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Hiring guides

These guides cover the searches teams actually run: boolean search, applicant tracking systems, interview questions, job descriptions, and the rest of recruiting when you do not have a recruiter yet.

  • Boolean search for recruiting

    Boolean search is a way to query a candidate database with AND, OR, and NOT so you only see people who match a role. It is still useful. It is also slow, easy to get wrong, and a poor fit once the search has to account for messy job titles.

  • What is an applicant tracking system?

    An applicant tracking system, or ATS, is the record of a hire. It stores the role, the people who applied or were sourced, the stage each person is in, and the notes that explain a yes or a no. The software does not hire anyone. It keeps the process from living in someone’s inbox.

  • How to write structured interview questions

    An interview question is only useful if a second interviewer would score the same answer the same way. Structured interviews do that by fixing the questions, the order, and the rubric before anyone is on the calendar.

  • How to write a job description

    A job description is a filter and an invitation. It tells a stranger what the role owns, what “good” looks like, and how to apply. Most of them fail because they list every skill the team has ever admired.

  • Recruiting metrics that matter

    A recruiting metric is worth keeping if a hiring manager would change this week’s work because of it. Counts of emails sent rarely qualify. Time, drop-off, and the quality of the shortlist do.

  • Recruiting email templates that get a reply

    Candidates can tell when a message was sent to a list. The emails that get replies are short, specific to their work, and ask for one thing. The templates below are outlines. Fill the blanks from the profile, or do not send the note.

  • How to hire software engineers

    Hiring a software engineer at a startup fails in two repeatable ways. The search looks for a job title instead of the work, and the interviews reward people who talk well about systems they did not run. Fix those two and the rest of technical recruiting gets shorter.

  • Candidate experience for small teams

    Candidate experience is not a career-site theme. It is whether a person knows what happens after they apply, how long the next step takes, and why they were rejected or advanced. Startups lose strong people by going quiet.

  • How to source passive candidates

    A passive candidate is someone who is not in your applicant pool. They already have a job. They will talk if the role is specific and the note proves you read their work. Spraying InMails at a title search is not sourcing.

  • What recruiting is, for a team without a recruiter

    Recruiting is not posting a job and waiting. It is four pieces of work: defining the role, finding people, evaluating them against that definition, and making a decision the candidate hears. On a small team, those pieces are usually scattered across a founder and a manager, which is why roles stay open.

  • How to build an AI hiring workflow

    An AI hiring workflow is a sequence you can repeat: define the role, let software find and screen people, have a person decide, and record the outcome. It is recruiting automation with a named owner for the judgment. It is not a chatbot pasted onto an old process.

  • AI recruiting and compliance

    Using AI in hiring means you should be able to explain the process to a candidate and to your own team. This page is a practical checklist for that explanation. It is not legal advice, and it is not a substitute for counsel in your jurisdiction.

  • How AI companies hire

    Teams that ship AI products do not have a secret interview. The ones that hire well do a few ordinary things with discipline: a narrow role, a short list of people who have done similar work, a structured screen, and a decision in days rather than months.

  • How to spot fake job applicants

    A fake applicant is a person, or a stack of generated text, that will not survive a real conversation about the work. AI-written resumes and prompt injection make the paper look fluent. They do not make the work history real. You can catch most of this before you spend an interview.

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