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.”
CIO Business Intelligence
MARCH 4, 2025
The Block ecosystem of brands including Square, Cash App, Spiral and TIDAL is driven by more than 4,000 engineers and thousands of interconnected software systems. Today, Block is doubling down on engineering velocity, investing in major initiatives to help teams ship software even faster.
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Network World
JANUARY 15, 2025
My journey took me through roles as a validation engineer, logic designer, full-chip floor planner, post-silicon debug engineer, micro architect, and architect, he wrote. Last decade, the company developed a line of chips called Centriq but abandoned those efforts in 2018 and laid off its development team.
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.
Advertiser: Procom Services
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.
CIO Business Intelligence
JANUARY 23, 2025
Software developers are in demand. They must be developer-friendly because software development is not a traditional 9-to-5 job. Autonomy: The basis for innovation Autonomy is the essential element of a company that wants to create a developer-friendly work environment by expanding the scope and responsibility of employees.
CIO Business Intelligence
NOVEMBER 19, 2024
Imagine that you’re a data engineer. These challenges are quite common for the data engineers and data scientists we speak to. An enhanced metadata management engine helps customers understand all the data assets in their organization so that they can simplify model training and fine tuning. Seamless data integration.
Speaker: Dr. Greg Loughnane and Chris Alexiuk
Technology professionals developing generative AI applications are finding that there are big leaps from POCs and MVPs to production-ready applications. However, during development – and even more so once deployed to production – best practices for operating and improving generative AI applications are less understood.
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.
Advertiser: Datadog
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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