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Calibrating in Tezi

Process and best practices for calibrating in Tezi

Updated over a month ago

Calibrating Tezi well is essential for effective sourcing and inbound screening. Depending on the role, calibration may take anywhere from 15 minutes to 2-3 hours over multiple sessions. This investment enables Tezi to automate recruiting at scale, ultimately returning significantly more time to you and helping you hire faster.

Pre-work


Before starting calibration in Tezi, determine the basics of your target candidate profile. We recommend capturing your criteria in the following format:

  • Located in [one of the following US states: California, Washington,...]

  • Currently holds one of the following job titles: [SWE, Software Engineer, Frontend Engineer, Fullstack Engineer, Software Developer, Frontend Developer, Fullstack Developer, Member of Technical Staff, Founding Engineer]

  • Min [3] years of experience

  • Max [10] years of experience

  • Currently or previously worked at one of the following companies: [seed through Series C companies]

  • Attended one of the following schools: [top 30 universities and top 30 liberal arts colleges in the United States]

  • Has one of the following keywords: [AI, GenAI]

  • Has never held one of the following job titles: [Founder, Cofounder, Manager, Director, VP, Vice President, Head of, CTO, Chief Technology Officer]

This basic format works well for the majority of roles. Feel free to add or remove criteria as needed to fit your specific needs.

💡 Tips

  1. We recommend building a thorough list of relevant job titles upfront. This helps ensure that you do not miss out on any relevant candidates.
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  2. Company and school lists can be highly effective for zeroing in on the most relevant candidates, so we recommend testing one or more lists in your search.

    1. Tezi's system can automatically generate basic company and university lists with guidance from you, e.g., Klaviyo, Ramp, Deel, and 30 similar B2B companies, top 20 computer science universities in the United States, etc. For more advanced lists (e.g., all 2020-2023 YCombinator companies), provide an explicit list.
      ​

  3. For job titles, companies, and keywords, Tezi's system performs partial exact matches. This means that, when you enter a phrase like “software engineer,” the system will return candidates who have that exact phrase in their job title, even if it appears within a longer title. "Senior software engineer" and "software engineer, machine learning" will match, while "SWE" will not.

Calibration

  1. Navigate to the Tezi calibration page for your role.
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  2. Add the criteria from your pre-work to the appropriate section of the page.

    1. Inbound and Sourcing Criteria: these criteria will be applied by Max in both inbound screening and sourcing

    2. Additional Sourcing Criteria: these criteria will be applied by Max in sourcing only
      ​

  3. Carefully observe how Tezi's system interprets each criterion. Correct any misinterpretations or make any other modifications as needed.
    ​

  4. Review the candidates returned. We recommend reviewing at least 5-10 candidates in each iteration of criteria.

    1. Poor fits: Are there any themes to the poor fits?

    2. Good fits: Do the strong candidates have any job titles, past companies, schools, etc. that are worth adding to the criteria to expand the pool?

  5. Based on any themes you observe, iterate on the criteria to refine the candidates returned.

Calibration results are representative of who Max will source. Therefore, we recommend reviewing at least 10 profiles before finalizing criteria.

After you have completed initial calibration, you may want to recalibrate in the future as you learn more about your target profile (e.g., from candidates' interview performance) or when Max runs out sourcing pool. While a role is live, it is typical to revisit calibration every 1-3 weeks.

💡 Tips

  1. All criteria are treated as requirements. Tezi's system does not support preferences. This helps provide more predictability in candidate quality.
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  2. The number on the right side of each row indicates how many candidates meet all criteria up to and including the requirement in that row. The circle icon visually indicates the percent drop-off from that row's criterion, relative to the prior steps, similar to a pie chart.
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  3. To evaluate whether a criterion is improving results, try implementing the opposite criterion to see who is being excluded and whether that exclusion makes sense. For example, if you have a criterion like Has a degree in Computer Science, consider testing Does not have a degree in Computer Science.

