Join us in this insightful episode of The Workgrid Podcast where we sit down with Linnae Selinga, Senior Product Manager at Workgrid Software.
Linnae unravels the complexities and exhilaration that come with steering the product management helm in a tech-forward landscape. She delves into the intricacies of managing a diverse array of stakeholders and the art of integrating cutting-edge features, such as Artificial Intelligence, Guided Attention, and low-code/no-code functionality into Workgrid's offerings
What You’ll Learn:
The pivotal role of product management in tech companies and its impact on product success. The balancing act between immediate feature releases and long-term product vision.
A day in the life of a product manager: key responsibilities and challenges; and why product managers need to fall in love with the pain and challenges of their customers. Strategies for effectively managing multiple stakeholders in a product development environment.
Insights into the incorporation of novel AI features. Such as conversational AI, NLP, and proactive engagement into product offerings. The concept of "guided attention" and how it helps curate critical content and actions for users.
The advantages of Workgrid's AI Work Assistant over traditional chatbots. How AI can proactively anticipate employee needs and streamline workplace efficiency.
Tell us about yourself
I’ve been working with Workgrid for about 5 years in product management. I started with a single team focused on natural language chatbot, well before the commodification of large language models (LLM), and task management and workflows. Over the years I’ve grown my knowledge on the digital workplace and the product management practices, and started supporting other product managers. Now, I have my paws across all things across product in Workgrid. There isn’t really one specific path into product management. It’s still a relatively new discipline, but the path that I took was through marketing and communications.
Prior to Workgrid I was working in internal communications which was an amazing primer to understanding the digital workplace and the needs of its people. Before that I was a senior marketing manager for a skills-based college that works with businesses who partner with the college to upskill their staff and promote from within. Prior to that it was all B2B marketing and content creation for a globally renowned advertising agency. All these pieces of my career gave me different lenses to put on when I look at different aspects of product management. It’s all really contributed to my current career.
Our primary audience tends to be application owners and digital workplace leaders. I think what could be helpful is really understanding the role of product management for those outside of the SaaS sales side. What is the typical day in the life and how do you balance those short-term gains of feature functionality to long-term vision?
Like many knowledge workers, a day in the life is always different. If we were looking more broadly at the week, each week I’m working closely with the engineering team, checking in on the roadmap, progress, and what they are working on – features, functionality, and maintenance to make our platform great. We are discussing with engineering leads and UX leads on the purpose and scope and experience of upcoming bodies of work that we have and getting ready for that next batch they are working toward.
I also sit with customers and prospects each week to learn about their digital workplace obstacles, their needs, and their feedback on our product so we can work that into the roadmap as necessary, or as is beneficial. I will typically also be reviewing incoming feedback that comes through other indirect channels.
Last but not least I am rolling up my sleeves on a weekly basis to do a little bit of trouble shooting, which is a great way to get to know our product better, understand how people are using the product, and identify some obstacles we might be able to remove to make things easier and provide a little more value.
Regarding short-term versus long-term gains, I’ve got this interest in human behavior, particularly habit formation. There is this great book called Atomic Habits by James Clear, have you heard of it?
I have but I haven’t read it.
It’s a great read, highly recommend. One of his many mantras that has stuck with me is “every action you take is a vote for the person you will become.” I think about product in the same way. Every feature, every capability, every fix, and every tweak that we make is another vote for what our product will be in the future. So, I always keep that in mind when we are making short-term gains. It always needs to be a vote for what we want to be when we grow up. That’s how we focus on making lots of small and rapid improvements, whether they are customer initiated or internally initiated, everything we do needs to move us toward our end vision.
I like that. It’s an interesting take. Its which wolf are you feeding, or which behaviors are you feeding, which is ultimately going to lead you to your future. That’s a great take. You talked about wearing multiple hats in the process – part referee, part traffic cop, part negotiator – how do you manage those various stakeholders to make sure that you are building to the future and the right product.
Product does have a lot of stakeholders and that’s where conflict arises because there are many of them and they have great ideas all the time. Of course, you have customers and prospects who are using your product, and they want to grow it and evolve it with you. They want to solve their problems with it. Then you’ve got the leadership team, and they’ve got the vision for the product. They of course are always going to have input and direction that’s going to influence the final product outcomes. Then you have the sales team and they’re the ones looking to move the product and sales cycles along. They’re going to have great insight into what it’s going to take to close deals. Then you have customer success, the ones working directly with customers every day, and they know intimately what features are going to help with the overall product experience. Surprisingly, for those who are not in the SaaS world, engineers are also a stakeholder. They have a tremendous amount of pride in the work that they put out and they’re always having great ideas on how to enhance it further, how to make it that much more of a better experience. So, you have all these ideas coming in all the time from all different places and people.
