Here's 5 recruiting agents I use daily at Abnormal AI.

🔍 Outbound Sourcer: Thinks like a top recruiter and a top candidate at the same time. Reads the profile, infers what motivates them, writes outreach that actually lands. Not templates. Actual personalization at scale.
📝 Intake Agent: Stops bad reqs before they open. Pushes back on vague job descriptions and forces clarity on what "good" actually looks like. Less interview noise. Fewer late-stage surprises.
🎯 Debrief Synthesizer: Turns messy panel feedback into a clear hiring decision. Flags conflicting signals, catches bias patterns, and makes a recommendation. Hire, no hire, and why.
🦄 Recruiting Ops Automator: Finds where your process is quietly breaking. Time-in-stage, funnel drop-off, and offer slowdowns — surfaced automatically, no manual report needed.
🏆 Talent Brand Agent: Keeps your voice consistent across every candidate touchpoint. Same positioning, same tone, no drift. It also includes employee stories for the different job families.

The numbers across two quarters: 88% offer acceptance with a 46.6% InMail response rate — nearly 2x benchmark, up 22.6% since October.

That's what recruiting on systems looks like. Most teams have the same tools.

The gap is whether you're building or waiting.

I keep building things and then not knowing how to talk about them.

Not because they're complicated. Because every time I sit down to write a LinkedIn post, I realize the thing I want to say is actually 1,200 words long :)

So I'm putting it all in a new blog. I want us to share what we're building and to show that getting there isn't nearly as intimidating as it sounds. I started where most people start. I made a lot of mistakes. I lost track of time in my home office more than once. And I got somewhere I couldn't have imagined a year ago.

The first post is about the last year: starting with ChatGPT and job descriptions, learning to connect to data, joining Formation Bio, and eventually building tools with Claude Code that I use every single day that have fundamentally changed how I work.

Special shout out to those I've met along the way. Jason Miller , Joe Atkinson and the entire PromptMates community - it's been so fun to learn how to do this in talent together! If you're curious what that actually looks like inside a company that takes AI seriously, I hope you'll read it. https://lnkd.in/eiGPccRK

Most recruiters are leveraging AI in the wrong way and wonder why candidate experience is getting worse...

Over time, my hires are more or less evenly split between:
- Applications
- Referrals
- Sourced/headhunted.

The real time-killers remain painfully human:
- Reviewing 1000s of applications
- Rallying colleagues for referrals
- Sourcing & engaging passive talent

Once suitable and relevant candidates are in the funnel, they all get pre-screened and interviewed.

I use AI for:
✅ Summarising lengthy interview transcripts
✅ Sharing job, interview, team & culture details with candidates at scale
✅ Analysing my own hiring data

I DO NOT use AI for

❌ Reviewing or rejecting applications
❌ Engaging and messaging passive talent
❌ Conducting actual interviews

AI should elevate my experience as a recruiter, not replace my judgement or ability to interact with candidates.

Agree?

Everyone thinks AI in recruiting is about speed and efficiency. I can screen 10,000 more resumes now. I can manage 10 or 12 roles without being the bottleneck. AI will do the work I don't have time for.

That’s the wrong path.

When you think like that, you’re trying to remove yourself from the process. You’re looking at AI like it’s there to screen resumes, surface the top candidates, and call it a day. That’s what every sourcing product does.

And you can see where that leads. Just look at Eightfold. They’re now facing a class action, and The New York Times wrote about it. Their AI turned into a black box that started discriminating against candidates.

A lot of teams bought it chasing speed, not quality.

The real value isn’t in getting through more resumes. It’s in learning from the ones you already have.

Where are you sourcing wrong? What makes a quality hire in your pipeline? Which filters are hurting you instead of helping?

AI can answer those questions if you use it the right way. Give it your data and ask for patterns, not shortcuts. Let it help you find strategies, not do your homework.

You can move fast all you want, but that doesn’t always mean you’re finding better people.

Everyone is talking about AI in recruiting, but much of the conversation remains at a surface level, focusing on tasks like writing job descriptions or automating screening processes. The real opportunity for recruiters lies much deeper.

In recent months, I have been experimenting with AI in areas that traditionally consume the most time for recruiters: research, market intelligence, and talent strategy. Here are a few interesting use cases that have proven effective:

• Talent mapping in minutes: AI analyzes company ecosystems, competitors, and adjacent industries to identify non-obvious talent pools.

• Sales hiring intelligence: Quickly understanding which SaaS companies are scaling in specific regions and where strong enterprise sellers are likely to be found.

• Stakeholder advisory: Transforming raw hiring data into insights, including market compensation trends, talent availability, and realistic hiring timelines.

• Candidate insight synthesis: Summarizing lengthy interview notes and identifying patterns across candidates more efficiently.

AI is shifting the recruiter’s role from “process manager” to “talent advisor,” allowing recruiters to focus on what truly matters: people, potential, and impact.

I am curious to hear from others in talent acquisition: How are you using AI in your recruiting workflows today?

When I first used AI to draft job descriptions and posting ads with conducting search and replying email its instant output left me thrilled yet anxious—amazed by its efficiency, but fearing #TalentAcquisition or HR generalist might be replaced by this invisible tool. As I work with AI daily, I’ve gained a clear view of its pros and cons, and learned how to strengthen myself amid this shift. Such as AI-enabled Moka HR SaaS or LinkedIn redefinment of quality and quantity of output; embrace the power of AI adoption.

AI brings tangible benefits, especially for operational and administrative level. It quickly supplies materials and coherent drafts, acting as my inspiration assistant to free me from repetitive work like researching and outlining. This lets me focus on deep and boosting both quality and productivity. For data analysis, AI sorts messy data, spots trends and anomalies fast, cutting hours of late-night work and speeding up decisions. It handles tedious, mechanical tasks, lifting my efficiency greatly and leaving time for high-value thinking.

Yet AI’s flaws weigh on me and #Everyone. Over-reliance has dulled colleagues’ writing skills, stripping their work of soul until they were replaced. AI also spreads false information confidently, so careless use leads to mistakes. More worrying, it’s replacing routine jobs like simple data analysis, leaving me anxious about my own security.

To stay #irreplaceable, I now craft emotional, user-centric content that AI cannot replicate, and dig into the business logic behind data instead of only trusting AI results. I’m learning video editing and digital operations to diversify my skills, and mastering advanced AI prompts to turn it from an assistant into a partner.

In this fast-evolving AI era, I keep learning like a sponge, follow industry updates, and build cross-domain integration skills to create unique value. AI is opportunity and challenge alike—I will not be over-optimistic or fearful, but keep growing and forge my own way in this changing world.

“The AI Tsunami Is Unstoppable — Here’s How to Ride the Wave. Cultivate Relentless Curiosity. The wave is here. Don’t just survive it—master it”