Latest news with #engineeringteams
Yahoo
2 days ago
- Business
- Yahoo
Technical Program Manager Interview Prep Course Launch - Interview Kickstart's FAANG TPM Experts Share Interview Preparation Secrets
Santa Clara, Aug. 06, 2025 (GLOBE NEWSWIRE) -- As the world moves deeper into 2025, the role of Technical Program Managers has evolved from simple project coordinators to strategic leaders who drive innovation and ensure the successful delivery of complex technical initiatives. In today's rapidly changing tech landscape, companies are dealing with increasingly sophisticated projects that involve multiple teams, cutting-edge technologies, and tight deadlines. This complexity has made Technical Program Managers more valuable than ever before, as they serve as the crucial bridge between technical teams and business objectives. Recognizing this growing demand and the specialized skills required, Interview Kickstart has developed a comprehensive Technical Program Manager Course that prepares professionals for these strategic leadership roles at top technology companies. To learn more about the course, visit: The modern Technical Program Manager needs to understand not just project management principles, but also the technical details of the systems they're managing. They work closely with engineering teams to design scalable architectures, coordinate releases across multiple products, and ensure that technical decisions align with business goals. This dual expertise in both technical and management domains makes them essential for companies trying to move fast while maintaining quality and reliability. In 2025, Technical Program Managers are expected to have a deep understanding of system design principles, especially when it comes to building scalable solutions. They need to know how different components of a system work together, understand the trade-offs between different architectural choices, and be able to communicate these concepts clearly to both technical and non-technical stakeholders. This technical depth allows them to make informed decisions about project priorities, resource allocation, and timeline planning. Given these evolving requirements, traditional project management training is no longer sufficient for aspiring Technical Program Managers. They need comprehensive preparation that combines technical knowledge with program management skills, which is exactly what Interview Kickstart's Technical Program Manager Course provides. The course is specifically designed to prepare professionals for the demands of modern TPM roles at top technology companies. The course spans 15 to 17 weeks and provides a thorough foundation in both technical concepts and program management principles. Students dive deep into data structures and algorithms, which helps them understand the technical challenges their engineering teams face. This knowledge is crucial when making decisions about project scope, timeline estimation, and resource planning. The scalable system design modules teach students how to think about building systems that can handle growth, which is essential knowledge for any TPM working on products that need to scale. What makes this course particularly valuable is its industry-relevant curriculum that includes 4 to 6 weeks of training on specific technical domains. Students can choose to focus on areas like data engineering, machine learning, data science, frontend development, backend systems, site reliability engineering, test engineering, Android development, iOS development, and more. This specialization allows future TPMs to develop deeper expertise in the areas most relevant to their career goals, making them more effective in their roles. The course requires a significant commitment of 10 to 12 hours per week, which includes live sessions where students interact with instructors and peers, practice solving coding problems, and participate in live doubt-solving sessions. This hands-on approach ensures that students don't just learn theory but also develop practical skills they can apply immediately in their work. The 1:1 personalized coaching from FAANG professionals provides invaluable guidance from people who have successfully navigated TPM roles at the world's most demanding tech companies. One of the most valuable aspects of the program is the 15 mock interviews with FAANG+ interviewers. These practice sessions simulate real interview conditions and help students understand what top companies are looking for in Technical Program Manager candidates. The feedback from these sessions is incredibly detailed and helps students identify areas for improvement before they face actual interviews. In a job market where Technical Program Managers are in high demand but companies have very specific requirements, having comprehensive preparation makes all the difference between landing the target role and continuing to search. For more information, visit: About Interview Kickstart Interview Kickstart, founded in 2014, is a trusted upskilling platform designed to help tech professionals secure roles at FAANG and other leading tech companies. With over 20,000 success stories, it has become a go-to resource for career advancement in the tech industry. The platform offers a flexible learning experience with live classes and over 100,000 hours of on-demand video lessons. This ensures learners have the tools they need to dive deep into technical concepts and refine their skills on their own schedule. Additionally, 1:1 coaching sessions provide personalized support in areas like resume building and LinkedIn optimization, enhancing each learner's professional profile. ### For more information about Interview Kickstart, contact the company here:Interview KickstartBurhanuddin Pithawala+1 (209) 899-1463aiml@ Patrick Henry Dr Bldg 25, Santa Clara, CA 95054, United States CONTACT: Burhanuddin Pithawala
Forbes
30-07-2025
- Business
- Forbes
How Engineering Teams Are Reimagining Work Through AI
