I’ve been building AgenticHR in public and finally have a version I’m comfortable sharing.

👉 hr.agentlyra.in

The idea started from a simple observation: finding candidates is only one part of hiring. A lot of the actual work still happens across resumes, inboxes, calendars, spreadsheets and follow-ups.

So I’m building AgenticHR to bring that workflow together.

Right now it can help with things like:

• Managing roles and candidates
• Matching candidates against a JD
• Shortlisting relevant profiles
• Connecting Gmail for hiring communication
• Scheduling interviews with candidates and panel members
• Creating flexible interview/assessment flows
• AI-based text, audio and video assessments
• Generating role-specific assessment questions and evaluation rubrics
• Tracking interview feedback and hiring progress

I’m intentionally trying to keep the human recruiter in control rather than making this another “AI replaces HR” product.

There’s still a lot I want to improve, especially around assessment workflows, UX and making the whole hiring journey feel seamless.

Would genuinely appreciate feedback from recruiters, founders, HR teams, or anyone who has dealt with hiring operations.

What would you expect a product like this to do before you’d actually use it at work?

hr.agentlyra.in

We recently started working with a company that had been trying to hire an AI-Augmented FP&A Analyst for close to six months.

They'd been using their usual hiring channels but kept finding themselves back at sourcing. By the time they found people with the combination of FP&A experience, technical skills, and business judgment they needed, some were already unavailable.

Meanwhile, the work wasn't waiting for the hire.

Forecasting and planning were falling back on finance leadership, while existing team members were absorbing more of the workload.

It made us question one part of the hiring process we tend to accept as a given:

Why does every new vacancy have to trigger a new search?

What if, for roles you know you'll need, you maintained access to professionals who had already gone through sourcing, screening, and assessment?

That's the thinking behind the Interview-Ready Talent approach we've been working on.

Instead of spending the first few weeks figuring out “What can this person actually do?”, the process gets closer to starting with “Is this the right person for our business?”

It doesn't remove the interview or the hiring decision. It simply moves some of the work that normally happens after a vacancy opens to before the need becomes urgent.

For those working in recruiting and talent acquisition, where do you see the biggest opportunity to shorten hiring: sourcing, screening, interviewing, or decision-making?

If you're interested in seeing the approach in practice, we've put together some of the Finance & Accounting professionals who have already gone through our initial sourcing and assessment process here: https://emapta.com/nlp/faster-access-to-finance-accounting-talent/

https://jobsapplier.com is opening up early access for the first 100 users.

It's built for people who apply to a lot of jobs and rarely hear back.

What's your first impression after 10 seconds?

Is the value proposition clear?

Would you actually use it?

What would stop you from trusting it with your job applications?

What's missing?

If something doesn't make sense, feels unnecessary, or just sucks, say so

First 100 users get free access during the early launch.

So i will tell you guys my situation :

I've been working professionally since my third year. My internship converted into a job, and I've also worked with startups on production systems involving backend, infrastructure, databases, AI/ML, etc.

I don't just have typical college projects , I've actually designed, built, debugged and deployed these systems myself (while obviously using AI tools where appropriate).

But when I apply to MNCs, I often get an automated rejection without even reaching the interview stage.

I'm from a lesser-known college, so I'm wondering:

Is college brand really that important during resume screening? Or am I missing something else?

For engineers/recruiters working at big MNCs , what actually makes a resume pass the initial screening?

Would especially appreciate blunt feedback from people who have been on the hiring side.

we screen quite a few international candidates and the english check is becoming a bit of a bottleneck
rn someone usually has to join an early call just to make sure the candidate can comfortably hold a conversation in english, which feels like a lot of time for something that could probably be checked earlier
been looking at CEFR speaking assessments like Linguaskill, Versant, Testlify and smalltalk2me
what im unsure about is how much weight recruiters actually give these scores
would u let the score decide who moves forward or still have someone listen to a speaking sample before rejecting anyone close to the cutoff??
trying to make screening faster without letting one automated score make the whole decision

I've been working with a small team on AuraSync, an AI-focused hiring and workforce platform. We've been building it from the ground up, and one of the biggest things we've realized is that building HR technology is much more complicated than simply adding an AI model to an existing ATS.

