Searching for Software, Hardware, and AI Skills, a Chip Designer Turns to AI for Hiring

Building a Hiring System Around Customer Needs

One pesky issue Cognichip had, quite familiar to most other hiring organizations, was volume without signal, or, you could say, quantity with unclear quality. “We posted a job and got more than 200 resumes in a short span of time,” Daneshpanah says. “Bots were applying, and it was very hard to filter the signal from the noise. Posting a job was almost useless.”

Cognichip initially engaged Octopyd through its white-glove service, which functioned similarly to a search firm. “We tried a job or two,” Daneshpanah says. At the time, Octopyd was building out its end-to-end hiring system. Cognichip was building its own interim processes: manual worksheets, spreadsheets, and structured templates to track candidate journeys.

Over time, the build-it-in-house mindset at Cognichip began to change. Octopyd adapted to the company’s needs. The technology it built was based heavily on feedback from Daneshpanah and other fast-growing firms. “Octopyd worked with us to transform our processes and incorporate what we needed,” Daneshpanah says. “It made a production-worthy version of the processes and tools we developed internally in 2025, and it’s gotten better and better over time.”

The platform gradually expanded to cover the full recruiting lifecycle, including evaluation, outreach, scheduling, and analytics. What began for Cognichip as a white-glove service was now an end-to-end hiring platform.

From Volume Hiring to Precision Hiring

A key shift was in how candidates were sourced and evaluated. Instead of overwhelming hiring teams with huge applicant pools, Octopyd filtered and ranked candidates based on defined criteria.

The scoring model differs from how a lot of other tools have been built. Many technologies score candidates with something like 1, 2, 3, 4, or 5 stars. Or, they use very general language like “good match” and “very close match.” With Octopyd, scoring works differently. Rather than just a single composite score, Octopyd provides granular breakdowns across dimensions such as startup experience, language stack, AI/ML experience, or leadership vectors, depending on the talents necessary for a given job.

This level of granularity proved more useful to Daneshpanah than a single aggregate rating. He has, in fact, seen candidates with modest overall scores that stand out in critical areas.

Meanwhile, the number of bots applying has dramatically diminished. “Octopyd is only sending people who are a real human being, and meet our criteria. So if they needed to be working onsite for four days in the office, only those people, real people, were sent to us.”

The earlier flood of irrelevant or automated applications began to diminish.

Diagnosing the Hiring Funnel

As Cognichip’s hiring scaled, visibility into the recruiting pipeline became as important as the hiring workflow and the filling of jobs. Octopyd introduced analytics that allowed the team to assess pipeline health and recruiter performance.

“It started telling us how deep our pipeline is,” Daneshpanah says. “At which stage are people getting dropped the most? How is the performance of our external recruiters?”

This led to concrete decisions. “We identified which external recruiters were doing well, and which were not doing well, just adding noise and none of their candidates were being hired,” Daneshpanah says. “We went back to them and said we didn’t want to use them anymore.”

Rather than relying on intuition, Cognichip could quantify where breakdowns were occurring and adjust accordingly.

Stress-Testing Hiring AI Against Human Judgment

On an airplane flight, Daneshpanah tested Octopyd’s recommendations against his own manual screening. He took a look at a list of 300 resumes and selected 15 for a shortlist. He then compared that list to Octopyd’s shortlist of its 15 favorites to see if Octopyd was picking people he would have chosen.

He found that 13 of the 15 manually selected candidates appeared in Octopyd’s top 30. The system also surfaced three strong candidates that Daneshpanah missed.

He realized that the value of AI in recruiting is not just potential efficiency, time, and cost savings, but also the additional insight into potentially great employees humans could overlook.

A Different Kind of Talent-Technology Vendor Relationship

At the outset, Cognichip had evaluated LinkedIn Recruiter. It had some useful functionality for storing information, but the pace of iteration—and the challenge of legacy systems trying to become more complete AI operating systems—became a deciding factor.

“I would prefer a system like this to one where a feature we need comes after six months,” he says. “I would rather work with a partner who can add a feature we are interested in a month.”

That responsiveness shaped the broader relationship. “It’s tech forward,” Daneshpanah says. “They listen to the customers. The hiring system isn’t something some marketing person thought about. It’s a platform immediately built based on the needs of its users.”

From Founder-Led Hiring to Operational System

Today, Octopyd functions as Cognichip’s central hiring platform. “Every hire we do goes through Octopyd,” Daneshpanah says. “we don’t have another ATS.” What began as a white-glove service has evolved into a system supporting the full journey from approval to offer.

Daneshpanah himself has shifted roles. In the early days, he acted as both hiring manager and almost a de facto recruiting lead. Now, with a head of HR in place, he describes his role differently: “I consider myself a user and an advisor on the company’s recruiting infrastructure.”

Despite all the technology, the core hiring challenge remains for Cognichip. AI isn’t a silver bullet that solves all its problems. Cognichip continues to seek hard-to-find interdisciplinary candidates who combine expertise across AI, software engineering, and hardware, which represent an inherently narrow and competitive pool. Daneshpanah likes to find people strong in at least two of these three areas. “And that type of talent is hard to come by,” Daneshpanah says.

With that in mind, Cognichip is not replacing human judgment with Octopyd’s AI, but is using Octopyd to surface candidates it could have missed, get insights to improve its recruiting, and streamline its hiring workflow to bring chip designers on faster.