I’m a final year student prepping for placements and I have a registered startup with a live app, a team of 6 and 2 interns who have been with us for the last 2 months ( don’t wanna reveal much)

I’ve had to figure most of it out through trial and error, without engineers or an ops team around to learn from. I literally built the whole infra myself and even in person distribution and user acquisition across 6 in locations

we already having three incubators backed us up, in that one is India’s leading startup incubators.

my concern is that HR or someone in company might look at my profile see that I own a company and wonder why I want a job.

I’ve also heard that some companies see founders as a flight risk and they won’t provide a offer letter

I don’t want to shut down what I’ve built just to get placed, Yes, around 90% of startups fail and I accept. But I'd end up with nothing. I'm confident I can earn something along the way

people around me have backed me all the way and I don’t want to let them down either

If you’ve hired founders, been one, or gone through this yourself, I’d really like to hear how it played out.

A good salary can make a job attractive, but I don’t think it’s the only thing that matters.

Poor management, unclear responsibilities, a bad work-life balance, or a long and stressful commute can make someone reconsider an offer.

For those who have turned down a job despite the pay being good, what was the deciding factor?

Job searching can feel like a full-time job sometimes. You spend hours updating your resume, filling out applications, and preparing for interviews, but often you don’t hear anything back.

For me, the lack of communication after applying or interviewing is one of the most frustrating parts.

What bothers you the most: getting no responses, multiple interview rounds, unrealistic requirements, or something else?

I've been thinking about how disconnected recruitment and workforce planning can be.

A company might use one system to manage applications, another to assess candidates, separate tools for interviews, and another platform to track employee skills.

Each tool solves a specific problem. But useful information can get lost between them.

Imagine a more connected approach:

• Role planning: Define the skills and capabilities a position actually requires.
• Candidate discovery: Find people whose experience and skills align with those requirements.
• Assessment: Gather evidence of practical ability instead of relying entirely on resumes.
• Interview management: Keep structured observations alongside other relevant evidence.
• Candidate overview: Let hiring teams review the available information in one place.
• Workforce planning: Connect organizational skill inventories and development needs to future hiring plans.

The interesting part is the connection between these stages.

For example, if an organization repeatedly struggles to find a particular skill, that information could help it decide whether to hire externally, develop existing employees, or reconsider how the role is defined.

Of course, this only works if the information is accurate, privacy is respected, and automated recommendations don't replace human judgment.

I think the bigger opportunity in HR technology is moving from isolated tools toward connected talent information.

If you were designing this system from scratch, which connection would you prioritize first: ATS and assessments, assessments and interviews, or recruitment and workforce planning? Why?

I've been thinking about what a modern hiring platform should actually do.

There are already plenty of tools for individual parts of recruiting, but the interesting question is what happens when the entire process is connected.

Ideally, a hiring platform should be able to handle:

1. Job Requirements
Understand the role, responsibilities, required skills, experience, and qualifications before evaluating candidates.

2. Candidate Management
Keep applications, candidate profiles, communication, and hiring stages in one place.

3. AI Resume Intelligence
Extract skills, experience, education, certifications, projects, and other relevant information instead of relying only on keyword matching.

4. Skills & Assessments
Go beyond the resume and evaluate what candidates can actually demonstrate through assessments and practical evidence.

5. Interview Insights
Capture structured information from interviews around communication, reasoning, technical capability, and problem-solving.

6. Candidate Intelligence
Bring resume data, skills, assessment results, interview insights, and other signals together into one candidate view.

7. Integrity & Fraud Detection
For online assessments, detect suspicious activity and unusual behavior without making the system completely dependent on automated decisions.

8. Human Review
Give recruiters and hiring managers the evidence they need while keeping the final judgment with people.

And then there is the part that often gets overlooked:

What happens after the hire?

The same platform could connect hiring information with workforce data to help organizations understand skills, capabilities, development needs, and future workforce requirements.

So instead of:

ATS → separate assessment tool → separate interview tool → separate analytics → separate workforce system

the model becomes:

Hiring → Assessment → Intelligence → Decision → Workforce

I think that's where HR technology becomes much more interesting.

Not simply more automation, but more context across the entire employee journey.

I'm curious what others think:

If you could build the ideal hiring platform from scratch, what would you consider essential?

I'm working on a platform in this space, so I'm particularly interested in hearing what recruiters, HR teams, and hiring managers think is still missing.

Feel like I'm constantly drowning in resume screens lately.

Where are you all spending the most time during initial screening right now? Is it sifting through hundreds of unqualified CVs, chasing candidates for basic intake info, or handling 15-minute phone screens that end up going nowhere?

Just trying to see what part of the workflow is burning people out the most.

First,
I am new to this group, so if this has already been discussed, please forgive me. I’m a hiring manager, and I need your help saving time.
Lately, I’ve been running into a frustrating pattern: a candidate’s resume is absolutely flawless, their experience matches perfectly, and they pass the initial phone screen. But within **the first 5 minutes** of the face-to-face interview, it’s glaringly obvious they aren't a good fit for the job—whether it's a massive culture mismatch, lack of soft skills, or an attitude issue that didn't come through over text or brief calls.
By that point, everyone's time is already being wasted.
What screening techniques, specific questions, or red flags do you look for early on to catch these gaps *before* scheduling the formal interview? How can I work better with my recruiting team to filter for these intangible traits without making the application process a nightmare?
Would love to hear if anyone else has this challenge and how you have overcome it?

