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Developers unimpressed by the early returns of generative AI for coding take note: Software development is headed toward a new era, when most code will be written by AI agents and reviewed by experienced developers, Gartner predicts. That’s what we call an AI software engineering agent.
IT leaders know they must eventually deal with technical debt, but because addressing it doesnt always directly result in increased revenue or new capabilities, it can be difficult to get business management to take it seriously. Add outdated components or frameworks to the mix, and the difficulty to maintain the code compounds.
Many CEOs of software-enabled businesses call us with a similar concern: Are we getting the right results from our software team? Most innovators don’t have a technical background, so it’s hard to evaluate the truth of the situation. The explanation from software leadership is often unsatisfying or unclear.
AI agents are valuable across sales, service, marketing, IT, HR, and really all business teams, says Andy White, SVP of business technology at Salesforce. An AI briefer could inform a sales pipeline review process, for instance, or an AI trainer could simulate customer interactions as part of an onboarding program, he adds.
Speaker: Eran Kinsbruner, Best-Selling Author, TechBeacon Top 30 Test Automation Leader & the Chief Evangelist and Senior Director at Perforce Software
Though DevOps is a relatively new role, it’s one that allows visibility across the whole operation, making it important to senior tech positions. While advancements in software development and testing have come a long way, there is still room for improvement. Understand the future of DevOps tied with AI/ML technologies.
In the fast-paced world of tech recruiting, finding the perfect candidate can feel like searching for a needle in a haystack. Resumes can be deceiving, and traditional interview formats may not always give you the full picture of a candidate’s technical abilities. This is where live coding interviews come in.
In a world where business, strategy and technology must be tightly interconnected, the enterprise architect must take on multiple personas to address a wide range of concerns. These include everything from technical design to ecosystem management and navigating emerging technology trends like AI.
Last summer, a faulty CrowdStrike software update took down millions of computers, caused billions in damages, and underscored that companies are still not able to manage third-party risks, or respond quickly and efficiently to disruptions. It was an interesting case study of global cyber impact, says Charles Clancy, CTO at Mitre.
As systems scale, conducting thorough AWS Well-Architected Framework Reviews (WAFRs) becomes even more crucial, offering deeper insights and strategic value to help organizations optimize their growing cloud environments. This time efficiency translates to significant cost savings and optimized resource allocation in the review process.
Understanding and tracking the right software delivery metrics is essential to inform strategic decisions that drive continuous improvement. This transformation requires a fundamental shift in how we approach technology delivery moving from project-based thinking to product-oriented architecture.
Why do people apply TDD? Here’s a secret: it’s not for the tests. Learn about the actual goal and values hidden under the surface of Test-Driven Development. What Are the Real Reasons for Doing TDD? Test-Driven Development (TDD) is a controversial topic amongst developers. Feedback on what?
Cloud technology is the new normal for tech-savvy people who consider themselves Digital Nomads. With the rise in a shift towards cloud technology, especially IT people, have changed the way they work. Moreover, they are privileged to get top-notch technology at affordable plans by upgrading an old device into a powerful PC.
From obscurity to ubiquity, the rise of large language models (LLMs) is a testament to rapid technological advancement. Just a few short years ago, models like GPT-1 (2018) and GPT-2 (2019) barely registered a blip on anyone’s tech radar. Let’s review a case study and see how we can start to realize benefits now.
For the past decade and a half, I’ve been exploring the intersection of technology, education, and design as a professor of cognitive science and design at UC San Diego. I’ve been intrigued by this emerging practice called “vibe coding,” a term coined by Andrej Karpathy that’s been making waves in tech circles.
However, in todays era of rapid technological advancement and societal shifts, especially over the past five years, relying solely on traditional approaches is no longer enough to stay competitive. Ultimately, AI should be treated not as a standalone tech initiative but as a core business capability that drives value and impact.
Verisk (Nasdaq: VRSK) is a leading strategic data analytics and technology partner to the global insurance industry, empowering clients to strengthen operating efficiency, improve underwriting and claims outcomes, combat fraud, and make informed decisions about global risks.
Regardless of the driver of transformation, your companys culture, leadership, and operating practices must continuously improve to meet the demands of a globally competitive, faster-paced, and technology-enabled world with increasing security and other operational risks.
All the conditions necessary to alter the career paths of brand new software engineers coalescedextreme layoffs and hiring freezes in tech danced with the irreversible introduction of ChatGPT and GitHub Copilot. Without writing the code, what is a list of tests youd write to assure full coverage of this component?
University recruiting is evolving rapidly, driven by changes in technology, student expectations, and shifting employer needs. From embracing technology-driven recruitment methods to focusing on diversity and inclusion, university recruiting is becoming more dynamic and strategic.
Most CIOs and CTOs are bullish on agentic AI, believing the emerging technology will soon become essential to their enterprises, but lower-level IT pros who will be tasked with implementing agents have serious doubts.
Noting that companies pursued bold experiments in 2024 driven by generative AI and other emerging technologies, the research and advisory firm predicts a pivot to realizing value. Forrester said most technology executives expect their IT budgets to increase in 2025. Others won’t — and will come up against the limits of quick fixes.”
By modern, I refer to an engineering-driven methodology that fully capitalizes on automation and software engineering best practices. This approach is repeatable, minimizes dependence on manual controls, harnesses technology and AI for data management and integrates seamlessly into the digital product development process.