Bratin Saha, Chief Product and Technology Officer at DigitalOcean, tech executive with 20 years of experience across AI and cloud computing. AI is one of the most transformative technologies of our time. Given the rapid pace of AI innovation, it seems that practically every leader is thinking about how they can reimagine their work using AI. While this may be daunting and will take persistence, I believe the reward is well worth it. Having worked on many projects using AI, I want to discuss the factors that are critical to ensuring the success of these projects—from an iterative mindset to new mechanisms and rigor in tracking metrics. AI For Coding AI is rapidly emerging as an indispensable tool for software engineers. As teams explore AI-powered coding assistants, it's essential to look beyond 'lines of code generated' and consider impact on code quality, security and long-term maintainability. Many engineering teams are now experimenting with tools like GitHub Copilot, and we've personally seen up to 40% increases in code generation. But productivity isn't the only metric worth tracking—security, code quality and maintainability are just as critical. One helpful practice is to implement internal evaluation systems that compare AI-generated and human-authored code for defects, rollback frequency and overall impact on velocity. Our initial findings suggest that AI-generated code can match or even outperform human benchmarks in some areas, though consistent monitoring remains essential. For leaders considering similar integrations, there are a few principles that can help guide responsible adoption. Define baseline metrics early, evaluate AI output with the same rigor applied to human-authored code and build feedback loops to inform ongoing tool selection. Thoughtful experimentation combined with clear evaluation criteria is key to realizing the value of AI without compromising quality or trust. AI For Rootcausing Cloud Incidents One way of figuring out where to add AI is to understand where your employees are spending the most time and then automating that activity with AI. Cloud engineers, for instance, typically spend over 20% of their time troubleshooting incidents. Additionally, high availability is critical for customers who rely on cloud services. AI can play a powerful role in accelerating incident resolution, especially when engineers are spending a significant portion of time on root cause analysis. As an example, we developed a GenAI-powered site reliability engineer (SRE) agent that assists engineers by analyzing real-time logs and telemetry to find root causes autonomously during incidents. Engineers can ask follow-up questions and rate accuracy. By eliminating the need to assemble multiple engineering teams for incident triage and diagnosis, this approach can help reduce the time and effort required to resolve issues and restore the service faster. Accuracy is one of the crucial measures of the agent's effectiveness, and achieving that was an iterative process. The agent needs to be trained on high-quality, representative data; it needs to be tightly integrated into incident response workflows with real-time access to observability systems; and it must have mechanisms to learn from new incidents and user feedback. Besides encouraging engineer feedback, one thing we found beneficial is to incorporate the agent into the post-incident review (PIR) process. This retrospective analysis refined the agent's accuracy and functionality by clarifying incident causes and guiding engineers on prompt optimization. Once the agent meets your predefined success metrics, you can then expand its role. In our case, we extended the agent role beyond reactive incident response. By embedding the agent earlier in the incident lifecycle to monitor system alerts, the agent can automatically assess alerts and propose root cause solutions, significantly reducing investigative time for engineers. These continuous and targeted improvements are key to building a successful GenAI agent. AI For Server Maintenance Another way to figure out how to use AI is to consider operations where data analysis can be used to avoid undesirable outcomes and help teams move from a reactive mode (fire fighting) to a proactive mode. For example, server downtime in a data center is undesirable because it directly impacts the service uptime. Servers usually do not fail out of the blue; there is a pattern of malfunction that can be detected by closely monitoring server health with AI tools. At DigitalOcean, we use AI to analyze logs in real time, providing a confident root cause to engineers. This analysis can help repair machines faster while reducing repeat outages. We also collect messages that are emitted by the operating system or the out-of-band management controllers of servers, and perform a rules-based evaluation to trigger the removal of workloads from at-risk machines. If a stick of RAM issues a hardware warning or a disk array degrades in a production hypervisor, AI can automatically migrate customer and internal workloads to healthy machines. Companies can use similar techniques that use AI to perform a real-time analysis of relevant metrics to drive operational improvements and use predictive rather than reactive operations. In Conclusion AI is already changing every aspect of how we work, and it is important for leaders to get in front of it. The most important part is to get started; identify some workflows that are ripe for automation, put together a tiger team and give them the latitude to experiment till they get the AI right. Even if the initial experiments do not work, the learnings are invaluable and set you up for success down the road. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Yahoo
28-07-2025
- Business
- Yahoo
Full fibre broadband rollout begins in Woolston to boost speeds
Work is now under way on a full fibre broadband network that will transform connectivity. Openreach has begun building the new infrastructure in Woolston, promising gigabit-capable speeds and improved reliability for homes and businesses. The upgrade will enable faster streaming, smoother video calls, and better support for growing data needs across multiple devices. Martin Williams, Openreach partnership director for Hampshire, said: "We're bringing full fibre broadband to Woolston and letting local people know what to expect. Crews use existing ducts to speed up fibre installation process (Image: Openreach)READ MORE: AI phone assistant reduces cataract wait times "This is a major infrastructure upgrade, so there will be more engineering teams, equipment and vans around town, and we're working hard to keep disruption to a minimum." He added that most of the work will use existing ducts and poles to reduce roadworks and avoid installing new street furniture. However, Martin warned that in some areas, new underground ducts, fibre cables, or poles may still be needed to ensure all properties are included in the upgrade.
