惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

C
Cybersecurity and Infrastructure Security Agency CISA
H
Heimdal Security Blog
Security Latest
Security Latest
Cisco Talos Blog
Cisco Talos Blog
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
S
Securelist
A
Arctic Wolf
C
CXSECURITY Database RSS Feed - CXSecurity.com
cs.CL updates on arXiv.org
cs.CL updates on arXiv.org
T
Threat Research - Cisco Blogs
P
Proofpoint News Feed
K
Kaspersky official blog
C
Cyber Attacks, Cyber Crime and Cyber Security
D
Darknet – Hacking Tools, Hacker News & Cyber Security
T
The Exploit Database - CXSecurity.com
P
Privacy International News Feed
The GitHub Blog
The GitHub Blog
U
Unit 42
Application and Cybersecurity Blog
Application and Cybersecurity Blog
月光博客
月光博客
Scott Helme
Scott Helme
Attack and Defense Labs
Attack and Defense Labs
爱范儿
爱范儿
NISL@THU
NISL@THU
博客园 - 司徒正美
阮一峰的网络日志
阮一峰的网络日志
L
LINUX DO - 热门话题
美团技术团队
C
CERT Recently Published Vulnerability Notes
Y
Y Combinator Blog
P
Proofpoint News Feed
博客园 - 聂微东
雷峰网
雷峰网
Exploit-DB.com RSS Feed
Exploit-DB.com RSS Feed
博客园 - 【当耐特】
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
PCI Perspectives
PCI Perspectives
H
Help Net Security
TaoSecurity Blog
TaoSecurity Blog
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
Jina AI
Jina AI
宝玉的分享
宝玉的分享
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
MongoDB | Blog
MongoDB | Blog
Google DeepMind News
Google DeepMind News
F
Full Disclosure
Hugging Face - Blog
Hugging Face - Blog
Hacker News: Ask HN
Hacker News: Ask HN
大猫的无限游戏
大猫的无限游戏
Blog — PlanetScale
Blog — PlanetScale

IEEE Spectrum

How AI Attribution Could Finally Pay Musicians for Training Data How Liquid Cooling Let a Humanoid Robot Shatter Half Marathon Records Inside GM’s AI Push to Speed Up the Design of Cars and Moon Rovers Smart EV Charger Learns Your Battery’s Age to Let It Live Longer Phoenix Links IoT Chips to Save High‑Value Legacy Systems Phoenix Links IoT Chips to Save High‑Value Legacy Systems Tensordyne's Wild Log Math Aims to Leave Nvidia’s AI Chips In the Dust The Tiny Turbine That Kick-Started the U.S. Wind Industry Satellites Are Tracing Railroad Tracks Across SPHEREx’s Cosmic Map Are Emotion Reading Robots Still Missing What Matters Most? Watch This Humanoid Robot Move in Ways Your Hips Wouldn't Like The Real Cost Of Cooling GPUs In Space Might Shock You The Google DeepMind Spinoff Chasing Hidden Drug Targets We Are Crowd-Sourcing the Panopticon Gene Therapy and Sound Waves Team up to Steady Failing Hearts Save 14 Percent of Energy Used in LLM Training With This Trick The Real Tradeoffs Between Startups, Mid-Size Firms, and Giants When Does Job Hopping Stop Helping Your Engineering Future Why a Computer Science Degree Still Opens Hidden Doors AI Can Help Track the World’s Shrinking Glaciers Curiosity’s 13 Years of Software Hacks Keeps It Alive on Mars Fractal OS Lets Security Researchers See What Their CPUs Really Do Formula E DNA Helps the Cayenne Electric Bend Physics to Beat the Heat Moon’s Dark Craters Could Become the Most Precise Clocks in Space New Radio Giant in New Mexico Takes Its First Glimpse of the Cosmos Nvidia’s AI Hardware Comes to Windows in RTX Spark PCs Can Humanoid Robots Run Stairs Without Tripping? Do They Need Shoes? Inside the Compact Fusion Reactor Aiming to Power 280,000 Homes NSF X Labs Power Agile, High-Stakes Experiments "Hemopurifier" Could Help Fight Bundibugyo Ebola Strain Why Quantum Computers Need a ‘Healthy Chunk’ Of Classical Power
Beat Biased Hiring By Owning Your Story In Every Interview Room
https://www.facebook.com/48576411181 · 2026-06-18 · via IEEE Spectrum

This article is crossposted from IEEE Spectrum’s careers newsletter. Sign up now to get insider tips, expert advice, and practical strategies, written in partnership with tech career development company Parsity and delivered to your inbox for free!

