Really excited to officially launch AI Sourcer in Elly today!

Last fall, we launched a (very early) beta for the AI Sourcer and over the past few months we rebuilt it from the ground up around one core idea:

Sourcing should feel like continuing the hiring conversation, not rebuilding it from scratch.

Almost every recruiting team still uses LinkedIn, boolean searches, spreadsheets, enrichment tools, and outreach platforms just to run a search. With Elly, you can do it all in one tool:
1. Use Elly as a notetaker on a kickoff call
2. Automatically write a JD, create a hiring plan, and build out scorecards
3. Chat to search across 100M+ US-based candidates
4. Ask Elly ~why~ certain candidates are being surfaced and refine the search as needed
5. Run outbound campaigns on email & LinkedIn
6. Use Elly's ATS to run the rest of your process

Try it out here: https://lnkd.in/eNM3ecMr

Next week, we’re hosting a live “old way vs new way of sourcing” showdown. I’ll be using AI Sourcer while our Head of Search runs a traditional LinkedIn + boolean workflow side-by-side on the same role.

Register at the link in the comments!

AI doesn't replace recruiting judgment. It scales it.

That's why giving an AI sourcing tool to a Talent Associate can feel a lot like handing the keys to a Ferrari to someone who just got their driver's license.

The Ferrari isn't dangerous.
The lack of experience behind the wheel is.

AI sourcing tools are incredibly powerful. They can identify thousands of candidates, automate research, generate outreach, and uncover talent pools that would have taken recruiters days or weeks to find.

But they can also amplify mistakes.

A bad search becomes a bigger bad search.
A flawed prompt becomes a larger flawed prompt.

A recruiter who doesn't understand candidate evaluation, market mapping, or sourcing fundamentals can create a lot of noise very quickly.

The best recruiters I've worked with don't use AI to replace their expertise.

They use AI to multiply it.

The future isn't AI replacing recruiters.

The future is recruiters who understand recruiting fundamentals using AI to outperform everyone else.

Learn to drive before you floor the accelerator.

Washington, DC — May 24, 2026 — HiredAI today announced the general availability of Cortex, an automation layer built into its recruiting platform that handles two of the most time-consuming functions in modern hiring — inbound applicant triage and outbound candidate sourcing — without requiring recruiters to babysit either one.

Cortex is now live for all HiredAI customers at app.hiredaiapp.com/cortex, with no separate purchase required.

It's Monday. Stop letting manual administrative tasks slow down your search. ⚙️🤖

As a Recruiter with an engineering background, my obsession is always efficiency. In a fast-moving market, the recruiters who win are the ones who automate the noise so they can focus on the human connection.

If you are looking to accelerate your workflow this week, here are the top 3 ways I am leveraging AI right now - without compromising compliance or executive quality:

1. Building Executive Market Reports with Claude 📊 When I’m working on Director, VP, or SVP roles with leadership, they don’t want a list of names; they want market intelligence. I use Claude as a "thinking partner" to help structure talent maps, organize salary benchmarking data, and build polished executive-level reports. It turns hours of data-crunching into a strategic overview in minutes.

2. Polishing Interview Notes with Gemini (Compliance-Safe) ✍️ Like many of you in regulated industries like banking or tech, I cannot use AI transcription bots during live interviews due to strict data privacy and compliance. My workaround? I take my raw, messy, bulleted notes from the call, feed them into Gemini, and ask it to structure, clean, and format them into a highly professional summary. It saves my hands from typing, keeps my data secure, and delivers flawless notes to Hiring Managers.

3. Next-Gen Sourcing with LinkedIn’s "Hiring Assistant" 🔍 Sourcing for niche tech roles can be a black hole. Using LinkedIn’s built-in AI assistant helps pipeline building by identifying overlapping skills and "passive" talent patterns that traditional Boolean strings might miss. It doesn't replace the recruiter's eye, but it speeds up the initial calibration.

💡 Bonus Recruiter AI Tip: If you haven't looked into autonomous AI agents like Manus, keep an eye on them. We are moving from "chatbots" to "agents" that can execute multi-step research workflows in the background while you are on the phone interviewing.

The goal of AI in TA isn't to replace the human element - it’s to buy us the time to actually be human.

Recruiters: How are you using AI to "debug" your workflow this Monday? What’s your favorite prompt right now? Let’s share notes below! 👇

#TalentAcquisition #TechRecruiting #AInTA #ExecutiveSearch #RecruitmentEfficiency

I've been saying it since they first started. Metaview is a game changer and they continue to improve. If you arent using this tool for your recruiters, might wanna check it out!

Most recruiters are using AI wrong. Heck, I was using AI wrong in the beginning. They treat it like Google.

“Write me a job description.”
“Summarize this resume.”
“Draft an email.”

