectively will squander AI's potential. This seems promising, but the reality is more nuanced. In DevOps, the intersection of AI and operations goes beyond implementing advanced algorithms; it demands a robust foundation of organized, high-quality data. Without this foundation, achieving desired AI outcomes becomes a formidable challenge, and we risk stumbling at the first hurdle. Cleaning Up Your Data Is More Than Fixing Spreadsheets Understanding the role of information management means recognizing that AI thrives on high-quality data. The expression "garbage in, garbage out" applies here. If data isn't managed for accuracy and accessibility, desired AI results won't be achieved. High-quality data, on the other hand, sets the stage for success. Consider a car engine: Removing deposits and sludge (inaccurate, outdated, irrelevant and incorrect information) reduces friction, while clean oil (large language models and AI) ensures smooth performance. Much like good car engine maintenance, effective information management ensures longevity and optimal performance, generating superior and enduring AI results. Remember, even the most skilled data scientists and developers can't achieve optimal results without reliable data. And while many businesses understand AI's dependence on quality data, few feel ready to act on it. It's a shame because only organizations that govern, unify and protect their information will unlock AI's full, transformative potential. Optimize Your AI Initiatives With Quality Data Is your AI engine running on premium data? For DevOps teams, maximizing value starts with a solid information management foundation. Begin with these five steps: 1. Audit Your Data: Conduct a comprehensive review of all data assets (data logs, appdev dashboards, metadata, etc.) across cloud and on-premises storage. Identify data sources, formats and quality to build a knowledge base for AI workflows that can support faster application delivery, automated testing and intelligent code suggestions. Clean historical data also improves time-to-market predictions. 2. Set Data-Governance Standards: Adhering to data governance standards ensures that the applications they build comply with privacy regulations and industry standards. Establish clear data-governance protocols to safeguard privacy and ensure proper data management. Consistent, high-quality data flows are essential for reliable AI results, making effective governance paramount. 3. Implement Continuous Data Integration: Embrace an ongoing process to integrate disparate datasets into a unified format suitable for AI analysis. This continuous aggregation ensures AI assistants have a relevant and useful foundation for effective functionality. This can reduce the burden on not only application developers, but also quality assurance testers and managers, as accurate results can be assured every time. 4. Secure Data Flows: Prioritize data security and align your practices with regulatory requirements and industry standards. Implement proactive validation checks and AI-driven threat detection to maintain data integrity and security. Developers must incorporate security best practices, such as encryption and access controls, into their data handling processes. 5. Enhance Data Accessibility: Enable conversational search interfaces and AI assistants to access relevant datasets from multiple knowledge bases, when your information is clean. These tools can empower developers to optimize the software delivery cycle and reduce delivery times. With tools like this, clients I've worked with were able to maximize test coverage in less time and on (or under) budget, while enjoying greater access to high-level insights. Elevating DevOps With AI Through Information Management AI and automation have already shown their potential to enhance operations and productivity. However, the next step is sustainable and scalable AI. This evolution is essential for reimagining business information ecosystems and elevating people to become innovative leaders, rather than late adopters. As technology leaders, we stand at the forefront of the AI revolution, and we must recognize that information management is not merely a support function, but the catalyst for AI excellence. Effective information management not only boosts AI capabilities, but it also encourages innovative, targeted and successful application development, delivery, execution and measurement. Embracing information management as a cornerstone of AI-driven progress is the key to achieving the level of product excellence that once seemed like science fiction. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Time Business News
6 days ago
- Business
- Time Business News
How Swift App Application Development Is Fueling Business Growth
