Systems | Development | Analytics | API | Testing

AI Alone Won't Improve Productivity or Velocity

AI tools promise to revolutionize everything, but are they making us smarter or lazier? Here are the questions I still have about the real impact of AI in development. Are teams using AI to augment their work or replace themselves entirely? Process and social change are a no-brainer, but are we keeping up? Are we adapting or coasting? And the big question: As AI gets smarter, are we dumbing ourselves down, losing our grip on what it means to understand?

AI Regulation: More an Adoption Accelerator Than a Brake

The emergence and growing adoption of generative AI and the agreement to and implementation of the EU AI Act uncannily coincided. These two factors have catalyzed an AI renaissance within many enterprises. Yes, companies were already applying AI here and there across their organizations — but responding to the impact of these two exogenous forces required a whole new way of thinking and doing. All of a sudden, all eyes were on AI.

Supercharging Data Lakes: GenAI & Snowflake Advantage

In today’s GenAI-driven world, having the right data foundation is essential to unlock the full potential of AI. Traditional on-premise data lakes often fall short in scalability and agility, while even many cloud-based solutions struggle with reliability, performance, and governance. Join Ruchi Soni in this webinar to explore how Snowflake is democratizing access to data and intelligence with AI and large language models (LLMs).

Gen AI or Traditional AI: When to Choose Each One

When it comes to leveraging AI to capture business value, it’s worth asking, “what kind of AI do we need exactly?” There are significant differences between the methodologies collectively referred to as AI. While 2024 might have almost convinced us that gen AI is the end-all-be-all, there is also what’s sometimes called ‘traditional’ AI, deep learning, and much more.

The AI Tipping Point: What Healthcare and Life Sciences Leaders Need to Know for 2025

AI is proving that it’s here to stay. While 2023 brought wonder and 2024 saw widespread experimentation, 2025 will be the year that healthcare and life sciences get serious about AI's applications. But it’s complicated: AI proofs of concept are graduating from the sandbox to production, just as some of AI’s biggest cheerleaders are turning a bit dour.

Is AI Making Development Harder Instead of Easier?

AI was hyped as the big solution to developer productivity, but the 2024 DORA report paints a different picture. Here’s what’s holding teams back: Developers don’t need help writing code—they need time to write it. AI isn’t clearing their calendars of endless meetings. Tech debt and documentation remain roadblocks, and AI tools aren’t solving them. AI can assist, but it often acts like a junior dev—adding more work instead of reducing it.

Agentic AI: The Top 5 Challenges and How to Overcome Them

As generative AI continues its unprecedented surge in popularity, we are already seeing it evolve into the next generation of machine learning-driven technologies: agentic AI. With agentic AI, we are not just prompting models and receiving an answer in a simple one-step process. The AI is engaging in complex multi-step processes, often interacting with different systems to achieve a desired outcome.

AI in Software Development: Transforming How We Build Applications

According to a report by Verified Market Research, the Artificial Intelligence software development market will reach USD 2740.46 billion by 2031. AI has seamlessly integrated into the Software Development Life Cycle (SDLC), becoming a crucial tool for developers. By blending human creativity with AI, developers can achieve more ingenious and efficient outcomes.

Gen AI in Action: Customers Use Cortex AI to Save Time and Personalize Customer Experiences

For years, companies have operated under the prevailing notion that AI is reserved only for the corporate giants — the ones with the resources to make it work for them. But as technology speeds forward, organizations of all sizes are realizing that generative AI isn’t just aspirational; it’s accessible and applicable now.

How to Drive Business Growth with Innovation. Interview with Sean Everett | The Innovation Blueprint

Welcome to Episode 6 of The Innovation Blueprint! This time, we’re diving deep into the impact of AI, data, and digital tools on real estate investment and business scaling. Our guest? Sean Everett, CEO of Evergence — a company that helps executives and boards tackle tough scaling challenges through acquisition and innovation. With decades of experience leading AI-driven growth strategies for Fortune 500s, private equity, and high-growth startups, Sean has built products used by billions, attracted acquisition interest from Apple and Box, and driven explosive business growth.