Sit through three vendor demos this quarter and you will hear the word "agent" in all three. The keyword-search tool you used last year is an agent now. The Chrome extension that scrapes LinkedIn is an agent. The chatbot that writes outreach is an agent. The label got applied to everything the moment it started selling, which means it now tells you almost nothing about what the product does.
That is a problem when you are the one signing the contract. The gap between a tool that genuinely runs sourcing for you and a tool that renamed its search box is the difference between getting time back and paying more for the same work with a chat window on top.
This is a buyer's guide, not a ranked list. It gives you five questions to ask in any demo that separate a real sourcing agent from a relabeled tool, the signals to watch for in the answers, and an honest read on where the category actually is in 2026. If you want the plain definition of the category first, why a custom GPT can't source candidates covers what "agent" means and why most things called one cannot source at all.
The five questions that separate an agent from a tool
Ask these in the demo, in this order, and make the vendor show you rather than tell you.
1. Does it run the whole job, or speed up one step?
A tool accelerates a step you still drive: you run the search, you read the results, you pick names, you write the messages. An agent takes the goal and runs the steps itself. The test in a demo is simple. Ask the vendor to give it a role and then take their hands off the keyboard. If the product needs a human click between every stage, it is a faster tool, which is fine, but it is not an agent.
2. What data can it actually reach?
This is the question that matters most, and the one most demos skate past. An agent is only as good as the data it can see. Ask exactly where it sources from: LinkedIn alone, or many sources at once? Can it see passive candidates who never set a status, or only people who raised a hand? Can it read your own ATS to avoid surfacing someone you placed last year? A tool that can only re-search the same LinkedIn results you already see is not giving you reach. It is giving you a faster way to look at the same shelf.
3. Does it judge fit and reachability, or just return matches?
Returning a list is the easy part. The work is knowing which names are worth your time. Ask whether the product explains why each profile fits the brief in plain language, whether it gives you a read on compensation so you know who sits inside the budget, and whether it has any signal on who is actually open to a move. A product that hands you 200 profiles ordered by keyword overlap has moved the busywork, not removed it.
4. Does outreach live inside it, or do you export to another tool?
This one is a fast tell. If the answer to "how do I contact these people" is "export a CSV and load it into your sequencer," you are looking at a sourcing tool, not an end-to-end agent. A real agent treats outreach as part of the job it runs, not a handoff to a different product. Be precise here about what is automated versus assisted, and watch for over-promising (more on that below).
5. Does it keep working when you close the tab?
A tool works while you are in it. An agent keeps running in the background and tells you when there is something worth your attention. Ask whether you can set it on a role and walk away, and what actually happens while you are in interviews or asleep. If the product only does something when you are actively prompting it, the "agent" is a chat session, not a background worker.
| What you ask | Relabeled tool | Real sourcing agent |
|---|---|---|
| Who runs the steps | You click through each one | It runs the workflow on a goal |
| Data it reaches | Re-searches what you already see | Many sources, including passive candidates and your ATS |
| What it returns | A list ordered by keyword overlap | A shortlist with fit rationale, comp, and reachability |
| Outreach | Export to a separate tool | Part of the job it runs |
| When it works | Only while you prompt it | In the background, then alerts you |
Why the data question outranks the rest
If you only have time for one question, make it the second one. Autonomy, a clean interface, and a good chat experience are easy to build on top of any model. Live access to candidate data your own stack cannot reach is not, and it is the thing that actually decides whether an agent produces names you could not have found yourself.
Plenty of tools that market themselves as agents in 2026, names like Gem, GoPerfect, Leonar, Pin, and Tezi among them, are real products solving real parts of the workflow. But the marketing word is doing a lot of work across the category, and two products with the same "agent" label can sit on completely different amounts of data underneath. The interface is what you see in the demo. The data layer is what you live with after you sign. Test the second one harder than the first.
Glozo's Sourcing Agent against this test
It is only fair to hold our own product to the same five questions, including where it falls short.
On the whole-job question, Glozo's Sourcing Agent runs in the background in manual mode: you create it from a search, it works the role on its own, and it emails you when there are results worth a look. An auto mode and a good-match review step are designed but not live yet, so today you stay in the loop on each batch. That is honest manual-mode autonomy, not a hands-off claim.
On data, this is the part Glozo is built around. The Agent reads more than 10 million market signals every month and pulls profiles from 30-plus sources, not LinkedIn alone. On fit and reachability, it runs three things a generic model cannot produce: a plain-language rationale for why each profile fits the brief, a Market Value estimate so you can see who sits inside the budget before you reach out, and an Open to Offers read that points to passive people likely to be receptive rather than only those who set themselves to "open to work." On outreach, Glozo includes outreach in the platform today in manual mode, so contact happens in one place rather than a separate sequencer, though it is not a fully automated multi-channel sequence. And on persistence, running in the background and emailing you when results are ready is the default behavior, not an add-on.
The point of running our own product through the checklist is the checklist, not the product. Use the five questions on every vendor you talk to, including this one, and ask each to show rather than tell.
How to run the test without a six-month commitment
You do not need a long pilot to apply this. Give two or three vendors the same hard-to-fill role, ideally one you have struggled to source, and watch the first run in the demo. Count the human clicks. Ask where every candidate came from. Check whether the shortlist tells you why each person fits and who is reachable, or just how many keywords matched. Note whether outreach happens in the product or in an export.
The vendor that needs the fewest clicks, reaches the most data beyond LinkedIn, and hands back a shortlist you can act on rather than a list you still have to qualify is the one closest to a real agent. If you want the wider category map of AI tools by job rather than by brand, our guide to picking AI recruiting tools by category sits next to this one.