The way in which I try to organize that incoming feedback and resolve potential conflicts in terms of all these great ideas and what do we do with them all is really focus on communication and transparency. Level-setting that this is the roadmap and how it stands today and how it applies to you, our objectives, and our vision. Just being very clear on the decisions we’re making and the decisions we have made or are re-thinking. For example, sharing something like “we were originally going to do X but now we’re going to do Y because ABC” whether it be opportunity feedback or a shift in the marketplace, transparency and communication really solves conflicts of all sorts.
One of the things I wanted to ask you about, particularly with the speed of emergent AI tech and where the world of technology has evolved to over the last year or so, is if you can walk us through lifecycle development and how do you prioritize which features to focus on when AI is moving so fast?
For prioritization there are dozens, maybe hundreds, of project management tools that you can use. But they are just that. They are tools in your toolkit, and you need to have the right context to know which tool to use. I am always thinking about any opportunity in front of us, but especially quick moving technologies and AI, which is always iterating and coming up with some new flashy opportunity that we could take advantage of. I must ask the right questions to figure out what would be appropriate for us. So, asking what is the greatest opportunity in front of us right now? What is the greatest threat? How might this new technology help us accelerate our goals and vision? How can it solve customer pain points? Is this new technology becoming ubiquitous and therefore a table stake for our whole category or market.
As you mention the commoditization of generative AI, that’s the obvious example that’s coming out fast and furious. We’ve been incorporating conversational interfaces into our product since day one, but with the advancements that LLMs are providing, and just wholistically in the digital workplace space, it’s astonishing. We’ve really stepped back and assessed our own intelligence so we can step up our conversational capabilities in a truly delightful way.
One of the things we’ve been doing over the years is working with AI and LLMs. I wanted to ask you, what gets you most excited around the AI Work Assistant and how do you see it changing the work environment for knowledge workers, frontline workers, etc.?
I think the practical answer to that is that it’s going to help with productivity tremendously. The proactively notifying employees when they have something to know or to do, that’s really important and needs to be elevated. It will reduce context switching, provide useful tools, improve productivity, and the value they can deliver to the workplace. A very practical, productivity focused answer, but it really gets me excited every single day.
Where I see real opportunity is that work assistants can provide organizations the power to give every single employee the benefit of their own administrative assistant. Of course, only executives have that today because you can’t have 1:1 human support for every single employee. But when you have a digital work assistant you can have that proactive support for everything you need to know and do. You can have everything on demand and ask for whatever it is that you need instead of having to remember where to find a particular resource or portal. You have someone or something doing that for you.
You can have this value-added support for your core responsibilities – so you have help writing, or coding, or assessing and analyzing information – now everybody can feel like their work and worth to a company is that much more important. To me it’s more than just a productivity tool, it’s an investment in your employees that says, “your time and expertise matters.” That’s what makes me very excited for the future of the work assistant.
I love that response because the organization that’s investing in those products truly understands that their employees are the most valuable assets that they have, and they need to give them the right tools and resources so that they can ultimately do their best work. One aspect that we’ve been certainly moving towards is the ability for the assistant to guide attention for employees. Like you said, not just simply acting when summoned but being proactive in delivering key information when and where it’s needed. Can you speak more to this and how guided attention enhances employee productivity by being right there when they need it most?
We spent a lot of time considering what makes a great executive assistant and brainstormed around that because we wanted to create that type of behavior in a digital assistant. I do want to back up a moment and say, I don’t think a digital assistant is going to replace all our executive assistants, the value that they provide through their relationships especially is irreplaceable. But again, you can’t scale that for every person so that’s why digital is the next best thing.
But thinking about these amazing assistants and what they’ve been providing to their executives… it really is the ability to anticipate. You know what’s coming up and that they need their schedule and the next meeting’s agenda and the conference their going to doesn’t have their dietary preferences. They anticipate and know before you do what it is that you need. That’s what we’re doing with guided attention. We are anticipating what it is you’re going to need and then guiding your attention to it at the right place and time, so you don’t miss a deadline or become a bottleneck if someone is waiting for an approval for example. The guided attention aspect is curating the most important content you need to know when you need to know it and having the capacity to actually pay attention to it.
How do you ensure that guided attention technology doesn’t become intrusive and that those notifications and nudges, the proactive behavior, doesn’t become counterproductive to the employee?
It starts out with measurement. How do we know it’s productive to begin with? I think this is interesting thing to think about because with a lot of SaaS particularly in the consumer space, and increasingly in the B2B space, the goal becomes “how do I keep you in my platform?” and “how do I be the place you want to go?” You see that a ton with social media but you’re seeing it more with different workplace platforms that are trying to be the one. They are measured on a number of interactions or time on platform. But when you are thinking about guided attention you want to go the opposite direction. My goal with guided attention isn’t about capturing attention so much as it’s about how do I effectively get you what you need and get you out so that you can get on with your day. Which is quite the opposite of what you see with SaaS today. I would measure things like the length of time between delivering a notification and the time it takes to act on it.
