Remove Engineering Remove Software Review Remove Weak Development Team
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AI-native software engineering may be closer than developers think

CIO

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.

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8 questions to answer before your startup faces technical due diligence

TechCrunch

Will your organization and your code pass technical due diligence when it’s your turn? Let’s start with the positives: If an investor is proceeding with technical due diligence (TDD), you’ll likely pass. Here’s the not-so-good news: Companies can pass the business test, but fail TDD.

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The Top 20 Symptoms of a Weak Development Team

TechEmpower CTO

When speaking with founders and CEOs, we often hear concerns like this: My project manager is losing confidence in the development team. I think that poor communication and differing team cultures might be part of the problem, but how can I know for sure? This is where a technical review can be useful!)

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10 ways to kill your IT culture

CIO

Without a strong IT culture, inspiring IT teams to extend beyond their “run the business” responsibilities into areas requiring collaboration between business colleagues, data scientists, and partners is challenging. Additionally, 84% of leaders believed their organizations had strong teamwork compared to 60% of team members.

Culture 211
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The future of data: A 5-pillar approach to modern data management

CIO

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.

Data 167
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Simple sabotage for software

Erik Bernhardsson

You can of course make a series of obviously bad decisions, but you'd get fired quickly. Make sure production environment differs from developer environments in as many ways as possible. Leverage any production issue as a reason to “pull the brakes” Introduce very complex processes for code change and common workflows.

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When is data too clean to be useful for enterprise AI?

CIO

Once the province of the data warehouse team, data management has increasingly become a C-suite priority, with data quality seen as key for both customer experience and business performance. But along with siloed data and compliance concerns , poor data quality is holding back enterprise AI projects.

Data 211