The new search

Search Github has a new engine. Describe the role in plain language, and a research agent reads that description along with any context you attach, sources developers by the work they have actually shipped on GitHub, and strengthens each match with LinkedIn. Candidates arrive in rounds of 50, and a thumbs up or down on any card shapes the next round.

Vamo sources engineers from their public GitHub work. Book a demo and we'll run a live search together on a role you have open right now.

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Sourcing runs in rounds

Every search returns a round of 50 developers. The agent reads your request and any context you added, finds people through the projects they build, then confirms the fit with their LinkedIn profile. A round is a complete set to work through, and every round is new people, never a repeat of a name you have already seen.

When a round is thin, the agent widens on its own before it gives up: it broadens the technical interests and fans out to similar companies, and it never relaxes the location you set. When you want more, Source another round produces a fresh 50 tuned by everything you have rated so far.

The filters, grouped the way a search actually works

Open Refine search in the top right to see the plan the agent drafted, organized into three tabs.

Context holds what the search was built from: the Location (the one hard requirement), your Original request, an attached Job description, and any Context links like a company site or a blog post.

GitHub is what their code should be about:

• Subjects: the domains the work covers, like dating apps or physics simulation.
• Skills and technologies: languages, frameworks, and tools.
• Projects: seed repositories to search near, set to Similar or Exact contributors.
• Project stars and Followers: ranges that shape ranking.
• Early career signals: surfaces learning-in-public work, courses, and up-and-comers.
• AI focused: biases every angle toward agents, MCP, LLMs, and inference.

LinkedIn is who they are professionally:

• Require a LinkedIn match: narrows to people with a linked profile.
• Experience: Early-career, Up to senior, or All levels.
• Unconventional paths: product managers, solutions engineers, and second-career builders who ship real code.
• Individual Contributors: engineers at any level including staff and principal, without founders, executives, and people-managers.
• Likely Looking: a soft read on who may be open to a move.
• Companies: match on current employer or anyone who has worked there, with a Current and All switch.
• Current company size and School.

Every filter is a strong signal that shapes ranking. Location is the only hard requirement, so a round always fills instead of coming back empty.

Rate a card to steer the next round

Each result carries the evidence for why it matched: the strength signals and confirmed LinkedIn details under Who they are, and the specific proof from its GitHub work under Why they match. A thumbs up or thumbs down on any card feeds the agent. Up reinforces what it found, down lets you say what ruled the person out, and the next round reflects both.

How to use it

What to expect

Rounds land in under a minute and carry a repo on every card, so the reason a person surfaced is on screen. Ratings compound: the more you react, the closer each round gets to the role. Earlier searches stay in the sidebar under Search Github, so you can return to any of them and pick up where you left off.