Technical Review Testing Weak Development Team 
TechCrunch
OCTOBER 25, 2022
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.
CIO
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. This technology already exists.”
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TechEmpower CTO
SEPTEMBER 25, 2023
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!)
CIO
NOVEMBER 13, 2024
But a substantial 23% of respondents say the AI has underperformed expectations as models can prove to be unreliable and projects fail to scale. Sometimes it actually creates more work than it saves due to legal and compliance issues, hallucinations, and other issues. It gets beyond what we can manage.”
AWS Machine Learning - AI
MARCH 4, 2025
As systems scale, conducting thorough AWS Well-Architected Framework Reviews (WAFRs) becomes even more crucial, offering deeper insights and strategic value to help organizations optimize their growing cloud environments. This allows teams to focus more on implementing improvements and optimizing AWS infrastructure.
Hacker Earth Developers Blog
DECEMBER 26, 2024
Why its important: A shorter Time to Hire generally reflects an efficient recruitment process, allowing your team to remain productive and ensuring that candidates dont lose interest due to a lengthy hiring process. Why its important: Quality of Hire directly impacts team performance, innovation, and culture.
TechCrunch
JULY 14, 2022
In the rush to build, test and deploy AI systems, businesses often lack the resources and time to fully validate their systems and ensure they’re bug-free. In a 2018 report , Gartner predicted that 85% of AI projects will deliver erroneous outcomes due to bias in data, algorithms or the teams responsible for managing them.
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