#software-engineering

#software-engineering

I moved to the US from India in 2021 to attend Amherst College, where I triple-majored in computer science, mathematics, and statistics. During my freshman year, I developed a support system for statistical programming that became part of an introductory statistics course. Opportunities to talk about my work on and off campus started coming up, which led to different perspectives, insights, and connections. I thought about how I could scale this up to a broader audience.

"While businesses aren't investing, it's hard to make much progress in the software world," Fowler said. "And so we have this weird mix of no investment, pretty much depression in the software industry, with an AI bubble going on."

IT development has been around for more than 60 years and it has undergone radical transformations from the emergence of the first programming languages and OS development to the internet boom and the current AI era. Although programming tools and approaches are constantly changing, one thing remains constant: Only those developers who can adapt and master new knowledge and skills survive.

Your competitors aren't building perfect code either. If you spend 6 months building the theoretically perfect architecture, they'll ship something "good enough" in 2 months and eat your lunch. You'll have beautiful code that nobody uses. Tech debt is the cost of moving fast enough to win. The biggest risk in software isn't technical debt-it's being irrelevant. Markets move fast. User needs evolve. Competitors iterate. While you're refactoring for the third time to achieve "clean architecture," your competitor is talking to users, learning what actually matters, and shipping features that solve real problems.

One of the most notable innovations is support for compaction, a technique that enables the model to seamlessly manage multiple context windows and perform tasks involving millions of tokens within a single session. This enables large-scale refactors, extensive debugging rounds, and work cycles lasting several hours. GPT-5.1-Codex-Max is available immediately within the Codex environment in the CLI, IDE extension, and cloud; API access will follow later.

At Ping Identity, we believe in making digital experiences both secure and seamless for all users, without compromise. We call this digital freedom. And it's not just something we provide our customers. It's something that inspires our company. People don't come here to join a culture that's built on digital freedom. They come to cultivate it. Our intelligent, cloud identity platform lets people shop, work, bank, and interact wherever and however they want. Without friction. Without fear.

technical skills don't cut it.

"Five years from now, we'll have more engineers working for our company than we do today," Cannon-Brookes said.

Booksy connects beauty, wellness and health professionals with local customers, powering millions of appointments annually. As a Booksy employee, you'll join a team of 800+ around the world building the fastest growing appointments marketplace. Regardless of the position you hold, you'll make a direct impact every day helping our providers grow their businesses and build loyal client relationships in their communities.

"As tasks get automated within a job, your output in that job can go up tremendously, and that will then have a different range of impacts depending on the segment that company is in, or depending on what role that person is in," Levie said. Software engineering has been at the center of the debate on job replacement, as AI coding tools have automated many aspects of the work, and many recent grads are struggling to find jobs.

The Role ITHAKA is looking for a Software Engineer to join the JSTOR Labs team. As Software Engineer, you will have a pivotal role in building the Transfer Explorer pilot application. The Transfer Explorer is a collaboration between Ithaka S+R and JSTOR Labs which aims to make it easy for students, school administrators, and advisors to see how earned credits and prior learning experiences will transfer and count toward a degree at a new institution.

Gill's prediction has come true: developers are now regularly using AI coding assistants to generate code, but the output is often buggy, forcing engineers to spend a lot of time on corrections. CodeRabbit can help catch some of the errors. The business has been growing 20% a month and is now making more than $15 million in annual recurring revenue (ARR), according to Gill.

On the "OpenAI Podcast," which aired on Monday, cofounder and president Greg Brockman and Codex engineering lead Thibault Sottiaux outlined a vision of vast networks of autonomous AI agents supervised by humans but capable of working continuously in the cloud as full-fledged collaborators. "We have strong conviction that the way that this is headed is large populations of agents somewhere in the cloud that we as humanity, as people, teams, organizations supervise and steer in order to produce great economical value," Sottiaux said.

I got my Master's in Computer Science in 2011, and like others, I got tracked into coding as a software engineer. I started my career as a Java engineer developing software applications. Six or seven years later, I came across the profile of machine learning. Machine learning was not in a boom at that moment. The projects we got were almost always software engineering; machine learning projects were really, really hard to get.

I started working at Google in December 2021 as a software engineer, based in New York. I spent three and a half years there and earned up to $326,000 in total compensation before taxes, but I became disillusioned with corporate life and, at age 27, I quit and became a creator and entrepreneur, traveling as a digital nomad. It's made me feel more fulfilled.

Olo's digital ordering, payment, and guest engagement solutions empower restaurants by boosting personalization, enhancing guest experiences, and optimizing operational efficiency in a competitive market.

Entering a new phase of software engineering, individuals are becoming addicted to agents. More people will create applications, necessitating new tools for support.

Nearly 100% of engineers at Robinhood are using AI code editors, making it hard to distinguish between human-written and AI-generated code, according to CEO Vlad Tenev.

When I built ZVDB, I deliberately applied every Z80 optimization I knew. Why? Because these 'old' techniques are timeless - they just happen to make modern code blazingly fast.