Productizing AI: why BigPanda is every engineering leader’s dream
As someone with 20 years of experience managing multinational, multi-location engineering departments, I was looking for an opportunity to hang my hat with an organization invested in strengthening its engineering and research and development (R&D). Spending 11 years at NICE Systems (an enterprise on the more mature side, as far as R&D goes) and seven years at Sisense (when it was in its early stages) left me seeking a company sandwiched in between those two phases of growth. I knew my next chapter should be to help an organization grow globally that wanted to mature its stance and its leadership. And then I found BigPanda.
BigPanda is on the cutting edge of AI and IT, but it is also poised to make AIOps accessible to organizations of any size. Its unique position in the market and its stellar, progress-focused engineering department are just two of many reasons I’m thrilled to join the team.
Why BigPanda?
BigPanda was born in the cloud, which was an essential component of my ideal organization. I have helped companies migrate to the cloud before, and while those were enriching experiences, I knew I wanted to work with a cloud-native, product-centric, SaaS-based company.
I also enjoyed getting to meet the leadership team at BigPanda as I got to know the company. Every executive from our CEO Assaf Resnick to the new Chief Product Officer Fred Koopmans to the Chief People Officer Matt Morgan has done an outstanding job bringing the company to where it is today with the product it has. And of course, the engineering team was truly impressive.
Most importantly, the engineering department—which is already doing incredible work—has an extraordinary opportunity to make a good thing better.
Engineering is ready to shoot for the moon
An engineering department is responsible for delivery of a product, including the technology behind it. This means it is reliable, resilient, scalable, and meets the product management’s definition of customer expectations. It’s also responsible for fixing any problems immediately and developing the product to ensure it consistently delivers value the way the sales people say it should.
BigPanda’s Israel office is full of engineers accomplishing these feats every day. And they’re doing it in a culture rife with enthusiasm, transparency and accountability. This culture can evolve and support the enhancement of product and R&D collaboration, which I believe will further strengthen the offering of BigPanda as a whole.
Productizing AI and implementing incremental value
One of my goals for the engineering team is to become more data-driven in our day-to-day operation so we can make decisions at scale and build reliability metrics. I also want to see how we can deliver more productized AI, meaning making AI-based capabilities more accessible to end users. Expanding our AI capabilities and accessibility will mean that more people within our customer organizations will be able to leverage BigPanda’s AIOps capabilities, reduce manual work and benefit from automation.
One way to achieve this goal is to work on making AIOps a product of gradual value realization where organizations can implement incremental parts of the product and increase the value they get out of it gradually. Moving the product in this usage-based, data-driven direction requires architectural changes and a lot of data to be able to know how customers are consuming the product. Enabling customers to start with a “piece” of BigPanda and helping them realize value in a piecemeal way opens the door for both more companies to leverage AIOps and for BigPanda engineering to refine our product.
Introducing AI-based features in additional areas of the product will also allow us to continue to support and scale our existing customers who are the largest IT organizations in the world.
Solving real problems with real solutions
One of BigPanda’s strengths lies in its proven product. As Gartner’s recent AIOps report tells us, many companies out there purport to offer AIOps, but in fact they only offer AIOps features or related tools. BigPanda actually helps IT organizations address the noise coming in from multiple fronts by providing a solution that delivers significant value and proves ROI.
And as a personal bonus, I find BigPanda’s technology truly interesting. It’s not simple, and it takes a great deal of brainpower to understand its architecture. I enjoy such a challenge.
I’m looking forward to taking these existing strengths of BigPanda’s and helping the team to enhance them. Together, we will help existing and future customers increase their business’ reliability, detect issues faster and reduce operational noise. As we continue to augment our efforts with high-level talent, we’ll be able to drive faster delivery, ensure quality and support scalability—every engineering leader’s dream.
