Interview with Aaron Kesler, Sr. Product Manager, AI/ML at SnapLogic
Aaron Kesler brings over ten years of experience in product management, focusing on building scalable frameworks that combine design thinking, jobs to be done, and product discovery. At SnapLogic, an AI-powered integration platform, Aaron develops AI-driven products and mentors aspiring product managers on strategy, execution, and customer-centric development.
How Early Entrepreneurial Experience Shaped a Product Mindset
Aaron’s entrepreneurial journey began in college with a startup called STAK, which was eventually acquired by Carvertise. This hands-on experience taught him to engage directly with businesses to understand their problems and craft solutions—a practice he continued even before holding the formal title of product manager.
He explains the shift from engineering to product management as moving from “solving problems with technology” to “finding the right problems worth solving that drive business value.” The resourcefulness required in a self-funded startup instilled a practical approach: solve problems in ways that sustain the business. This foundation remains relevant whether at a startup or a large enterprise.
Advice for Aspiring Product Managers
Aaron emphasizes the importance of arguing from the customer’s perspective. Truly knowing your customer’s needs, pain points, and context turns opinions into insights, making you a go-to person for clarity in product decisions. Without this focus, discussions often default to power dynamics rather than facts.
The AI-Augmented Future of Work
People are already working alongside multiple AI agents tailored to specific tasks. Companies are creating “AI coworkers” for each employee—agents that assist with everything from drafting user stories to coding and customer feedback analysis. These agents don’t replace humans but remove repetitive, low-value tasks, freeing people to focus on higher-level work.
In five years, Aaron expects AI agents to be as integral to teams as tools like Slack or Google Docs are today.
Bridging AI Literacy Between Technical and Non-Technical Teams
Start small with a clear plan that integrates AI into your data and application strategy. Focus on solving mundane but high-value problems tackled daily by frontline employees. Hands-on experience is key, combined with simple explanations of AI concepts and ongoing learning.
Security and governance are critical—define who can access what data and ensure AI tools comply with policies. Treat AI adoption like a course: explain basics, provide controlled practice, then deepen knowledge over time. It’s okay not to know everything; the goal is to build confidence in asking the right questions.
Effective AI Upskilling Strategies
- Give employees hands-on opportunities to use AI tools relevant to their work.
- Encourage experimentation, treating it like sanctioned shadow IT to find creative solutions.
- Provide access to user-friendly AI platforms, such as SnapLogic’s AgentCreator, to build agents without coding.
- Collect feedback and questions from users to tailor ongoing training.
Risks of AI Adoption Without Proper Upskilling
Major risks include governance and data security violations, which can lead to regulatory penalties and data exposure. Many companies also overestimate AI capabilities or push adoption top-down without engaging end users.
Successful AI integration requires champions who educate teams, strong data strategies, guardrails, and time for learning. Without these, AI tools often fail to deliver real value.
AI’s Role in SnapLogic’s Product Strategy
AI is central to SnapLogic’s innovation approach, not just as a feature but as a way to simplify integration and automation for all users. The goal is to build products that serve both technical and non-technical teams effectively, using AI to bridge skill gaps.
How AgentCreator Empowers Businesses
AgentCreator allows teams to build enterprise-grade AI agents using natural language prompts—no coding needed. These agents integrate tightly with enterprise data to automate workflows, make decisions, and act in real time.
For example, Independent Bank used AgentCreator to launch voice and chat assistants that reduced IT help desk backlogs, freeing IT to work on new initiatives. Aptia automated benefits elections, cutting hours of manual data entry to minutes.
Democratizing Integration with SnapGPT
SnapGPT, SnapLogic’s AI-powered integration copilot, enables users to build integrations and workflows through simple natural language commands. This opens the door for non-technical employees to build and iterate on integration pipelines, SQL queries, documentation, and data transformations.
This democratization speeds up iteration and innovation by expanding who can build solutions beyond traditional developers.
What Sets SnapLogic’s AI Tools Apart
- First generative integration platform with fast, code-free GenAI app building.
- Purpose-built for cloud, on-premises, and hybrid environments with strong real-time and hybrid support.
- Iterative development with automated validation and schema-on-read accelerates project turnaround.
- Supports a wide range of skill levels, reducing dependency on highly skilled developers.
- Processes over four trillion documents monthly, ensuring high performance and scale.
The Future of Product Management in an AI-Driven World
Aaron is excited by “vibe coding”—building working prototypes in real time using natural language. This could enable product, design, and engineering teams to collaborate live during customer calls, co-creating solutions on the spot.
This approach promises a more collaborative and creative product development process, allowing teams to quickly test ideas and better solve customer problems together.
For product professionals looking to deepen their AI skills and stay ahead, exploring hands-on AI courses can be a practical next step. Resources like Complete AI Training offer structured learning paths tailored to product development roles.
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