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Business Insider
21 hours 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.
Forbes
05-06-2025
- Business
- Forbes
Cracking The Code: How AI Revolutionizes Software Development
As more organizations awaken to the power generative AI holds for building software, this guide can light the way. Few practices stand to benefit from today's generative AI boom more than software development. Prompting GenAI systems to create code reduces repetitive processes and accelerates production cycles, freeing developers to focus on new, higher value projects. The upside is likely a big reason why 78% of developers surveyed by Stack Overflow said they were using AI-assisted programming tools to save time on routine tasks. Excitement aside, developers face learning curves while using GenAI to create code. Fortunately, Dell and NVIDIA have created this eBook, which follows a day in the life of a software developer whose team is tasked with conceptualizing a proof-of-concept (PoC). When Sam, an early career programmer, arrives at the office Monday morning she opens Jira and learns that her IT leadership team has requested a PoC sketch for a mobile shopping application. Building such a PoC could take multiple workdays but Sam knows that with the help of the company's coding assistant, named Clarion, she can quickly produce a mockup while minimizing mistakes. With her plan in mind, Sam begins prompting Clarion: You're a software developer. Please write a sample function for a mobile shopping app. Choose the most optimal language, such as Java or Python, to build the app. Sam watches her screen as Clarion instantly produces credible code that would have taken her an hour or more to write and refine. Clarion elected to write the code in Java, a choice Sam approves of given its track record of success in mobile app development. Going the extra mile in case leadership wants broader functionality, Sam prompts Clarion to connect the script via an API call to the Shopify mobile shopping service. Again, Clarion produces the code in seconds. But how does Sam know if the code is clean enough to work? She could pore over it line by line but not today. Sam asks Clarion to test and validate the code: Pretend you're a quality assurance tester. Execute a quality assurance test for the mobile app shopping script above. Be sure to debug the script and validate the code. Explain your work. Clarion quickly produces a debugging script and executing code validation. Moreover, knowing that documentation is a critical proof point for PoCs—or really any software development enterprise—Sam asks Clarion to document the entire technical process. Clarion does so in seconds. Reflecting on the process, Sam realizes that streamlining such tasks reduces the cognitive workloads on developers while enhancing overall code quality. Although Sam is excited by the potential of Clarion to turbocharge productivity for her IT organization, she is also pragmatic. As impressive as the output is, it's just the start. Leadership will expect a storyboard, wireframe and user interface schematics to flesh out a minimum viable product. She and her team must also check Clarion's work, consistent with her organization's guidelines for ensuring a human remains in the loop throughout the development process. Regardless, Sam huddles with her developer team, they check the code in and present the PoC to leadership. They are impressed by all the team accomplished in such a short time. Sam's scenario presents a snapshot of the potential productivity impact of GenAI. And as coding assistants advance, they will likely create a flywheel leading to more breakthroughs in AI—and corresponding productivity boosts. In time, McKinsey expects GenAI will alter the software development lifecycle, improving product quality while freeing teams to spend more time on higher-value work, including innovation that improves the user experience for internal stakeholders or customers. Regardless of the path organizations choose to take using GenAI to augment software development, they will need trusted expertise to help pick use cases, as well as robust technology infrastructure on which to deploy them. Dell Technologies and NVIDIA can help your organization leverage AI to drive innovation and achieve your business goals. The Dell AI Factory with NVIDIA delivers capabilities to accelerate your AI-powered use cases, integrate your data and workflows and enable you to design your own AI journey for repeatable, scalable outcomes. From NVIDIA accelerated computing, software and networking technology to Dell servers, storage and professional services, the Dell AI Factory with NVIDIA helps organizations achieve the optimal outcomes from their AI use cases. As GenAI reshapes the software development landscape, is your organization ready to seize on this shift? Learn more about the Dell AI Factory with NVIDIA.
Techday NZ
04-06-2025
- Business
- Techday NZ
Snowflake boosts AI with real-time licensed content access
Snowflake has introduced Cortex Knowledge Extensions, allowing enterprises to supplement their AI agents with real-time, licensed content from third-party publishers, with Stack Overflow among the first partners to join the Snowflake Marketplace. The introduction of Cortex Knowledge Extensions enables enterprise customers to enrich their AI applications and agents with updated, reliable content from publishers such as Stack Overflow, USA TODAY, and Packt. This approach ensures proper attribution and licensing of content, distinguishing it from other systems that use scraped material without consent from original publishers. According to Snowflake, this new capability is designed to address challenges faced by both enterprises and publishers. Enterprises often struggle to gain access to timely external information for their AI systems, limiting accuracy and depth of insight. Meanwhile, publishers are seeking a secure and fair way to allow their content to be used by enterprise AI, with assurance of both compensation and control. "Building powerful AI apps and agents at scale hinges on enterprises having access to a wealth of internal and external data that adds rich context to AI outputs. Snowflake is raising the bar on enterprise-wide collaboration to make it even easier for customers to fuel their AI initiatives with AI-ready data and harness the power of agentic apps — regardless of whether the data and apps reside within their own four walls or come from trusted third-party sources. Our latest innovations enable teams to turn possibilities into reality with data and AI, all without worrying about security and governance risk," Prasanna Krishanan, Head of Apps & Collaboration and Horizon at Snowflake, commented on the launch. With Cortex Knowledge Extensions, publishers are able to list their content, such as news articles, textbooks, and research papers, on the Snowflake Marketplace. Enterprises can then purchase this content and integrate it into their AI-powered apps and agents, including Cortex Agents, Cortex Search, and the soon-to-be-available Snowflake Intelligence. This functionality enables AI systems to provide responses informed by timely and relevant information while allowing publishers to monetise their intellectual property under agreed licensing terms. The mechanism for delivering content through Cortex Knowledge Extensions relies on retrieval-augmented generation and is underpinned by Snowflake's Zero-ETL Sharing functionality. This setup empowers publishers to revoke access to content if necessary, while always displaying clear attribution and links to the original source, thereby enhancing reliability and provenance. Alongside Cortex Knowledge Extensions, Snowflake has introduced Semantic Model Sharing, which is currently in private preview. Semantic Model Sharing allows enterprises to integrate and interact with AI-ready structured data within their Snowflake Cortex AI applications — whether the data originates from internal sources or third-party providers. The use of semantic models helps ensure consistency in how data and business concepts are defined and applied across different systems, contributing to more trustworthy and accurate AI outputs. By mapping internal data to standardised semantic models, enterprises can accelerate insights, support more uniform decision-making, and access industry-standard metrics while maintaining governance and version control. Snowflake reports that these advances are intended to eliminate the manual effort required to create semantic models internally, while supporting high-quality, context-rich, and accurate AI responses. Users can directly interact with their data using Semantic Model Sharing in Cortex AI, including Cortex Analyst, Cortex Agents, and Snowflake Intelligence. In addition to content and model sharing, Snowflake is adding support for Agentic Native Apps in its marketplace. This feature provides customers with access to third-party agentic applications, which can securely combine provider and consumer data within the enterprise's governance framework. Data remains within the customer's environment while agents perform tasks such as portfolio management and optimisation, using proprietary algorithms and datasets. Currently, Snowflake Marketplace connects enterprises with over 750 providers, offering more than 3,000 live data, application, and AI products. The introduction of Agentic Native Apps is intended to give providers new ways to distribute and monetise their offerings while allowing enterprises to drive additional value from their data without compromising privacy or security.