So to get back to your original question, we need to be able to measure that and focus on that metric to ensure that it’s not being intrusive or counterproductive. It would be counterproductive if we were trying to trap employees and make them spend more time in the digital assistant, but we don’t want to do that. We want to get them out and on with their day so they can provide more value.
That’s a key differentiator because most SaaS applications are looking to justify their existence and prove their value to their customers. I wanted to ask you about the builder functionality, which is our no-code/low-code development platform that can act as an accelerant for AI and machine learning (ML). Tell us more about how this really changes the game for digital workplace leaders to accelerate on their key initiatives where AI and ML may come into play?
This is where I really start to geek out a bit. I mentioned earlier that we’ve been working with conversational intelligence for a while, about four or five years now, and I am painfully familiar with how challenging it is to create and maintain a natural language bot that’s flexible, and valuable, and functional, from day to day. It is hard. That’s why so many chatbots are no more than decision trees. You’ve got your options, usually like three buttons, things like “did I meet your needs,” or “main menu,” that’s what a lot of the chat experience are and what most people think when they hear chatbot. Natural language is very different in that we try to make it much more conversational; you ask a question, and it gives a response. It doesn’t matter how you ask it; we need to be able to interpret it. Historically that was really hard, but the commoditization of large language models, like OpenAI for example is a big one right now, we now have a lot more capabilities and flexibilities to embrace that natural language.
We’ve built that into our AI assistant and now combining it with our no-code builder. Users can leverage our builder and templates, which could also be known as plug-ins or agents, but are those micro experiences that deliver notifications or on-demand experience to you via the assistant. You can plug those in and use them straight out of the box, modify them slightly, or build them from scratch to make your AI assistant whatever you need it to be. Write a couple sentences about what that app or agent is, plug it into the conversational AI model, and it works. You don’t have to do any time-consuming training or regular maintenance. You don’t have to do extensive user testing to see what kind of wild utterances are being thrown out that you haven’t accommodated for and go in to retrain it. It’s not magic but it feels like magic the way in which you can plug these apps into the Assistant’s model and have it actually be able to respond to a user regardless of what type of language they throw at it.
It becomes completely possible to go from having no AI assistant whatsoever to having a full functioning one that’s intelligent, can understand natural language, and do it in like a day. You can do it in a day. That totally blows my mind.
That’s amazing. It’s a game changer if you will. I have thrown so many different things at it and have gotten proper magical responses. I’ve done limericks and Pig Latin and still it gets me to a semblance of an answer that is correct. What advice would you give to aspiring or new product managers who are looking to step into this career path?
Good question. It’s a career path that’s pretty in-demand. I know there are ton of books and resources and classes you can take. I think the big take away would be basically an adage at this point but find something you love about the problem that you’re trying to solve and not your product. You’ve got to fall in love with the customer and their pain and figure out how to solve for that pain and not so much the thing you’re building out. Not only does it give you personal satisfaction, solving the issue that you’re trying to solve, but also so that you don’t become attached to any one particular solution.
For me it goes back to providing every employee with top level support so that they feel valued, and I love that about my job. The reason why you don’t want to become overly attached to the solution is because you’re wrong all the time about what that solution is. I think that’s my second bit of advice. Be okay with being wrong. I think there is some stat, and I’m probably going to get it wrong, but even super high-level product managers, the cream of the crop, only get one of ten product features right. Then you’re back to the drawing board for the other nine. But the goal is to be wrong as early in the process as you can and be comfortable with just being wrong.
I think the last bit of advice is just really invest in building deep relationships with people. Build out your human skills because above all it’s really a people business that we are in. Yes, we build products and things, but we don’t have any control over anything. We don’t actually do the building, we just influence. We influence stakeholders. We influence engineers. We influence customers. We take in feedback, share out our vision. You need to be an excellent communicator and have great relationship skills.
I think those are the three things I would say to anybody aspiring to be a product manager or starting out on their journeys.
I think what we are enabling with searching knowledge bases and more capabilities through integrations, that’s really increasing the value of the AI Assistant and what we can bring to organizations. They can then bring the AI Assistant to employees so that’s all exciting and well and good. But what gets me actually excited is that we are creating a conversational assistant that delights. Like you mentioned earlier throwing limericks and Pig Latin at it and that’s exciting. That gets people to actually want to use this chatbot or to quote our friend Frank, Director of Partnerships “it’s like a chatbot but one you actually want to talk to,” and that is exciting to me. Yes, we are providing value through our integrations and our searches but we can actually engage people in a way that was previously extremely difficult and make people say wow.
Finally, a rapid-fire question. What’s the last best book you read?
For work, I would say Cracking the PM Career by Gayle Laakmann McDowell and Jackie Bavaro. I’ve read a lot of product books since then, but I always go back to that one because it has the most actionable advice that’s easy to read and understand so I would recommend that one over and over again.
