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

Recent Commits to openclaw:main
Recent Commits to openclaw:main
L
LangChain Blog
月光博客
月光博客
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
博客园 - 【当耐特】
宝玉的分享
宝玉的分享
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
Last Week in AI
Last Week in AI
人人都是产品经理
人人都是产品经理
博客园_首页
T
Tailwind CSS Blog
P
Proofpoint News Feed
雷峰网
雷峰网
D
Darknet – Hacking Tools, Hacker News & Cyber Security
IT之家
IT之家
V
Vulnerabilities – Threatpost
阮一峰的网络日志
阮一峰的网络日志
C
CERT Recently Published Vulnerability Notes
Attack and Defense Labs
Attack and Defense Labs
S
Schneier on Security
Security Archives - TechRepublic
Security Archives - TechRepublic
L
Lohrmann on Cybersecurity
V
Visual Studio Blog
云风的 BLOG
云风的 BLOG
WordPress大学
WordPress大学
The Register - Security
The Register - Security
N
Netflix TechBlog - Medium
Hugging Face - Blog
Hugging Face - Blog
Project Zero
Project Zero
博客园 - 叶小钗
F
Full Disclosure
大猫的无限游戏
大猫的无限游戏
Latest news
Latest news
S
SegmentFault 最新的问题
C
Cyber Attacks, Cyber Crime and Cyber Security
Google Online Security Blog
Google Online Security Blog
Recorded Future
Recorded Future
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
Hacker News - Newest:
Hacker News - Newest: "LLM"
腾讯CDC
L
LINUX DO - 最新话题
Google DeepMind News
Google DeepMind News
P
Privacy International News Feed
I
InfoQ
F
Fortinet All Blogs
Vercel News
Vercel News
H
Hackread – Cybersecurity News, Data Breaches, AI and More
T
Threatpost
T
Tenable Blog
B
Blog RSS Feed

Stack Overflow Blog

Building more than just an agent harness What's left for infrastructure-as-code after AI moves in? Agent orchestration is so two-years ago When the sensor starts thinking: SnortML, agentic AI, and the evolving architecture of intrusion detection The good, the bad, and the AI apps How do you turn AI coding chaos into a repeatable playbook? Why intent prediction needs more than an LLM Paging Charity! How can engineering leaders avoid becoming Bond villains? Code isn’t the only thing causing your production failures Your AI shipped a backend that boots. That is the whole problem. The 2026 Developer Survey is now open (for human developers only)! Oh the places you’ll go with spatial data Dispatches from O'Reilly: From capabilities to responsibilities You don’t understand DNS like you think you do The new bottleneck - Stack Overflow AI agents are a confused deputy with the keys to your kingdom If context is king, architecture is the castle Selenium vs Cypress vs Playwright: Choosing Your Test Automation Framework Designing CherryScript: Optimizing Data-Driven Workflows via Custom Python-Based Interpreters Paging Charity? How do I get my leaders to stop running teams Into the ground? Developers are emotionally attached to their tools When the cost of code approaches zero, what does engineering leadership look like? Announcing Stack Overflow for Agents Creating checkpoints by gaslighting a Postgres database What can 500 years of journalism teach developers about AI trustworthiness? Making the OWASP top ten in the vibe code era What it takes to be a player in the international AI game Best of the Heap: First post of the past The find out stage of AI is just supply chain and password protection In an AI world, the most valuable developers will be both artisans and builders Agents on a leash: Agentic AI remains mostly single-agent and monitored at work Do you have what it takes to run AI in production? Dispatches from O'Reilly: The accidental orchestrator Breaking your AI storage bottlenecks Coding agents are giving everyone decision fatigue Pack your agentic stack in Slack Your fridge could be a threat to national security “You can't vibe code scale”: What the AI hype gets wrong about software engineering No Dumb Questions: What is cloud computing and why is everyone doing it? Observability and human intuition in an AI world
Interviews aren’t about you (sorry)
Greg Hatchuk · 2026-05-19 · via Stack Overflow Blog

Early in my career, I thought interviews were about me. My skills. My achievements. My victories.

Then I sat on the other side of the table. And everything flipped.

Sitting on the decision side, I started seeing patterns — tiny details that made or broke the deal. More importantly, I saw what interviewers were actually looking for — very different from what I assumed when I was the one sweating in the chair.

After doing this a hundred times, I could spot strong candidates quickly. The good ones had their hacks. They demonstrated specific results — and who recognized them for them. They kept the interview flowing: question, concise answer, next question. I didn’t have to wrestle for time.

But most importantly, the winners understood what the interview was really about.

It wasn’t about the résumé. It was about the hiring manager’s problem.

Most candidates show up ready to impress and treat interviews like a stage. They list accomplishments. They describe how great they are to work with. And sure, that’s nice.

But behind the table, as the hiring manager, I’m rarely thinking, “Wow.” More likely, I’m wondering:

“Can this person solve my problem?”

Because every open role is a symptom. No team hires because everything is perfect.

So what kinds of problems are hiring managers trying to solve?

It could be anything — but you won’t find it in the job ad. Job ads rarely capture the specific internal pressure driving the hire.

They don’t tell you that:

  • The only engineer who understands the payment system just quit.
  • Production incidents are happening often enough that everyone sleeps lightly.
  • The team’s code is solid, but the user experience is suffering.

And as a candidate, you need to know that. Because without understanding the problem, it’s impossible to position yourself as the solution.

So instead of performing and impressing, demonstrate curiosity — be a detective.

Early in the conversation, ask things like:

  • “What prompted the opening for this role?”
  • “What’s been hard for the team lately?”
  • “What problem are you hoping this role solves?”

Those questions surface the real issue.

And once the pain is on the table, the interview changes shape.

Because now, instead of giving a prepackaged speech, you can say:

“In my last role, we faced something similar…”

Instead of random autobiography — relevance.

Once you identify the problem, connect your experience directly to it. Specifically. With examples.

If the team is struggling with coordination, talk about glue work. If they’re scaling fast, talk about trade-offs you made under pressure. If they’re rebuilding trust, show that you understand people — not just systems.

That’s empathy. Not the buzzword. The mindset.

You ask.

After the pleasantries, politely inquire whether there’s a specific problem they’re trying to solve with this hire. Nine times out of ten, they’ll tell you. And if they won’t, it will leak out in offhand comments about deadlines, team dynamics, or recent departures: “We’ve had some coordination challenges…”

Sometimes — and this sounds strange — they may not even fully realize what the problem is. That’s where you come in. With thoughtful follow-up questions, you can help clarify it.

That’s how you set yourself apart.

When I first started interviewing people, I thought I was evaluating talent. What I was actually doing was looking for a solution.

And as a candidate, if you understand that — and respond to what the interview is really about — you stand out.

Not because you’re performing better. Because you’re solving something.

So stop making it about you. Figure out their problem. Then demonstrate you’re the solution.

That’s often when interviews turn into offers.

These articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International license.

creativecommons.org/licenses/by-sa/4.0/deed.en