In this exclusive Q&A, we had the privilege of speaking with an AI Innovator, Greg Sabo, whose career spans time at Stripe and Asana. Greg now leads the Engineering department at Fieldguide, which offers AI solutions that help advisory and audit firms grow. With insights into cutting-edge technologies like large language models (LLMs), practical advice for overcoming AI adoption challenges, and a visionary take on how tools like GoSearch are revolutionizing the workplace, this conversation is a masterclass in understanding the present and future of AI.

This interview dives into six key questions shaping the AI landscape today—covering groundbreaking advancements, ethical considerations, and the evolving skill sets engineers need to stay competitive. Whether you’re a tech enthusiast, a business leader, or someone navigating the digital workplace, these insights provide a roadmap to leveraging AI for meaningful impact.

Here’s what Greg Sabo had to say:

Q&A with Greg Sabo

AI Advancements & Integrations

Question: What are the most exciting AI advancements you foresee impacting our industry in the next few years?

Greg Sabo: Lately, there’s a lot of buzz about LLM models that use test-time computing to break through the intelligence plateaus we began to see after the release of GPT4-class models. 

This technique is where the LLM thinks to itself for longer before answering a query. This might lead to a future where we can access models better than most humans at most tasks.

 This has huge implications for science and research but opens up possibilities for LLMs to assist in more complex strategic advisory work, such as coaching executives.

Question: How do you envision integrating AI into your current technology stack to enhance product offerings?

Greg Sabo: We’ve already seen great success using LLMs to summarize content, and retrieval-augmented generation continues to improve, often surfacing as “AI Chat” features. 

To reach the next wave of user adoption, we need to build features that use hard-coded prompts to provide specific, tested, and reliable values rather than relying on users to write questions or prompts effectively themselves.

“AI is going to completely transform what knowledge work feels like and how it is done. Things like meetings, hiring, performance evaluation, and the overall nature of office work will look quite different, even though the core human elements will still be present.”

—Greg Sabo, Head of Engineering @ Fieldguide

Overcoming AI Adoption Challenges

Question: What AI adoption challenges do you anticipate, and how can we overcome them?

Greg Sabo: There’s still cultural resistance to using AI for work—for example, using AI to write an email for your boss might feel disingenuous or like you’re “cheating.” Some breakthrough interaction designs might overcome this challenge, i.e., by making attribution easy. 

There’s also a slower-moving but more impactful opportunity for leaders and managers to recognize and encourage the real work that it takes to use AI effectively.

Ethical AI

Question: How do you ensure AI solutions remain ethical and unbiased in their decision-making processes?

Greg Sabo: So much of this relies on the choice of model that you use. I trust the LLMs provided by the “frontier labs” at OpenAI and Anthropic, primarily because of their clear dedication to reducing bias. 

However, increasingly, more “open source” model weights are available, creating difficult choices for vendors since they may come at a much lower cost.

As the number of providers increases, we’ll need to rely on our own testing and benchmarking to ensure that the models don’t have issues with bias. I’d love to see more third-party benchmarks and evaluations targeting this in the industry.

Essential AI Skills & Tools

Question: What skills are essential for our engineering team to develop to stay ahead in AI and technology?

Greg Sabo: I think writing skills are becoming more important for engineers than ever before. An ability to write clearly and directly helps engineers write good LLM prompts and have strong opinions on LLM output. 

As always, the ability to translate vague user requests and desires into technical concepts and specifications remains incredibly important.

Question: What do you think of GoSearch (AI enterprise search and custom AI agents) and other digital workplace solutions? What value do they bring?

Greg Sabo: When appropriately implemented, searching through an agent is a fundamentally better experience than traditional search experiences. Delivering an answer rather than simply a document massively improves employees’ ability to navigate their organization. I also think that a RAG solution focused on commonly accessed documents and resources will often outperform a RAG system that tries to index “everything.”

That’s why I appreciate GoSearch’s approach to security with workplace and personal connectors so that sensitive documents don’t get into the wrong hands.

Closing Thoughts from an AI Innovator

Introducing AI Innovators 

This blog marks the beginning of an exciting new series where we engage in thought-provoking conversations with leading voices in AI, technology, and engineering. In each installment, we’ll dive deep into the innovations, challenges, and opportunities shaping the future of these industries. 

From groundbreaking advancements in AI to the ethical considerations and skills needed to stay ahead, this series is designed to spark meaningful dialogue and inspire forward-thinking ideas. 

As we explore these topics, tools like GoSearch—our AI-powered enterprise search and custom AI agents—stand out as essential solutions for navigating the digital workplace. 

GoSearch transforms how organizations access knowledge and make informed decisions by delivering answers instead of just documents. 

Stay tuned for insights from trailblazers who are redefining what’s possible in the digital age!