AI is now on both sides of the hiring table: 4 things to change in how you hire tech talent

Juan Molina ·

Candidates now arrive with AI-written résumés, and soon AI twins. Here is what that changes for companies hiring engineers and tech leaders.

Before you meet your next engineer, their AI may already have talked to yours.

That isn't a forecast for 2030. This week, Eightfold AI CEO Ashutosh Garg described TwinCafe, a platform that builds a digital "twin" of a job seeker from their résumé, LinkedIn profile and work samples (Fortune, October 12, 2026). A recruiter can question the twin about past roles, skills and gaps before the first live conversation. Garg's argument is simple: if a machine can handle the fact-checking, why limit a first screen to a handful of people? "Why not interview everyone?" he asks.

Whether or not twins catch on, the direction is clear. AI now sits on both sides of the hiring table. Candidates use it to write, apply and prepare, and employers use it to screen. That changes what a hiring process can trust, and what it should spend human time on.

Here are four practical changes for any company hiring engineers, product people or tech leaders.

1. Decide what the live interview is for

Garg notes that recruiters often spend the first 20 minutes of an interview verifying résumé details (Fortune). If that work moves to software, the live hour becomes the most valuable part of the process, and the only part that tests what software can't.

Use it for what only people can judge:

  • How the candidate thinks under real constraints. Walk through a real problem from your roadmap, not a puzzle.
  • How they work with others. Disagreement, trade-offs, explaining a decision to a non-technical stakeholder.
  • What they would do in their first 90 days. This is where seniority shows.

Write down, before the interview, the two or three things the live conversation must answer. Everything else can be checked another way.

2. Treat the résumé as a starting point, not as evidence

A well-written résumé tells you less than it used to. In a survey of 2,000 US adults run by résumé platform Novoresume in May 2026, 42.6% said they used AI the last time they updated their résumé (TecHR Series, October 12, 2026). Among those who let AI write most or all of it, 74.8% admitted something on it was inaccurate, compared with 24.6% of people who used no AI. (This is the company's own research, published with a product launch, so read it as a signal rather than a census.)

Using AI to write is no proof of dishonesty. Most candidates use it the way they use a spell-checker. But polish is no longer a signal, so verification has to come from somewhere else:

  • Ask for work samples: a repository, a design document or a short write-up of a past decision.
  • Probe one or two claims in depth. "You reduced latency by 40%. Walk me through how you measured it."
  • Check references with specific questions rather than general ones.

Good candidates welcome this. It gives them a fair way to show what they did.

3. Make it easy for candidates to know you're real

AI helps scammers as much as it helps recruiters. Business Insider recently published the account of a data analytics professional who was nearly caught by a fake job offer (Business Insider, October 11, 2026). The scammer used a real recruiter's name, photo and LinkedIn profile, offered a role tailored to his experience, and wrote without a single typo. The usual red flags simply weren't there. What gave it away was a push toward a paid "career consultant" instead of the company's own careers site.

When someone impersonates a company, the candidate loses, and so does the company's reputation with the people it most wants to hire. A few simple steps help:

  • List every open role on your own careers page, so candidates can confirm an offer is real.
  • Say publicly which email domain your recruiters use, and that you never charge candidates anything.
  • Answer verification emails quickly. A candidate who writes to check is doing you a favor.

4. Spend human attention where AI can't help

If screening gets cheaper, the bottleneck moves. It's no longer finding people to talk to. It's the quality of the conversations you have and how quickly you decide.

For tech roles, that means three things:

  • Senior people on your side should be in the room earlier. A strong engineer or leader reads a candidate's judgment faster than any screen.
  • Feedback within days, not weeks. The best candidates usually have more than one process going.
  • A clear "why us" for the role: the problem, the team, and what success looks like in a year. AI can write a job description. It can't tell a candidate why this team is worth joining.

The short version

AI is changing hiring on both sides at once. Candidates arrive with AI-written documents and, soon, AI stand-ins. Employers screen with AI too. Neither side is going back.

So the companies that hire well will:

  • use automation for what it does well;
  • protect candidates from people pretending to be them;
  • put their best human attention on the few conversations that decide a hire.

If you're hiring engineers or tech leaders and want to talk through how your process holds up, you can book a 15-minute call.

Not ready for a call yet? You can post your open role for free.