CIO Business Intelligence
OCTOBER 17, 2024
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. This technology already exists.”
IT Toolbox
SEPTEMBER 12, 2022
Software developers differ from software engineers in 10 key ways, including their tools, salaries, and educational background. The post Software Developer vs. Software Engineer: Top 10 Differences appeared first on Spiceworks.
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Information Week
MAY 22, 2024
Will designing tools and workflows to bring self-service to software development help developers work more efficiently? A growing number of adopters think so.
CIO Business Intelligence
SEPTEMBER 26, 2024
Microsoft has announced the expansion of its Global Engineering Development Center to Abu Dhabi, marking a significant milestone in the UAE’s journey to becoming a global technology leader.
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With detailed pay rate data for top IT positions like Cybersecurity Consultants, Cloud Engineers, and Salesforce Developers, this guide is an essential resource for companies looking to stay competitive in today’s evolving workforce landscape. Download the guide to navigate 2024’s talent market with confidence.
IT Toolbox
JULY 26, 2024
OpenAI has introduced SearchGPT, an AI-powered search engine, while Microsoft has added AI features to its Bing search engine. Learn more about the development and its implications for the online search industry.
Forrester IT
JULY 25, 2023
The security operations center (SOC) has reached the same tipping point that software development faced many years ago: It’s dealing with too much data (big data and log management), struggling to innovate and update monolithic software (detection and incident response processes), and lacking ownership beyond initial deployment (content management). (..)
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Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes. Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics.
Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage
When developing a Gen AI application, one of the most significant challenges is improving accuracy. Using this case study, he'll also take us through his systematic approach of iterative cycles of human feedback, engineering, and measuring performance.
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Create the Optimal Environment for Developer Success. A software engineering team is most commonly measured by its outputs — the quality of the code delivered and the speed at which it was shipped. Yet the first step to achieving success is the inputs; leaders need to create an environment that enables developers to excel.
Speaker: Kim Burgaard, Head of Engineering at Fernish
Developer productivity is an output of many factors, including the people on the team, company culture, processes, and tools. Join Kim Burgaard, Head of Engineering at Fernish, for this enlightening talk on how to maximize your developers' productivity. Don't focus on points and velocity, but on value and outcomes.
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In this eBook, Christian Oestreich, a senior software engineering leader with experience at multiple Fortune 500 companies, shares how a metrics-driven mindset can dramatically improve software quality and enable DevOps at enterprise scale.
Speaker: Mark Ridley, Owner and Founder, Ridley Industries
Any PM or technical leader who’s led the charge of building a digital product knows that product engineering is one of the most expensive elements of business. How do you help your engineers get on board with buying instead of building? What happens to the business if the product provider switches off the service that was bought?
Speaker: Daniel "spoons" Spoonhower, CTO and Co-Founder at Lightstep
Many engineering organizations have now adopted microservices or other loosely coupled architectures, often alongside DevOps practices. Together these have enabled individual service teams to become more independent and, as a result, have boosted developer velocity. Understand a distributed system and improve communication among teams.
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However, they often struggle with increasingly larger data volumes, reverting back to bottlenecking data access to manage large numbers of data engineering requests and rising data warehousing costs. Why agile development concepts, when applied to the data tier, can dramatically increase data engineering agility.
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