Associated Press
09-07-2025
- Business
- Associated Press
Turn Every Challenge into a Breakthrough – PRIZ Guru Unveils Change Flow Thinking Tool for Engineers and Innovators
WILMINGTON, Del., July 09, 2025 (GLOBE NEWSWIRE) -- PRIZ Guru, the provider of an all-in-one Engineering Thinking platform, has launched Change Flow Thinking (CFT) – a game-changing tool that transforms how companies tackle complex engineering challenges. Billed as the ultimate 'stubborn challenge to celebrated win' machine, CFT guides teams through a systematic yet creative problem-solving journey, from pinpointing root causes to implementing innovative fixes. The result? Resilient, high-quality solutions delivered with scientific precision, turning every tough problem into an opportunity for measurable impact. PRIZ Guru's latest offering underscores its mission: to elevate engineering teams from reactive troubleshooting to proactive innovation, ensuring organizations can generate the innovative solutions that they need to stay competitive and profitable. The CFT Difference What sets Change Flow Thinking apart is its unique ability to merge change and risk management with systematic innovation tools into one visual workflow. In practice, CFT acts as a central command center for improvement projects: engineers map each step of a proposed change, flag potential risks or roadblocks, and collaborate on solutions in real time. Using CFT, a team can chart an entire production line upgrade on a single screen – linking every task to responsible owners, expected costs, and risk levels. If a step is marked 'problematic' or 'blocking,' the team can instantly run a root-cause analysis (like 5 Whys or Cause-and-Effect Chain) within the same platform. 'Change is inevitable; CFT makes it manageable by illuminating the entire path from idea to implementation,' said the product manager at PRIZ Guru. By combining all facets of problem-solving into one flow, CFT ensures teams are fully equipped to convert even the toughest problems into innovative solutions that keep businesses ahead of the competition. Strategic Business Impact PRIZ Guru emphasizes that CFT isn't just an engineering tool – it's a strategic business enabler. Every problem solved systematically is a competitive edge gained. By using CFT, companies can prevent costly failures and seize opportunities that would otherwise be missed. Hidden factory issues that once drained resources now become fuel for innovation. With clearer visibility and quantifiable risk, managers make faster, smarter decisions – accelerating time-to-market. Early users have reported dramatic reductions in unplanned downtime and scrap thanks to CFT's early identification and mitigation of potential blockers. 'PRIZ empowers you to flex your critical-thinking muscle and deliver high-quality solutions with systematic precision – from uncovering root causes to driving continuous innovation,' said a PRIZ spokesperson. Key Features & Benefits Leadership Quote 'Our goal with CFT was to create the ultimate problem-solving workflow – one that turns stubborn engineering puzzles into celebrated breakthroughs,' said Alex Agulyansky, CEO of PRIZ Guru. 'We've essentially closed the gap between identifying a root cause and implementing the solution. Now, an engineer can map out a complex change, analyze every risk, generate innovative solutions, and get management buy-in – all in one place. This means faster solutions, smarter use of resources, and teams that win accolades for overcoming challenges that once seemed impossible.' A New Way of Thinking To support adoption, PRIZ Guru provides robust onboarding, training, and facilitation. From interactive workshops to one-on-one guidance, PRIZ helps engineering teams master systematic innovation. Managers also receive training to instill a culture of continuous improvement and measure ROI. 'It's not magic – it's method,' the team emphasized. 'We've seen reactive teams become proactive innovators by embracing this structured way of thinking.' About us: Change Flow Thinking is now available as part of the PRIZ Guru platform. Teams can try CFT in the PRIZ Playground for free by visiting Interested teams are also invited to a live demo webinar on July 16, 2025, where the PRIZ team will showcase CFT using real-world examples and answer questions on integrating the tool into existing workflows. Reserve Your Spot With CFT's launch, PRIZ Guru delivers a clear message: every problem is a potential breakthrough – with the right tools, every team can innovate with confidence and clarity. Contact: Alex Agulyansky [email protected] Disclaimer:This content is provided byPRIZ Guru. 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Forbes
26-06-2025
- Business
- Forbes
The Future Of Engineering Is Human-Led And AI-Powered
Sebastian Avila is the co-founder at Qualitara. In the past two years, AI tools have become deeply embedded in the way engineering teams operate. From generating boilerplate code to assisting with architecture diagrams, AI is now part of the daily workflow. But despite this rapid adoption, the demand for experienced engineers continues to rise. This shift is creating a new dynamic in modern engineering teams, where success depends on how well human expertise and machine capabilities work together. From Writing Code To Guiding Systems Tools like Cursor and Windsurf are eliminating repetitive coding tasks. Engineers are spending less time on boilerplate and more time reviewing, integrating and validating AI-generated code. The role of a senior engineer is becoming less about doing every task and more about making sure the right decisions are being made across the system. They are setting direction, validating outcomes and ensuring that the software being shipped actually serves the business. Like autopilot