InfoQ Culture Methods

FEBRUARY 25, 2021

Machine learning is a powerful new tool, but how does it fit in your agile development? Developing ML with agile has a few challenges that new teams coming up in the space need to be prepared for - from new roles like Data Scientists to concerns in reproducibility and dependency management. By Jay Palat.

Machine Learning 128

Machine Learning Artificial Inteligence Agile Development 128

InfoQ Culture Methods

JANUARY 7, 2022

This article presents how to use data science to detect wastes and impediments, and concepts and related information that help teams to figure out the root cause of impediments they struggle to get rid of.

Software Development 104

Software Development Data Software Trends 104

O'Reilly Media - Ideas

NOVEMBER 22, 2022

Chander Damodaran of Brillio noted that, “the culture of sharing solutions, frameworks, and industry-leading practices” has been a crucial part of Brillio’s journey. Similarly, Tim Hope said that open source is critical in building an engineering culture and developing systems. That’s an important statement.

Open Source 79

Open Source Engineering Culture Weak Development Team Fractional CTO 79

Altexsoft

MARCH 3, 2023

Cross-functional teams in Agile Agile project management can be characterized by iterative development. This means the product development takes place in stages, where each further stage is an improvement over the previous one. So, cross-functional team approach is a fundamental aspect of Agile project management.

Examples 52

Examples UI/UX Development Technical Review 52

LeanEssays

JULY 14, 2019

Furthermore, no interactions or data exchanges were allowed except through API’s. If you give software engineers manual work, their first instinct is to automate it. The earliest technical problems centered on how to store all that data, and then how to search it.

Software Review 91

Software Review Software Engineering Continuous Delivery Technical Review 91

InfoQ Culture Methods

FEBRUARY 24, 2023

In this article, Tariq King describes the metaverse concept, discusses its key engineering challenges and quality concerns, and then walks through recent technological advances in AI and software testing that are helping to mitigate these challenges.

Testing 126

Testing Engineering Software Artificial Inteligence 126

LaunchDarkly

JANUARY 14, 2020

At the November Test in Production Meetup in San Francisco, LaunchDarkly’s Yoz Grahame (a Developer Advocate) moderated a panel discussion featuring Larry Lancaster, Founder and CTO at Zebrium, and Ramin Khatibi, a Site Reliability Engineer (SRE) and infrastructure consultant. You come from a data and AI background.

Weak Development Team 10

Weak Development Team DevOps Testing Agile 10