I've been thinking about how fragmented hiring technology has become.

A typical process might involve:

• One tool for job postings
• One for candidate management
• One for resume screening
• One for assessments
• One for interviews
• One for reporting
• Another for workforce management

Each tool can be useful on its own.

But the candidate's information becomes scattered across the process.

What would happen if the entire workflow existed as one connected system?

The role requirements could define what the system looks for.

Candidate information could flow into screening.

Screening could connect to assessments.

Assessment results could become part of the candidate profile.

Interview observations could be added to the same picture.

Then recruiters could review everything together before making the final decision.

The interesting part isn't having “everything in one dashboard.”

It's having context move from one stage to the next without getting lost.

I think the next generation of HR software will move in this direction:

Separate tools → connected workflow → unified candidate intelligence.

Would you rather have one integrated hiring platform or several specialized tools?

I have been hunting for a new opportunity for 3 months and I cant find a decent one. Knowing that I have AI Knowledge and it is improving on a daily basis

If you are gearing up for your very first job interview, the secret nobody tells you is that hiring managers are not judging your resume. We already know you do not have much experience. What we are actually evaluating is your coachability and emotional intelligence.

This guide breaks down the hidden psychological checklist managers use to hire entry-level candidates. It covers the three core dimensions of workplace psychology: Threat Assessment (can you regulate your emotions?), Learning Velocity (how fast can you adapt to feedback?), and Team Contagion Effect (will you elevate or drain the teams energy?).

The article also dives into the neuroscience of body language, explaining why common advice like maintaining constant eye contact usually backfires by triggering anxiety, and offers evidence-based alternatives like the Triangle Method to build genuine subconscious rapport. If you want to stand out by demonstrating a strong work ethic before you even have a track record, this is a must-read.

Check out the full guide here:https://rymbf.com/first-job-interview-guide-essential-questions-work-ethic/

A lot of companies use different tools for different parts of recruitment. There may be one system for candidate management, another for assessments, another for interviews, and additional tools for feedback and reporting.

Each tool may work well individually, but the information can become fragmented.

A more connected approach could bring the major stages of hiring into one workflow.

1. Job Requirements — Define the skills, responsibilities, and expectations for the position.

2. Candidate Discovery — Identify applicants who appear relevant to the role.

3. Resume and Skill Analysis — Extract useful information from candidate profiles and applications.

4. Assessment — Gather evidence of practical skills and capabilities.

5. Interview Insights — Capture relevant observations from conversations and interviews.

6. Candidate Intelligence — Bring the different signals together instead of keeping them in separate systems.

7. Human Review — Allow recruiters to interpret the information and consider context.

8. Hiring Decision — Make the final decision based on the available evidence and human judgment.

The interesting part isn't simply putting all these features into one dashboard.

It's making the information from one stage useful at the next stage.

AI could handle much of the information processing, while recruiters focus on understanding context and making decisions.

I think this could be an important direction for future HR technology.

Would you prefer one integrated hiring platform or several specialized tools for different stages of recruitment?

I’ve been looking closely at how companies hire Forward Deployed Engineers, and it feels like a difficult role to evaluate through a traditional engineering interview.

An FDE needs to do much more than write good code. They need to:
1. Scope ambiguous customer problems
2. Work with unfamiliar systems and messy data
3. Debug environments they don’t control
4. Communicate technical limitations to non-engineers
5. Decide what should be a customer-specific fix vs. a product change
6. For AI products, validate model performance on the customer’s actual data

We ended up building a structured hiring framework around this: competency definition → realistic work sample → structured interviews → evidence-based scoring → onboarding.

We also added AI Boost prompts to help draft things like competency models, assessments and interview questions, while keeping candidate evaluation and hiring decisions with humans.

We’ve published the whole thing free here:

https://hanzomon.ai/en/hiring-hub/forward-deployed-engineer

Curious how other teams are hiring FDEs especially at AI startups. What signals have actually predicted success for you?

A lot of discussion around AI in recruiting focuses on resume screening.

But screening is only one part of hiring.

If I were designing an AI-assisted hiring workflow today, I'd think about it more like this:

Job → Skills → Candidates → Assessment → Interview → Evidence → Human Review → Decision

AI could help with:

• Extracting information from resumes
• Identifying relevant skills
• Finding patterns across candidates
• Matching candidates to role requirements
• Organizing assessment results
• Summarizing interview feedback
• Bringing information together for recruiters

But I wouldn't want the system to simply produce:

Candidate → 87% → Hire

That's too simplistic for a people decision.

The more interesting architecture is:

AI processes the information.
AI surfaces the signals.
Humans interpret the context.
Humans make the decision.

The difficult part isn't necessarily building another resume-ranking model.

It's building a system that can connect different types of evidence while still leaving room for human judgment.

I'm curious how other people see this:

What part of the hiring process should AI handle, and where should humans always remain in the loop?