That’s not where the value is.
The real shift in thinking is this...
AI is not a tool but it’s a workflow layer.

Here’s what that looks like in practice...

Before AI:
1) Open req
2) Write JD from scratch
3) Manually screen 50 resumes
4) Start sourcing

After AI:
1) AI drafts the JD from intake notes
2) AI summarizes and ranks applicants against non-negotiables on the req
3) AI generates search strings
4) Recruiter focuses on decisions, not typing

Same job. Completely different leverage.

The teams who will be the most efficient won’t be the ones “using AI.”

They’ll be the ones redesigning their workflow around it. This doesn't need to be scary. It's actually super cool.

I’ve been heads-down building my AI workflow for the past few months.

As a Talent Partner at a VC fund, I’m constantly context switching: sourcing candidates, prepping for calls, writing content, tracking market signals, supporting founders.

The cognitive load is real.

So I started systematically automating the parts that don’t need me to be me so I can spend more time on the parts that do. 🛠️

Here’s what I’ve built so far.

🔍 Talent workflows
• Auto generated weekly prep sheets for all candidate 1:1s pulled from calendar and intake notes
• “Jobs of the Week” LinkedIn posts drafted automatically from role inputs
• Candidate matcher that scores my entire talent pool against any role in seconds
• LinkedIn network matcher using the same scoring across my 20,000+ connections
• Student finder that analyzes project depth not just keywords to surface top interns and new grads 🎯

📊 Market intelligence
• Daily briefing with layoffs, acquisitions, funding rounds and ready to use Boolean strings
• Weekly digest that turns signals into a portfolio ready email
• Monthly report covering news and press for every portfolio company 📰

🧠 Founder support
• Values based interview guide generator customized in minutes
• Talent playbook builder with Notion ready guides for hiring and people topics from pre seed to Series A
• Daily briefing also includes AI news and top stories

💡 Bonus
On workout days it tells me what to do at the gym. Yes, really. 💪

I’m not a developer.

I built all of this in Claude.

Took a few weeks of iteration. Saving hours per week already.

If you’re in recruiting, VC, or any role heavy on relationships and content, building your own system is very worth it.

The ROI is real.

Most recruiting tools promise "AI-powered sourcing" but give you the same generic LinkedIn searches with a chatbot wrapper.

I built my own AI sourcing agent instead — and it outperforms every vendor tool I've tested.

Here's what's different: Instead of one-shot prompts that return garbage results, I created a multi-step workflow using Claude's code capabilities.

The agent starts with ecosystem mapping — identifying companies, communities, and publications where your ideal candidates actually spend time. Then it moves to individual sourcing with built-in quality checks.

30% of initial candidates get filtered out automatically based on criteria I define. No more manually sifting through hundreds of irrelevant profiles.

The key insight: You need an agent that can write code, not just search databases. Once it can code, it can build custom tools for any workflow you throw at it.

I broke this down step by step in this week's video, including the full technical walkthrough and all the code you need to build your own.

https://lnkd.in/eyVwvgSW

What's your biggest frustration with current sourcing tools — the volume of bad matches or the lack of customization?

#AIforHR #TalentAcquisition #HRAnalytics #PeopleAnalytics

I received another "How did you find me?" yesterday.

I've been using an AI sourcing tool over the last few months to supplement other sourcing efforts. What this means? Semantic search is greater than keyword match.

For this search, I was using two key questions as a screener, one of which was focused on hardware design.

This person did not explicitly state this experience anywhere on their LinkedIn profile. However, they did have their industrial clients listed in their experience section of a consultancy.

The tool put two and two together.

Here's the Friday lesson: SEO and keyword optimization used to be the play. Semantic search is a game-changer.

It's not necessarily looking for any keyword match. Story, project, clients/customers, industry....these details come into play.

To be honest, semantic search is better for anyone who hasn't taken the time to optimize. But if you haven't, think about a profile refresh. In this case, just adding clients to the profile was the make-or-break.

Are your clients, industries, and projects actually visible on your profile?

We’ve built an AI operating stack that’s helping our recruiting firm move faster without adding more admin overhead.

Current stack:

- AI sourcing workflow to identify candidate leads
- Data enrichment workflow to improve contact and company context
- LLM + MCP connection to read/write directly in our CRM
- AI roll-up workflow to prep outreach-ready records
- Email + texting workflows for faster candidate response
- Social media content agent and scheduler for consistent daily posting and client development

What this does for us:

- Frees recruiters from low-value admin work
- Keeps CRM data cleaner and more current
- Speeds up candidate identification and outreach
- Improves consistency in market visibility and brand presence

We’re doing this with a ~400,000-person database, and it’s made a major impact on execution speed.

If you want the exact framework, comment SYSTEM and I’ll send it.