Businesses today are racing to build fast, reliable, and secure mobile applications. The competition is fierce. Customers expect more. They want smooth interfaces, instant load times, and secure payments. This is where Swift shines. If you're not using Swift, you're already behind. Why Swift Matters More Than Ever Swift has become the preferred language for iOS development. Apple launched it in 2014. Since then, it has rapidly evolved. According to a 2024 Stack Overflow survey, Swift ranks among the top 10 most loved programming languages. Developers love it because it's clean and easy to learn. Businesses love it because it reduces development time and increases app performance. Apps built with Swift run faster. They crash less. They use memory more efficiently. These advantages directly impact user satisfaction. That's why leading companies like Lyft, Airbnb, and LinkedIn use Swift. Speed Isn't Just a Bonus. It's a Necessity. In today's digital world, every second counts. According to Google, 53% of users abandon a mobile site if it takes more than three seconds to load. If your app lags, your customers leave. Swift minimizes that risk. Swift's performance is up to 2.6x faster than Objective-C. This speed isn't just about loading screens. It improves animations, API calls, and background processing. In short, it delivers a snappy user experience. Cost-Efficient and Scalable Swift helps businesses scale. Startups and enterprises alike save costs by using Swift's modern syntax and developer-friendly structure. It takes less code to build the same features compared to Objective-C. Fewer lines of code mean fewer bugs. Fewer bugs mean lower costs in testing and debugging. Moreover, Swift supports dynamic libraries. These get loaded only when needed. It reduces app size and memory usage. So your app stays lightweight as you scale. Security Built Into the Code In a world filled with data breaches, Swift adds a layer of safety. It uses strict typing and error handling. Developers catch mistakes early. This means fewer crashes and less vulnerability. Apple has invested heavily in making Swift secure. The language's design eliminates common coding mistakes. Features like optional and type inference reduce the chances of null pointer errors—a major cause of app crashes. Better Integration With Apple's Ecosystem If your app targets iOS, Swift offers unmatched integration. Swift works seamlessly with Apple's frameworks like SwiftUI, ARKit, and Core ML. This unlocks powerful features—augmented reality, machine learning, voice processing—all optimized for iOS. When you choose Swift, you future-proof your app. Apple continues to roll out new updates and APIs with Swift in mind. This makes upgrades easier. And it ensures your app stays compatible across all Apple devices. Working With a Swift App Development Agency Choosing the right team matters. A specialized Swift app development agency brings deep domain expertise. They understand Swift's nuances. They know how to build scalable, secure apps that align with Apple's best practices. Agencies also help reduce time to market. With pre-built modules, UI components, and third-party integration expertise, they accelerate the development process. This means you go from idea to App Store faster. If you're thinking long-term, partnering with an experienced Swift app development agency gives you the edge. They don't just build apps. They craft experiences. Key Industries Benefiting From Swift App Application Development Healthcare Apps need to be secure, fast, and intuitive. Swift enables HIPAA-compliant apps with robust performance. From telemedicine to fitness trackers, Swift handles it all. Fintech Security is the top concern. Swift's safe programming eliminates common vulnerabilities. Plus, high-speed performance is ideal for real-time transactions and biometric logins. Retail and E-Commerce Speed and responsiveness influence conversions. Swift ensures that your product pages, cart updates, and checkouts happen instantly. Swift's seamless integration with Apple Pay adds an extra layer of convenience. Education and E-learning Interactive and immersive apps help retain users. Swift supports advanced animations, video playback, and gesture recognition. This elevates learning apps into engaging experiences. Challenges You Might Face (And How to Overcome Them) Yes, Swift is powerful. But it's not without its hurdles. For example, hiring experienced Swift developers can be challenging. The demand outpaces supply. The solution? Work with a Swift app development agency. They have pre-vetted talent who can jump in right away. Another challenge is backward compatibility. Swift updates frequently. This may cause compatibility issues. Again, a professional agency stays ahead of updates. They ensure your app remains stable and future-ready. Real Results from Swift Apps Let's talk numbers. According to a 2023 Sensor Tower report, apps built with Swift showed a 23% higher retention rate after 30 days compared to apps built with older languages. This isn't just a technical metric. Higher retention means more revenue, better user engagement, and stronger brand loyalty. Even startups are seeing the impact. A Berlin-based travel app rebuilt their iOS app using Swift. Their crash rate dropped by 45%. Their App Store rating jumped from 3.8 to 4.6 in just two months. Actionable Insights for Your Swift Strategy Start small. Build a minimum viable product (MVP) in Swift. Use SwiftUI for faster UI development and native Apple look and feel. Invest in automated testing early. Swift works great with XCTest. Keep your codebase clean. Swift's syntax encourages clarity. Use that to your advantage. Don't try to go solo. Partner with a reliable Swift app development agency to get the most from your project. What's Next for Swift? Apple is all-in on Swift. With tools like SwiftData and Vision Pro coming into the picture, Swift will be the gateway to next-gen app development. If you want your app to thrive in the Apple ecosystem, Swift isn't optional—it's essential. Swift's versatility is expanding beyond iOS. With initiatives like Swift on the server, you can now build full-stack apps in Swift. This creates a unified tech stack, faster development cycles, and simplified team management. The future is bright. But only if you act now. We're Just Getting Started Swift is more than a programming language. It's a business growth engine. Whether you're building a fitness tracker, a finance app, or an educational platform, Swift gives you the tools to succeed. If you've made it this far, chances are you're serious about building something impactful. Don't let complexity or lack of resources hold you back. Leverage the power of Swift app application development and partner with a top-tier Swift app development agency. You'll save time, reduce costs, and create an app that users love. If this blog gave you something valuable, share it. Link to it. Let others benefit too. Together, we can build smarter, faster, and better. TIME BUSINESS NEWS
