Cisco just announced plans to slash thousands of jobs as part of a new round of “strategic investments” in its workforce, an investment path that could help what Chief Product Officer Jeetu Patel recently told SDxCentral was one of the vendor’s biggest challenges.

Patel told SDxCentral during an exclusive interview at Cisco’s headquarters that beyond “more time,” what he wished for most was “more talent.”

“We're always short on really highly capable technical talent,” Patel said. “We need more talent in silicon. We need more talent in cyber. We need more talent in networking.”

This “technical talent” need seems paramount when tied to Patel’s expectation that approximately 70% of the networking giant’s product portfolio will be fully AI generated by the end of next year, a plan that will include humans as being a key cog in that push.

Patel noted that this “AI-first standpoint” has already begun. That spark was Cisco’s AI Defense product, which the vendor unveiled in early 2025, and that Patel said “has been built 100% with AI. No human lines of code.”

Cisco’s next goal is “we will by the end of the year probably have a half-a-dozen products, and by the end of next year, my thinking is we'll have about 70% of our entire portfolio at Cisco by the end of the calendar year ’27, they'll be fully built with AI, no human lines of code,” Patel said.

This push is backed by 85% of Cisco engineers already using AI “on a regular” basis, highlighting what Patel said was a “massive proliferation of AI across the entire stack.”

How does AI help?

Cisco CEO Chuck Robbins hinted at this AI-related talent need when announcing the recent round of job cuts.

“The companies that will win in the AI era will be those with focus, urgency, and the discipline to continuously shift investment toward the areas where demand and long-term value creation are strongest,” Robbins wrote in a blog post on the moves. “I’m confident Cisco will be one of those winners. This means making hard decisions – about where we invest, how we’re organized, and how our cost structure reflects the opportunity in front of us.”

Robbins added that those investment areas would be focused in silicon, optics, security, and in employees increasing their use of AI.

“These investments are building from a position of strength – and focusing on the technologies and businesses that will accelerate our growth, deliver unmatched innovation to customers and partners, and define our future,” Robbins explained.

Patel, for his part, did note that this AI-fueled product push will require a complete re-think of how Cisco’s products are currently assembled and how code is managed, but did provide a bit of light for humans, adding that “the human having ownership of an AI app, that’s an app that’s built with AI coding, is super important.”

“You have to prepare for a world where humans will not know the code that's being written because you will not be able to review all the code that's being written by AI,” Patel said. “So what you have to do is you have to actually make sure that you automate the test beds and harnesses for measuring the outputs of the code.”

This will be required as that code “within the next year becomes a black box,” Patel explained. “When I say black box, I mean if you want to change code, you’re just going to go to AI and say, ‘go ahead and change this piece of code to have this outcome.’ It will go refactor in the way that needs to be refactored.”

However, this model will require the requester to be “very good at saying ‘now, I’m going to measure the outcomes in a way that there’s no regression,’ and that I think is the way this will go,” Patel added. “Your automation will get to be much more effective on the outputs.”

Patel noted that this does lead back to having the right model structure in place as “you have to create a synthetic environment where the outputs can be managed, can be measured for the sanctity of the output much more so than actually evaluating every line of code. That’s a big shift in a way of thinking.”

And also having a human minder nearby as “you also need to make sure that whoever is evaluating the outputs is the one that's responsible for the code, even though they don't know the code,” Patel said. “Every piece of code needs to have a provenance of a human, where you can track it back to a human.”