Simplifying the AI Stack | IBM's Dr. Maryam Ashoori
Mar 4, 2025
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Dr. Maryam Ashoori, Senior Director of Product Management for watsonx at IBM, dives into the evolving landscape of AI in enterprise applications. She emphasizes the pressing skill gap among developers and the necessity for improved tools to tackle AI's complexity. The discussion highlights the rise of no-code development as a game-changer, enabling broader access to software development. Ashoori also explores the impactful role of AI agents and the transformation of engineers into strategic roles that balance innovation with management of AI tools.
The evolution of AI necessitates that developers transition from mere task executors to decision-makers managing AI outputs effectively.
A significant skills gap among developers hinders the adoption of AI tools, highlighting the urgent need for strategic learning and implementation.
Deep dives
The Impact of AI on Developer Productivity
AI is fundamentally transforming the developer experience and productivity by shifting the focus from being mere doers to decision-makers. Developers can utilize AI tools such as coding assistants to handle repetitive tasks, enabling them to invest their energy in optimizing applications and strategizing development. For instance, survey results reveal that developers report saving hours daily by using AI for tasks like bug diagnosis and code reviews, which allows for significant efficiency gains. This transition emphasizes the growing necessity for developers to manage AI outputs intelligently rather than just executing tasks.
Challenges in AI Adoption Among Developers
Despite the potential benefits of AI, many developers face challenges related to a lack of skills and understanding necessary for effective AI tool adoption. A recent survey indicated that only about 25% of application developers felt competent in generative AI, highlighting a significant skills gap. This gap creates pressure on developers to adapt quickly by integrating new AI tools into their workflows, yet many lack direction in selecting the appropriate technologies that align with their business goals. Navigating this fast-evolving landscape of AI solutions can be overwhelming, particularly when faced with the barrage of new tools and ongoing changes in technology.
The Shift Towards AI-Driven Decision Making
As developers increasingly work alongside AI systems, there is a shift towards prioritizing decision-making capabilities over mere task execution. This could mean leading a team of AI tools rather than managing human teams, allowing for more flexibility in problem-solving without the social complexities often faced in traditional management roles. By acting as managers of these AI systems, developers can streamline their processes and substantially increase productivity, which could reshape organizational structures in tech companies. The future may see individual developers managing multiple AI agents, potentially leading to a new type of workforce dynamic.
Strategic Approaches to AI Tool Integration
Effective integration of AI tools into existing workflows requires a strategic focus on specific problems rather than merely jumping on technology trends. Developers must clearly define their goals and desired outcomes before adopting AI solutions, ensuring that the tools they choose directly address identified challenges within their processes. This targeted approach allows for better measurement of success and ensures that AI technologies deliver tangible productivity improvements. Organizations that emphasize this strategic mindset will likely navigate the complexities of AI integration more effectively and see a stronger return on their investments in these technologies.
This week, Andrew Zigler sits down with Dr. Maryam Ashoori, Senior Director of Product Management for watsonx at IBM. Together they discuss the evolving AI stack for enterprise and the growing skill gap challenging developers. Dr. Ashoori shares insights from a recent survey of 1,000 developers, highlighting the need for better tools and strategies to manage the growing AI tool sprawl.
The conversation also explores the rise of AI agents, the potential of no-code AI development, and the future of software engineering in an AI-powered world.
But first, co-host Dan Lines (COO of LinearB) sets the stakes for engineering leaders everywhere: the future of technical work will evolve with agentic capabilities. Must we all become “AI managers” now?