I’ve sat on both sides of the interview table several times over the past decade. You might be surprised to hear that I’ve often been just as nervous interviewing candidates as I was when being interviewed!

Nearly all the interview advice out there is about the candidate’s side, but understanding the other side can also help you prepare. Let me show you what I’ve seen firsthand, and what I’d bet is happening at the company you just interviewed with.

If you recently got rejected after an interview, this might explain what actually happened.

One caveat, because I’ve been on the receiving end of this: A couple of my recent interviews were run entirely by AI. These were screening rounds, but a growing share of job seekers now report being interviewed by a bot somewhere in the process. Everything below assumes you reached a person.

Most teams have no standard prep

You might assume companies train people to run interviews. Many don’t.

In practice, your interviewers may be much less prepared than it seems. Their prep might look like this: “Here’s a rubric from three years ago, figure it out.” Or: “Let’s grab a conference room between meetings and decide what to ask.”

The questions are often whatever the interviewer personally studied when they were job hunting. These days, they may be generated with an LLM the morning of.

Then the panel negotiates. One person wants to quiz candidates on data structures and algorithms for a role in which they design websites. Another insists system design is essential for a junior level position. People default to what was done to them and assume it’s normal because it was normal to them.

What’s normal to the spider is chaos to the fly.

“Scoring” that isn’t really scoring

After an interview, some processes I was part of had one simple scale to score candidates: yes, no, strong yes, strong no.

The result is predictable. Like the candidate? Strong yes. They rubbed you the wrong way but answered everything correctly? Somehow a soft yes at best.

Structured scoring with defined criteria measurably reduces this. The research backs it, and the rare times I saw it used well, it changed my own assessments. Yet many teams I worked on never used this approach.

Prestige bias and politics

Even with a strong scoring system, bias and office politics can change the outcome.

For instance, I once interviewed someone I was strongly against hiring. It was clear they didn’t know what they were doing, and they’d be running critical infrastructure. I gave a strong no with objective reasons, scoring notes, specific examples from the technical round.

Leadership pulled me into a meeting right after and asked why. I walked them through my notes.

What I didn’t know: Several of them already knew the candidate personally. They liked them. They wanted them hired. I said the decision was theirs, my assessment hadn’t changed, and wished them luck.

I’ve also watched a strong resume short-circuit an entire loop. The team saw a top-tier company name, skipped the standard technical rounds, lobbed a few softballs, and basically welcomed the candidate in.

But once this engineer got started, it turned out to be a poor fit. And it wasn’t the candidate’s fault. They were set up for failure, because nobody checked whether this person could do this job at this company.

In both cases, it didn’t work out.

What you can actually control

You could read all this and decide the system is broken or rigged.

The broken part is fair. The rigged part isn’t. People who are genuinely good at interviewing pass more often. It’s messy, but it’s not a lottery.

You can’t fight bias, politics, or a sloppy process. That’s like being mad at the weather. You can only play the two cards you’re dealt: your technical ability and your behavioral presence.

Most candidates obsess over the technical side and forget the behavioral rounds exist. But product managers, designers, and cross-functional leads—people with zero technical background—will judge you entirely on whether you can tell a clear story and seem like someone worth working with. If you’re unlikeable in the room, you’ve roughly halved your odds at every stage.

So here’s the unglamorous advice that actually works: put yourself on camera.

Talk through a project you led, a mistake you made, a hard problem you solved. Record it. Watch it back. Cringe. Do it again.

Think out loud, under pressure, with another human watching.

If you keep failing interviews, the fix isn’t always more technical prep. It’s getting better at being in a room with other people who are potentially more nervous, less prepared, and more biased than you ever imagined.

The process is broken. You can still win.

—Brian

NSF Experiments With New Kind of Science Funding

A new initiative from the U.S. National Science Foundation plans to distribute $1.5 billion of funding over 10 years to independent research organizations, which it calls “X-Labs.” The program is meant to support work being done outside of academic institutions, starting with two areas: scientific instruments for sensing and imaging, and interconnects and integrated photonics for quantum systems.

Read more here.

7 Ways New Engineers Can Flourish in the Age of AI

We’ve said it before, and we’ll say it again: AI is changing the engineering profession. So how can you stay in demand as the field’s tools evolve? A senior engineering manager at Walmart Global Tech offers seven quick tips.

Read more here.

Collection: Career Advice for Engineers, From Engineers

For even more expert tips, check out the new career advice collection from The Institute. These articles feature guidance written by working engineers, meant to help those in all stages of their careers stay at the forefront of their profession. Discover tips for technical presentations, dive into a specific career path like cybersecurity consulting, and more.

Read more here.