Business Insider
7 days ago
- Business
- Business Insider
5 Googlers who started as interns share their advice on securing a full-time offer
With internship application season in full swing, you might be wondering how to make the most of your summer gig — and how to turn it into a full-time offer. Landing an internship at a Big Tech company is highly competitive, but having one on your résumé can help you get in early. Google offers general online guidance for navigating the hiring process, including practicing coding on platforms like CodeLab, Quora, and Stack Overflow. The company also suggests keeping your résumé to one page and considering skills relevant to the role. Business Insider spoke to five former Google interns who turned their summer gigs into full-time job offers at the tech giant. They shared their process of landing internships at Google and advice on landing a permanent offer. If you want direct insight from the perspectives of those who landed internships and turned them into full-time jobs, keep reading. Nancy Qi Nancy Qi graduated in the winter and planned to return to Google full-time last June after spending three summers there as an intern, the first two with STEP and the last with Google's Software Engineering internship. Her primary advice: start early. Qi said she started taking data structure classes in high school at a community college and was practicing with leet code the summer before she started college, well before she had interviews lined up. When Qi started sending out applications in the fall of her freshman year, she said her résumé mainly had website initiatives and leadership experience for volunteering clubs from high school. She said she also had some part-time tutoring experience teaching math and English, " I think at that age, you're not expected to have so much CS experience or coding experience," Qi said. "So I think if you have some leadership experience or experience that shows your character, I think that's important at that time." During her internship, Qi said she thinks her strong suit was building relationships with her teammates by getting lunch with them every day. She said doing helped to create "team chemistry," and she also said it helped her feel excited for work and "motivated to pump out code." Islina (Yunhong) Shan Islina (Yunhong) Shan interned at Google three times, beginning in the summer of 2022. She graduated from an accelerated computer science Master's program at Duke University and started a full-time role as a software engineer at the tech giant this spring. Shan first participated in STEP and later in the Software Engineering Internship, which is a more competitive program geared toward technical development. When she applied for her first internship, Shan said she had some hackathon experiences and some technical projects from school. After she sent her résumé, she was invited to two rounds of final interviews, both of which were technical and back-to-back, she said. Her advice to interns hoping to secure full time jobs: choose a team during the match process that you're actually interested in. "Interest is really important in driving you to finish the project," Shan said. She also said it's important to choose a team with a manager you can see yourself working with because you'll have to communicate with them regularly. When she first started her internship, she said she set unrealistic goals. Once she adjusted expectations, she started seeing more progress. Shan suggested seeking help if needed, adding that Google engineers tend to be friendly. Lydia Lam Lydia Lam graduated from college in 2024 and participated in three Google internships, beginning with a STEP internship in 2021. In her internship résumé, Lam included a seven-week Google program for high-school graduates called the Computer Science Summer Institute. She also had experience with a summer program for girls who code and a tech consulting student organization that she joined during her first semester of college. Lam also recommended applying early in the recruiting cycle and said programs geared toward first and second-year students tend to be more aligned with that experience level. Lam said "strong engineering practices" are highly valued at the company and mentioned feeling imposter syndrome and wanting to impress her internship host. However, she said asking questions sooner rather than later can help projects get done more quickly. "It's much more efficient to ask someone else who knows a lot more than you try to figure it out longer," Lam said. She also suggested "producing a lot of artifacts," whether designs or other "tangible pieces of work," that can help show your skill