Recruiting is always a mirror of its time. The tools we use, the speed of the process, and even the power balance between employers and candidates reflect the technologies available and the cultural expectations of each era.
Let’s look across fifty years, from 1985 and the early days of the semiconductor revolution in California, to 2035, when AI will orchestrate talent systems. We can then see just how much the methods of finding and filling jobs have transformed. This comparison highlights not only the radical pace of technological change, but also how the human dimensions are always key.
1985: The Age of Envelopes and Phone Calls
The Job Seeker
In 1985, a young electrical engineering graduate named Mark Alvarez sat at his parents’ kitchen table in Fremont with the San José Mercury News spread before him. The Sunday classifieds section was thick with “Help Wanted” ads, organized by occupation. With a yellow highlighter, he circled openings that matched his background.
One ad from National Semiconductor, where I was working at the time, caught his eye:
“Design Engineer. Strong foundation in circuit design. Bachelor’s degree in Electrical Engineering required. Send résumé to HR, 2900 Semiconductor Drive, Santa Clara, CA.”
Mark spent his afternoon on an IBM Selectric typewriter formatting his résumé and cover letter. Every error meant stopping to use Whiteout. He printed his résumé on ivory bond paper, folded it into an envelope, and dropped it in the mail.
Two weeks later, the wall-mounted phone rang during dinner. His sister shouted, “Mark! Some company in Santa Clara!” A recruiter from National Semiconductor called to invite him to an interview a few days later.
On that day, Mark drove his Datsun 280 from Fremont down Route 17 and across 237, into Santa Clara. Dressed in his best navy suit, he walked into building 27 for his interview. His interview consisted of a resume review and answering a series of questions for half an hour with the recruiter. This was followed by two engineers asking him to sketch a circuit on a whiteboard and review his classes and grades. They scribbled notes on yellow legal pads and thanked him for coming. The recruiter then showed him around the various buildings where they were designing and manufacturing semiconductors. He was impressed and excited about the possibility of becoming part of this.
Weeks later, he received a phone call from the recruiter with an offer of $27,500 a year plus benefits. A few days later, he received a letter confirming the salary and the start date. When Mark’s father saw the letter and the salary, he whistled. “That much? For drawing little lines?” Mark laughed, knowing those “little lines” were the foundations of the Valley’s future.
The Recruiter
Bob Zimmerman managed recruiting at National Semiconductor. His cubicle was lined with a filing cabinet stuffed with résumés, sorted into manila folders by role. On his desk sat a Rolodex and a push-button phone.
Bob’s week began with a call to the Mercury News classifieds desk to renew ads. Résumés trickled in by mail. Bob and the other recruiters opened envelopes, stamped them with the received date, and logged them in a ledger. Promising résumés were tagged with colored stickers depending on the role and placed into folders.
Scheduling interviews required endless phone calls—no email, no calendars, just telephone tag. He penciled appointments into a large desk calendar, erasing and rewriting as managers shifted their schedules. One of his challenges was coordinating the interview schedules with the hiring managers and the candidates. After the interviews, he had to collect the handwritten feedback sheets, put them into candidate files, and type up offer or rejection letters on company stationery. The work was slow, manual, and administrative. He had an assistant who handled most of the coordination and typing, but he was still left with a significant amount of administrative work.
2035: The Age of AI Agents and Talent Graphs
The Job Seeker
Fifty years later, Maya Chen, a quantum materials engineer freshly graduated from UC Berkeley, never had to scour job ads. She carried a digital talent passport, basically a blockchain-verified record of her skills, coursework, projects, lab simulations, and her degree. Her AI learning assistant continuously updated this living document, with every project and credential instantly validated.
When Orion Semiconductors in Santa Clara set up a new chip line, its AI recruitment agent scanned the global talent graph for the best candidates. Maya’s profile was flagged as a top 2% match worldwide.
Her Apple watch wrist interface buzzed: “Opportunity Match: Quantum Materials Engineer, Orion Semiconductors. 87% alignment. Engage?”
She tapped “Yes.” Instantly, her AI began negotiating with Orion’s AI on compensation, flexibility, and research budget. By the time she sat down for dinner, she had a personalized offer package ready for review. No résumé. No cover letter. No waiting weeks for a phone call.
The Recruiter
At Orion, Alex Rivera no longer considered himself a recruiter. His title was Talent Systems Architect. The AI handled sourcing, matching, and negotiation. His job was to calibrate the system: ensuring the skill ontologies reflected the latest research, auditing decision trails for fairness under the 2032 International AI Employment Accord, and maintaining transparency.
When Maya’s profile surfaced, Alex reviewed the AI’s interpretability dashboard. It explained why she was flagged: her lab simulations in photonic lattice structures, her top percentile problem-solving scores, and her projected learning curve based on previous adaptive learning models.
Alex scheduled a mixed-reality call with Maya—not to test her, but to talk. “The system says you’re a fit,” he told her. “I want to hear what you think.” That was his role: providing the human bridge between data and meaning.
The Hiring Manager
Dr. Elena Torres, Orion’s head of quantum research, no longer sifted through résumés. Instead, her dashboard displayed AI-vetted candidates with dynamic skills maps and predictive learning trajectories. She didn’t wonder if Maya could do the job; the system had already verified her capabilities.
What Elena cared about was subtler: curiosity, ambition, alignment. She used her time to probe whether Maya’s long-term interests matched Orion’s trajectory. The hiring conversation had shifted from “Can you do this?” to “Do you want to do this with us?”
At Home
When Maya told her grandmother about the offer, the older woman shook her head in disbelief. “You didn’t apply? You didn’t send anything?”
Maya smiled. “No, Grandma. My AI handled it.”
Her grandmother laughed. “Back in my day, I spent hours typing my resume and going to interviews.”
The 50-Year Transformation
The comparison between 1985 and 2035 reveals just how far recruiting has come.
Speed: In 1985, the process took weeks or months. In 2035, matches are made in hours or days.
Tools: 1985 relied on newspapers, typewriters, landlines, and filing cabinets. By 2035, blockchain passports, AI agents, and talent graphs are standard.
Power Balance: Employers once controlled information and access. In 2035, candidates wield more agency, with AI advocating on their behalf.
Recruiter Role: Recruiters were once administrators of paper and phone calls. Now they are guardians of fairness, trust, and human alignment.
What has not changed is the human core of recruiting. In both eras, employers and candidates sought the same thing: fit. In 1985, this was tested at whiteboards and in face-to-face interviews. In 2035, it is explored in conversations about values, curiosity, and purpose.
And yet, the essence remains. Recruiting has never just been about matching skills to roles. It has always been about connecting people to opportunity in a way that builds both careers and companies.
The tools have changed. The pace has accelerated. The power balance has shifted. But the human thread—judgment, trust, and meaning—still ties the process together.
40 years ago the role of the recruiter was a lot of coordination, in the past few decades it shifted to "gatekeeping" (oftentimes), and AI will change it to connecting.
Great illustration of how this shift is occurring!