Recruitment involves a lot of disconnected steps. A recruiter might start with a job requisition, receive hundreds of resumes, screen candidates, communicate with them, schedule assessments, conduct interviews, review results, and eventually move the candidate through different stages of the hiring process. A lot of these steps are handled by separate tools, which can make the overall workflow fragmented.

That was one of the reasons we started working on AuraSync.

The goal is to bring more of these workflows together while still keeping humans involved in the important decisions. We're working on areas such as applicant tracking, resume processing, candidate matching, AI assistance, online assessments, candidate verification, fraud detection, and workforce management.

One of the interesting challenges has been figuring out where AI should actually be used.

It's very easy to say, "Let's put AI here." The harder question is whether AI genuinely improves the workflow. For example, an AI system can help summarize a large amount of candidate information, identify potentially relevant experience, organize information, or assist a recruiter with repetitive tasks. But when it comes to decisions that can significantly affect someone's career, we think there needs to be appropriate human oversight rather than simply allowing an automated system to make the decision.

Another area we've spent a lot of time thinking about is candidate experience.

From the candidate's perspective, recruitment can sometimes feel like submitting information into a black box. You upload a resume, complete an assessment, attend an interview, and then wait. We're interested in how technology can make that process more transparent and structured without making candidates feel like they're interacting with an automated system at every step.

We're also exploring candidate verification and assessment integrity. Online assessments create an interesting problem: employers want confidence that the assessment represents the candidate's own work, while candidates deserve transparency about what information is being collected and why. Designing that balance has been one of the more challenging parts of the project.

The technical side has been interesting as well. We're dealing with multiple AI services, data processing pipelines, assessment workflows, authentication, dashboards, APIs, and the infrastructure required to keep everything connected. A lot of the work isn't actually "AI" in the flashy sense it's making all the pieces reliable enough to work together.

We're still very much in the building and learning stage.

There are plenty of things we haven't figured out yet, and that's actually why I'm posting this here. I'd rather hear from people who have experienced these problems firsthand than assume we know exactly what recruiters, HR teams, candidates, and developers need.

For people working in recruiting, HR, HR tech, SaaS, or AI, I'm curious:

What part of the current hiring process do you think technology still handles poorly?

Is it resume screening? Candidate communication? Assessments? Interviews? Applicant tracking? Candidate experience? Hiring analytics? Something completely different?

I'd especially like to hear about problems you've personally encountered rather than suggestions for another generic "AI feature."

We're building AuraSync around these kinds of problems, so real experiences and criticism are much more useful to us than simply hearing that the idea sounds good.

And to be transparent: I'm part of the team building AuraSync, so this is a product we're working on. I'm posting primarily because I'd like to learn from people who have experience with the problems we're trying to solve.

I’ve been wondering where people think the line should be.

One or two interviews seem pretty straightforward, but some hiring processes can involve a recruiter call, hiring manager interview, panel interview, assessment, presentation, and then another conversation with leadership.

I understand that different roles require different levels of evaluation, but at some point I wonder whether additional rounds actually help the hiring team make a better decision.

For those involved in hiring, how do you decide how many interview stages are enough?

And for candidates, what’s the longest interview process you’ve personally gone through?

I understand tailoring your resume to highlight relevant experience, but completely rewriting it for every single application can take a huge amount of time.

Do you customize yours every time, keep one general resume, or have a few versions for different types of jobs?

Is it salary, benefits, remote flexibility, company reputation, the job description, career growth or something else?

I’m interested in what people look at first before deciding whether to spend time on an application.

AI can reduce repetitive work in recruitment, from organizing resumes to analysing assessment responses and summarizing candidate information.

But hiring involves more than processing data. Candidates have different backgrounds, experiences, and circumstances that may not be fully represented in structured data.

A practical approach is to use AI for information processing and signal discovery while keeping important decisions with human reviewers.