set and contributions. Tawfiq Mohammad Tawfiq Mohammad interned for two summers at Google before becoming a full-time software engineer at the tech giant. He said the summer after his first year in college, he didn't have any internships, so he took summer classes and did his own projects at home, like a gadget that read the license plate on his car and opened the garage without him having to press a button. Mohammad's biggest advice for incoming interns is to be prepared for imposter syndrome. Mohammad said the "biggest block" for him at first was being scared to do anything, and he suggested tuning out those negative feelings as much as possible. "You're going to feel very out of place initially," Mohammad told BI. "I honestly felt like I had no idea what I was doing." He said interns should set a goal to "learn as much as possible" from the more experienced employees and try to believe that they, too, felt like they didn't fully "know what they were doing" at one point. " They're really smart so you want to absorb as much information as you can from them," Mohammad said. He also suggested thinking "outside the box." " You're going to be given a project that summer and try to own that project. Try to own it from A to Z," Mohammad said. He also recommended networking with other interns and team members, adding that Google provides a number of opportunities to do so. "It's good to build up a good network of successful people and it's just good to network with people that are farther along the career path than you," Mohammad said. Zachary Weiss Zachary Weiss interned at Google for three summers before landing a full-time job as a software engineer in the Cloud department. He said he wasn't thinking about summer internships when he started as a freshman at the University of Michigan, but an older computer science major encouraged him to apply to Google's STEP program. Weiss said he was "ecstatic" to get the offer from Google a few months later. He went on to intern in multiple teams before returning full-time as a software engineer on the Cloud team. The Googler had two main takeaways from his internships, one of which was the importance of showing a "concerted effort" to management. Google interns are given a summer project, and Weiss said that being proactive and anticipating problems in advance is key to the job. He said a former internship manager complimented him for identifying an issue with a "one in a thousand" chance of occurring. He said interns should think about all the "weird edge cases" and speak up instead of waiting for a manager to say something. "You're given work that would have been going to a full-time employee," Weiss said, adding that employees value your opinion and voice. Weiss said communication was another key skill that he didn't anticipate would be so pivotal. He said that in school, students tend to focus on learning the principles, algorithms, and data structures involved in programming. In a workplace, though, verbal skills matter, too, Weiss said. "My day-to-day, I speak a lot more English. I read a lot more English. I read and write and talk and communicate a lot more than I am actually coding," Weiss said. "And I think communication is something that's really important." He said that at the University of Michigan, there were three courses about technical communications, like writing design memos, emails, and presentations. He said many students didn't take the class seriously, and it ended up teaching a crucial skill.
Techday NZ
09-06-2025
- Business
- Techday NZ
Stack Overflow, Databricks partner to boost AI knowledge
Stack Overflow has entered into a partnership with Databricks to make its Knowledge Solutions datasets available through the Databricks Marketplace. This integration, supported by Delta Sharing, provides customers with direct access to technical knowledge and code verified by millions of contributors across the Stack Overflow platform and Stack Exchange Network. According to the companies, the collaboration will give Databricks Marketplace users access to what is described as a comprehensive and trusted resource for technical knowledge, which can be used alongside internal knowledge sources within enterprises. Stack Overflow stated that it remains focused on supporting its community of public platform users, enterprise customers, and partners by evolving its offerings and ensuring knowledge sets are available within ecosystems and marketplaces dedicated to data, analytics, and AI solutions. The Stack Overflow public platform's body of knowledge, which the company says is continuously updated through community contributions and user feedback, will form part of the knowledge-as-a-service offering within the Databricks Marketplace. Jay Bhankharia, Senior Director of Marketplace and Data Partnerships at Databricks, said: "As enterprise demand for data intelligence grows, we're thrilled to integrate Stack Overflow's Knowledge Solutions datasets into the Databricks Marketplace. Stack Overflow has long been a pillar of developer knowledge and collaboration, and this integration brings that trusted expertise directly into the data and AI ecosystem. This partnership reflects our shared vision of empowering data-driven enterprises with high-quality, context-rich intelligence that evolves with the needs of both the community and the industry." Prashanth Chandrasekar, Chief Executive Officer of Stack Overflow, said: "Whether it's using Stack Overflow for Teams, integrated development