What if the candidate has a sparse online presence?

Tycoon Agent reports what she found honestly — "low public footprint, brief based on resume only" — and tilts her interview questions toward open-ended exploration rather than pre-loaded specifics. She never invents details to fill gaps.

Can Tycoon Agent also rate candidates or pick a winner?

She gives a role-fit score 1-10 per candidate but explicitly avoids ranking — hire decisions involve fit, team, and gut signals she can't see. Her job is to make sure you walk in informed; the call stays yours.

What about confidentiality — does she store the resumes?

Resumes are processed in-session and discarded. They're not added to any training data or persistent memory. The brief itself stays in your Lark thread, scoped to your workspace, and you can delete the thread anytime.

Can she do this for 10+ candidates?

Yes — she scales linearly, ~8-12 minutes per candidate to gather sources and write the brief. For a batch of 10 you'd have all briefs in ~2 hours. She'll prioritize by your interview schedule so the next-up candidates land first.

Ask Tycoon Agent: Screen these 3 candidates before I interview them

You'd think this needs 90 min per candidate of resume reading — Tycoon Agent hands you one-page briefs while you finish coffee.

The short answer

Tycoon Agent screens candidates by reading everything publicly available about them and synthesizing a one-page brief tailored to your role. For each candidate she pulls the resume, LinkedIn profile, GitHub (for engineers), public writing or talks, and any past company context, then outputs: top 3 reasons to hire, top 2 risks or red flags, 5 tailored interview questions targeting the candidate's specific gaps and strengths, and one "deep cut" question grounded in something they shipped or wrote. She cross-references their background against your role spec (pulled from your job post or recent chat) and flags any mismatch (e.g., "role says principal-level architecture, last 3 jobs were IC implementation"). Output is one Lark message per candidate, ready to read on your phone before the call. 5 minutes of prep replaces 90.

How Tycoon Agent actually does it

Gather sources per candidate
Resume PDF, LinkedIn profile, GitHub (repos + contributions), Twitter/X if relevant, blog posts, conference talks, prior companies' Crunchbase entries.
LinkedIn Sales NavigatorWebSearchGitHub
Pull the role spec
Read the job post, prior chat about what you're hiring for, and your hiring rubric if you have one in Notion.
Synthesize the brief
One page per candidate: 3 hire signals, 2 risks, role-fit score 1-10, 5 tailored questions, 1 deep-cut question grounded in something they shipped.
Flag mismatches
Title inflation, gaps in employment, repeated short tenures, stale tech stack vs your needs, or anything that warrants follow-up in interview.
Deliver in Lark
One message per candidate, formatted for phone reading. Linked sources at the bottom. Sent at least 30 min before each interview.
Lark

What it looks like in chat

YouScreen these 3 senior backend candidates I'm interviewing tomorrow.

Tycoon AgentGot the 3 resumes. Pulling LinkedIn, GitHub, and public writing for each. Briefs in Lark by 8pm tonight. Quick preview: **Candidate 1 (Maria Chen, ex-Stripe)** — Strong: 7 yrs payments infra, contributed to go-stripe. Risk: led a 12-person team last 3 yrs, your role is IC. Deep-cut Q: "Walk me through the idempotency edge case you wrote about in the Stripe blog." **Candidate 2 (Devon Park)** — Strong: shipped 2 production Postgres extensions. Risk: 3 jobs in 2 years, all under 9 months. Worth probing why directly. Deep-cut Q: "Your `pg_partman` PR was rejected — what did you learn?" **Candidate 3 (Aiyana Tom)** — Strong: built a side project that hit 8K GitHub stars in your space. Risk: no prior team experience, all solo. Deep-cut Q: "What did you cut from your side project that you wish you'd kept?" Full briefs in Lark in 4 hours. Send the calendar invites?

What you get back

One Lark message per candidate (5-7 bullets, phone-readable) with hire signals, risks, role-fit score, 5 tailored questions, and a deep-cut question. Source links at the bottom.

Cadence: On-demand per interview batch.

Screen these 3 candidates before I interview them