New capabilities include no-code features to streamline the process of auditing and tuning AI models. While the Generative AI Lab already exists as a tool for testing, tuning, and deploying state-of-the-art (SOTA) language models, this upgrade enhances the quality of evaluation workflows.
In investigating this phenomenon, Ng found the practice is becoming increasingly common, especially at large companies and in sectors requiring high skills, such as information technology. Hunter Ng conducted research based on nearly 270,000 reviews from the “Interviews” section of the popular recruiting platform Glassdoor.
In the competitive world of hiring, particularly in tech, recruitment is no longer just about finding candidates with the right technical expertise. For tech teams tasked with solving complex problems, interpersonal skills ensure smoother collaboration, innovation, and productivity. Why interpersonal skills matter in tech hiring ?
Like an onion’s skin, recruiters uncover multiple layers in their recruitment process: sourcing, screening, and evaluation to find the best talent with the modern tech recruiting strategies that gel into your organization. Now, you can’t *just* hire tech candidates who are willing to work. You create a job description ?
Currently there is a lot of focus on the engineers that can produce code easier and faster using GitHub Copilot. Eventually this path leads to disappointment: either the code does not work as hoped, or there was crucial information missing and the AI took a wrong turn somewhere. Use what works for your application.
For example, in tech hiring, many successful developers are self-taught or have bootcamp certifications rather than computer science degrees. Skills-based hiring leverages objective evaluations like coding challenges, technical assessments, and situational tests to focus on measurable performance rather than assumptions.
Why its important: A shorter Time to Hire generally reflects an efficient recruitment process, allowing your team to remain productive and ensuring that candidates dont lose interest due to a lengthy hiring process. Quality of Hire Attracting a high volume of applicants is one thing, but attracting the right candidates is another.
Industry benchmark: The average Time to Fill can vary by industry, but for tech roles, it can range from 30 to 45 days. How HackerEarth can help: HackerEarths automated coding challenges and assessments allow you to quickly filter candidates based on their technical skills.
For the first time ever, I was laid off, and had to find a new software developer job. It’s quite good, but I didn’t use it much, because I wanted to make sure I did all coding by myself at interviews. It was definitely worth it, I did much better on the test than I would have, had I not practiced beforehand.
But CIOs need to get everyone to first articulate what they really want to accomplish and then talk about whether AI (or another technology) is what will get them to that goal. Otherwise, organizations can chase AI initiatives that might technically work but wont generate value for the enterprise. What ROI will AI deliver?
Weve developed our software such that the LLM open source or proprietary can be swapped in or out via configuration. Thats a problem, since building commercial products requires a lot of testing and optimization. We picked Metas Llama to be the model of choice due to cost, control, maintainability, and flexibility.
I guess I've always been fascinated with how well this has stood the test of time? Technology When joining, require a 6-18 months rewrite of core systems. Leverage any production issue as a reason to “pull the brakes” Introduce very complex processes for code change and common workflows. Blame the previous CTO.
Learn more about the key differences between scale-ups and start-ups Why You Need a Framework for Scaling a Business Many businesses fail not because of poor products or insufficient market demand, but due to ineffective management of rapid growth. Scaling challenges can overwhelm even promising startups without a systematic approach.
European regulators joined Microsoft, OpenAI, and the US government last week in independent efforts to determine if DeepSeek infringed on any copyrighted data from any US technology vendor. So far, Americas issues with Chinese technology have mainly been based around storing American-based data on overseas servers, Park explained.
Understanding Unit Testing Unit testing is a crucial aspect of software development, especially in complex applications like Android apps. It involves testing individual units of code, such as methods or classes, in isolation. Why Unit Testing in MVVM? androidTestImplementation 'androidx.test.ext:junit:1.1.5'
But beneath the glossy surface of advertising promises lurks the crucial question: Which of these technologies really delivers what it promises and which ones are more likely to cause AI projects to falter? These are standardized tests that have been specifically developed to evaluate the performance of language models.
I was happy enough with the result that I immediately submitted the abstract instead of reviewing it closely. Well, here’s the first paragraph of the abstract: In an era where technology and mindfulness intersect, the power of AI is reshaping how we approach app development. And how did he know?
They have structured data such as sales transactions and revenue metrics stored in databases, alongside unstructured data such as customer reviews and marketing reports collected from various channels. Its sales analysts face a daily challenge: they need to make data-driven decisions but are overwhelmed by the volume of available information.
Despite mixed early returns , the outcome appears evident: Generative AI coding assistants will remake how software development teams are assembled, with QA and junior developer jobs at risk. AI will handle the rest of the software development roles, including security and compliance reviews, he predicts. “At
While a firewall is simply hardware or software that identifies and blocks malicious traffic based on rules, a human firewall is a more versatile, real-time, and intelligent version that learns, identifies, and responds to security threats in a trained manner. Humans have traditionally been the weakest link in any tech setup or network.
Helm.ai, a startup developing software designed for advanced driver assistance systems, autonomous driving and robotics, is one of them. launched to push the technology forward with a new approach. co-founders Tudor Achim and Vlad Voroninski took aim at the software. The company has raised $78 million , to date. ” Helm.ai
As Robert Blumofe, chief technology officer at Akamai Technologies, told The Wall Street Journal recently, “The goal is not to solve the business problem. These technologies often do not undergo a complete vetting process, are not inventoried, and stay under the radar. The goal is to adopt AI.”
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