environments, or in chat apps we continue to strive to support our community in meeting them wherever and however they like to work to deliver a world-class experience that makes their lives easier. Our goal is to set new standards with vetted, trusted, and accurate data that will be the foundation on which technology solutions are built and delivered. By joining the Databricks Marketplace, we expand this ecosystem enabling communities to continue to share knowledge while redirecting LLM providers and AI product developers to have pathways for fair and responsible use of community content." Databricks Marketplace offers data, analytics, and AI assets from a range of providers, with Delta Sharing enabling cross-platform and multi-cloud data access with security and governance. The introduction of Stack Overflow Knowledge Solutions follows other recent integrations of Stack Overflow data into the Moveworks AI Agent Marketplace and Snowflake Marketplace earlier this year. Stack Overflow continues to play a pivotal role in supporting developers and technologists worldwide through its public and private platforms. As one of the most visited websites globally, Stack Overflow enables millions of users to ask questions, share insights, and access technical knowledge exactly when they need it. Its flagship collaboration tool, Stack Overflow for Teams, is used by more than 20,000 organisations to streamline knowledge distribution, boost operational efficiency, and accelerate innovation. The platform's focus on community-driven learning and real-time support has solidified its position as a market leader in developer enablement and technical collaboration. Follow us on: Share on:
Time of India
08-06-2025
- Business
- Time of India
AI agents boost developer productivity
Bengaluru: AI tools have boosted developer productivity by 30% in their daily tasks. Many tech companies are actively exploring ways to further enhance developer efficiency using GenAI tools. Stack Overflow CEO Prashant Chandrasekar believes that AI is freeing up developers for more meaningful work. "From our perspective, AI agents don't replace developers. They free them up to focus on higher-order tasks—creative, strategic, or architectural work. The best agentic AI tools give developers back time and energy, helping them learn new technologies and make a greater impact," he said. According to Thejesh G N, an independent technologist, researcher, and hacker, AI agents are helping programmers grasp business concepts, leading to more efficient code writing. "It helps identify logic behind code. It helps us identify a business case of a line of code and tweak it accordingly," he said. Generative AI has become popular amongst developers as a comprehensive solution. "Explain a problem and it fetches the best possible outcome unlike a Google search where we have to dig out information. One can ask the agent to write code for a particular functionality," Sujit Sharma, Senior Director, Software Engineering Management at ServiceNow, said. by Taboola by Taboola Sponsored Links Sponsored Links Promoted Links Promoted Links You May Like 2 BHKs starts at ₹ 72.6 Lakh | No Floor rise | Zero PLC Mahindra Happinest Tathawade Get Quote Undo These tools are quickly becoming popular among developers, offering a more comprehensive solution. Sharma said that his team increasingly relies on AI agents instead of product managers to understand business processes. These agents generate code summaries, streamlining the development process further. Beyond coding, AI tools are also taking over routine and operational tasks. Bebi Negi, Senior Lead Data Scientist at Happiest Minds, uses generative AI for generating weekly reports and managing access permissions. "Currently, these tools handle 10% to 20% of tasks, freeing up a similar portion of my time by eliminating repetitive work," she notes. For developers, AI is automating traditionally manual tasks such as writing test cases. AI is proving especially helpful for senior developers overseeing junior teams. "GenAI is extremely beginner-friendly. Most freshers struggle to write proper code, but with AI, they can generate functional code and get the job done," said Thejesh. However, he cautions that beginners may not fully grasp the reasoning behind AI-generated code. A deeper understanding of programming logic, he says, still requires real-world experience. AI is also emerging as a quality assurance and management tool. Arindam Ray, vice-president at Maveric Systems, who leads the company's North America engagements, emphasizes that most AI agent deployments are still in the pilot phase. "They haven't taken over technology-related work yet. Right now, it's mainly about boosting internal productivity," he says. Chhavi Sharma, a product manager and India community member, uses GenAI for large-scale data analysis. According to her, success with AI hinges on crafting precise prompts. The evolution of agentic workflows is leading to smarter orchestration across the development lifecycle. Jitendra Dulhani, a manager and developer at Deloitte India, explains how agents now understand their roles within complex tasks and can coordinate among themselves. "For instance, in a migration case, one agent could identify the source and target languages, create a detailed migration plan, and delegate tasks to other agents—one handling the actual migration, another validating the output. The entire orchestration is becoming more dynamic and intelligent," he said.