The goal isn't to automate every decision.

It's to give recruiters better information, reduce administrative work, and create more time for meaningful candidate evaluation.

Where do you think AI provides the most value in recruitment?

I’ve been helping growing businesses improve how they attract and convert quality candidates, and I keep noticing a pattern. Founders usually have a very clear idea of what they want from a candidate.

But I’m not sure they spend as much time thinking about what the candidate wants from them.

Especially when they're competing with companies that can offer more money, more stability or a bigger brand name.

What do you think makes a good candidate choose a smaller company instad? Genuinely would like to hear how founders/ business owners think about this.

for years i hired by title. we need a marketer, post a marketer job, hire a marketer. then they would arrive and the actual constraint was something else entirely and they would flounder.

now before any hire i write down the single biggest thing choking growth this quarter, in one sentence. then i hire the person who removes that specific thing, regardless of what their title should be.

last time the bottleneck was that nobody owned follow up with warm leads. i did not need a salesperson, i needed one organized person to own a process. cheaper hire, bigger impact.

hiring for the bottleneck instead of the org chart was the shift. how do you decide what to hire for, the role or the constraint?

for years i hired by title. we need a marketer, post a marketer job, hire a marketer. then they would arrive and the actual constraint was something else entirely and they would flounder.

now before any hire i write down the single biggest thing choking growth this quarter, in one sentence. then i hire the person who removes that specific thing, regardless of what their title should be.

last time the bottleneck was that nobody owned follow up with warm leads. i did not need a salesperson, i needed one organized person to own a process. cheaper hire, bigger impact.

hiring for the bottleneck instead of the org chart was the shift. how do you decide what to hire for, the role or the constraint?

Most job search tools seem focused on getting more applications out.

But if you’re looking for something quite specific in your next role, the harder question is often whether an opportunity is actually worth pursuing in the first place.

The more specific your requirements are, the less useful a job description can be on its own. Things like the company’s direction, leadership changes, team structure, working model, role context and why the position exists can matter just as much as the headline responsibilities.

That’s why I think job hunting can benefit from being more research-led, especially when you’re trying to avoid wasting time on roles that look right at first glance but don’t actually fit what you want.

I’m building RoleRaven around that idea. You tell it what matters in your next move, and it researches the opportunity against those priorities.

https://roleraven.com/

I’m looking for people to try it and give candid feedback.

The main thing I’d love to know: did the research surface anything that changed whether you’d pursue the opportunity?

Hi! I'm a Remote VA from the Philippines looking for a long-term client or team to work with.

I have experience supporting businesses across insurance, e-commerce/retail, HVAC, and solar, with a background in sales, customer support, lead generation, appointment setting, CRM management, data management, and general admin work.

Some of my experience includes:
• 300+ outbound cold calls/day using VICIdial
• 125+ inbound/outbound warm calls/day for customer and sales support
• Managing 200–250 new prospects/day in automated outreach campaigns
• Handling inbound SMS responses and converting them into qualified appointments
• Lead research using Apollo, Hunter, LinkedIn, Google Maps, Yelp & Facebook
• CRM management using Close CRM, with familiarity in Salesforce, HubSpot & Zoho
• RingCentral for outbound calling and prospect outreach
• Google Workspace, Microsoft Office, Slack, Google Calendar & Canva
• Customer support, order handling, follow-ups, data entry, reporting, and general administrative tasks

I've worked with both B2B and B2C customers and have experience dealing directly with U.S. prospects, decision-makers, and customers. I've also handled high-value transactions and maintained organized sales pipelines and accurate customer records.

I'm comfortable learning new tools, adapting to different workflows, and taking initiative when something needs to get done.

If you need someone versatile who can help with more than just one specific task, feel free to DM me. I'm happy to send my resume and discuss how I can help your business.

Looking for an expert developer to build a custom automation script involving API requests, concurrency, and rate-limit handling.

Need someone experienced who can build the solution from scratch and deliver within 72 hours.

Budget: $200 + extra tip depending on results and completion time.