still requires an experienced pilot for critical decisions, engineering teams still need experienced leaders who know when to intervene, how to adapt and where to go next. Where AI Performs Well AI delivers real value in several areas: • Identifying bugs, inconsistencies and code smells across large codebases. • Generating documentation and summarizing legacy code with speed and accuracy. • Enforcing standardized patterns across microservices and infrastructure. • Automating unit tests, regression tests and common implementation details. • Accelerating code generation by helping developers move faster on standard components and avoid 'blank screen' delays. • Assisting in code reviews by flagging common issues and suggesting improvements early in the development cycle. These capabilities improve consistency and free up time that engineers used to spend on repetitive tasks. Where AI Falls Short And Human Judgment Takes Over Despite these advances, AI tools are still limited in ways that become clearly evident without strong senior oversight. They are only as good as the data they have seen and the patterns they can generalize. That is not enough when it comes to solving nuanced, evolving or high-stakes engineering problems. Here are key areas where AI continues to struggle and where senior engineers play a critical role: AI tools can suggest patterns or optimize resource usage, but they lack the foresight and trade-off analysis required in architectural decisions. They cannot anticipate how a system needs to scale over time, deal with edge-case reliability concerns or weigh performance against maintainability. In enterprise settings, architect-led reviews typically uncover issues in AI-generated proposals. Often, these adjustments involve rethinking core components because the AI lacked an understanding of business context, security policies or long-term goals. Forrester emphasizes ongoing human validation as essential. Only experienced engineers can make these calls effectively. They factor in company-specific constraints, regulatory risks and organizational readiness, which AI is not equipped to evaluate. AI lacks an inherent understanding of secure-by-design principles. It can unintentionally replicate insecure code patterns from public datasets, omit essential validation steps or suggest outdated dependencies with known vulnerabilities. For example, an AI tool once suggested downgrading a runtime environment to fix a compatibility issue. However, a senior engineer recognized that the recommended version was no longer supported and posed security vulnerabilities. Their intervention prevented a potentially critical exposure. Senior engineers play a crucial role in reviewing AI outputs through a security lens. Their knowledge of up-to-date practices, threat models and system dependencies helps ensure that AI-assisted development does not introduce avoidable risks. AI tools can generate a wide array of test cases based on past failures or code coverage gaps. However, they frequently miss critical business-specific scenarios or edge conditions that are not well represented in historical data. Senior quality assurance (QA) leads often catch the majority of high-priority test gaps. They understand what absolutely must not fail and apply domain-specific knowledge that AI cannot learn on its own. When AI-generated fixes introduce regressions, it is experienced engineers who step in to restore system stability. Why Senior Engineers Matter More Than Ever AI is making development faster but not necessarily better unless experienced engineers are there to guide the process. Their value is not in doing what AI can do but in knowing what AI cannot. Senior engineers today are doing more of the following: • Evaluating when AI-generated solutions are viable and when they need to be challenged. • Balancing immediate gains with long-term architecture integrity. • Translating between business needs, user behavior and technical feasibility. • Designing resilient systems that evolve with the product, not just meet today's needs. • Coaching developers to use AI productively and with critical thinking. These functions cannot be automated. In fact, as AI becomes more deeply integrated, these roles become even more vital. Teams that lack senior oversight often find themselves drowning in technical debt, security gaps and disconnected solutions that fail to meet real needs. Data supports this shift. Research from IBM and MITSloan indicates that engineers trained or mentored in AI tool usage can see productivity gains of up to 40% or more. But without mentorship, adoption plateaus and quality suffer. The best-performing teams are those where human and machine strengths are combined, not where AI is left to run unsupervised. Additionally, while AI enhances productivity, organizations must recognize that senior oversight remains essential. Continued investment in experienced talent is critical to maintaining quality and managing the increased complexity that comes with integrating AI. AI Is Not A Replacement—It Is An Accelerator The evidence is clear: AI is not here to replace senior engineers. It is here to support them, to extend their reach and to elevate the quality and speed of the work they deliver. Far from making human expertise obsolete, AI is increasing the value of experience, judgment and leadership in software development. The most successful engineering teams are not those that automate everything but those that learn how to combine human insight with machine efficiency. Senior engineers who embrace this shift are not becoming less relevant—they are becoming more strategic, more impactful and more essential than ever. AI is not making great engineers disappear. It is making them even better. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
