Let recruiters understand your experience, decisions, and impact. Answer role-fit questions from career evidence you approve. Show how you think, not only where you worked. Qualify the opportunity before it reaches your calendar.Let recruiters understandyour

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TLDT is a candidate-owned AI career profile. It sits between a static résumé and the first recruiter call: a recruiter can ask role-specific questions, while the profile answers only from professional evidence the candidate has reviewed and published. It is designed to explain scope, decisions, outcomes, and working style—not to imitate a personality or replace a live interview.

A résumé and LinkedIn profile are optimized for scanning, so they rarely explain how large a problem was, what the candidate personally decided, which constraints mattered, or why an outcome is relevant to a vacancy. TLDT lets a recruiter investigate those questions asynchronously before scheduling. The goal is a better-informed first call, sharper follow-up questions, and earlier visibility into obvious fit or evidence gaps. The candidate—not the recruiter—creates and shares the profile.

A résumé is fixed and broad; TLDT can adapt the explanation to the role and the recruiter’s question. A portfolio usually shows selected outputs; TLDT can connect those outputs to ownership, trade-offs, and results. A generic chatbot may answer from an open-ended prompt or arbitrary documents; TLDT is constrained by a published, candidate-approved memory and explicit disclosure boundaries.

The candidate adds career evidence such as a résumé, professional profiles, interview transcripts, project notes, and decision context. They review the resulting memory, choose what is Public or Private, and publish an immutable version. Recruiter conversations can use only the active published Public memory. Private memory, draft changes, internal source excerpts, filenames, and tool traces are excluded from the recruiter-facing answer.

TLDT is instructed to make the gap explicit, ask a focused clarification, or decline to state the fact instead of filling it with a plausible invention. The candidate can review owner-visible provenance and conversation traces, correct the underlying profile, and publish a new version. Like any AI system it is not infallible, so keeping the approved evidence current and reviewing conversations remain part of the product workflow.

TLDT cannot claim personal interest, confirm availability, accept or reject a role, negotiate terms, or make commitments for the candidate. The profile owner can separately connect Cal.com and enable scheduling. After the recruiter is validated, gives a concrete purpose, and explicitly agrees to book, TLDT may open a bounded booking form. The recruiter chooses an available slot and meets the real candidate who created the profile; this booking flow does not give the AI broader authority to act.

The candidate can review the transcript and an owner-facing summary, understand what the recruiter wanted, see where the profile answered well or lacked evidence, and decide personally whether to continue. Recruiters see the conversation they are having, but not Private memory, provenance records, policy checks, provider metadata, or other owner-only diagnostics.

The candidate adds a real vacancy and runs a private 20- or 40-minute first-stage HR screen against the same published career context. They can answer manually, generate an editable TLDT draft, or use Auto mode, then inspect the full transcript and HR verdict. Simulation is preparation—not a public conversation—and it does not let the HR agent change published memory or make commitments.