Supported criteria types

Logical operators

  1. And/all

    1. Has all of the following skills: React, TypeScript, and Python

  2. Or/one of

    1. Has experience in one of the following industries: Management Consulting, Investment Banking

    2. One of the following conditions much be true, OR them together - (Skills include enterprise, b2b, b2b3c - do not expand) OR (Current/Previous company includes Notion, Asana, Stripe, Slack - do not expand) OR (Candidate went to a top 10 university in the US)

  3. Not/never

    1. Has never held one of the following titles: Manager, Director

  4. If/then

    1. If the candidate did not attend a top 20 university in the US, then they must have a degree in computer science or computer engineering

  5. Current or previous

    1. Currently at a Seed-stage company

    2. Currently or previously at a Seed-stage company

    3. Previously at a Seed-stage company

  6. AI-generated lists

    1. Candidate must have attended a top 50 university or top 50 liberal arts college in the United States

    2. Candidate must be skilled in AWS, GCP, or similar cloud platforms

Work experience

  1. Job titles

    1. Candidate must be a Senior Software Engineer

    2. Note: Tezi's system performs partial exact matches. This means that, when you enter a phrase like “software engineer,” the system will return candidates who have that exact phrase in their job title, even if it appears within a longer title. "Senior software engineer" and "software engineer, machine learning" will match, while "SWE" will not.

  2. Seniority level (only supports most recent experience)

    1. Candidate must be at least a Senior level

  3. Managerial role

    1. Candidate must have management experience

  4. Executive role

    1. Candidate must be an executive

  5. Internship position

    1. Candidate must have interned at Google

  6. Company name

    1. Candidate must have worked at Google or Microsoft

  7. Company industry

    1. Candidate must have experience in the technology industry

  8. Company size

    1. Candidate must have worked at a company with 1000+ employees

  9. Company country

    1. Candidate must have worked in the United States

  10. Company funding stage

    1. Candidate must have experience at a Series A startup

  11. Start and end dates

    1. Candidate must have worked at McKinsey, BCG, or Bain with an end date before 2024

Education

  1. Degrees

    1. Candidate must have a Bachelor's degree

  2. Majors

    1. Candidate must have a degree in computer science

  3. School name

    1. Candidate must have attended one of the following universities: UC Berkeley, UCLA

  4. School country

    1. Candidate must have attended university in the UK

  5. Education dates

    1. Candidate must have graduated between 2010 and 2018

Location

  1. City

    1. Located in New York City, Boston, Philadelphia, or Washington DC

  2. State

    1. Not located in California or New York

  3. Country

    1. Located in Germany, France, or the UK

Tenure

  1. Total experience

    1. Min 2 years of total experience

  2. Minimum tenure

    1. Min 2 years of tenure in every role they've held

  3. Average tenure

    1. Min 3 years of tenure on average

  4. Tenure at most recent experience

    1. Max 5 years of tenure at their current company

Skills or keywords

  1. Skills or keywords that appear in their skills or experience summaries

    1. Has experience with Python or JavaScript

    2. Has one of the following keywords: 0->1, founding

Promotions

  1. Candidates who have been promoted

    1. Candidate must show a strong promotion trajectory

Examples of successful criteria

Early-Career Machine Learning Engineer

Early-career machine learning engineers with a strong academic foundation

  1. Located in San Francisco, Los Angeles, or Seattle

  2. (Has held one of the following titles: Machine Learning Engineer; ML Engineer; MLE; AI Engineer; Deep Learning Engineer; Applied Scientist; Artificial Intelligence Engineer; Software Engineer, Machine Learning; Software Engineer, ML; Research Engineer) OR (Has skills in DeepSeek R1, Claude, Langgraph, Cursor, RAG systems, Reasoning trace, Structured outputs, MCP, Chain-of-thought, Prompt caching, TPM limits, Langchain)

  3. Attended one of the following universities: Harvard University, Stanford University, Massachusetts Institute of Technology, Princeton University, Yale University, Columbia University, University of Chicago, University of Pennsylvania, California Institute of Technology, Duke University, Northwestern University, Brown University, Cornell University, Johns Hopkins University, Carnegie Mellon University, University of Southern California, University of California, Berkeley, University of Illinois, Urbana Champaign, University of Texas, Austin, University of Washington, University of Michigan, University of California, San Diego, University of Toronto, University of British Columbia, McGill University, University of Oxford, University of Cambridge, Imperial College London, University College London, IIT Bombay, IIT Delhi, IIT Madras, IIT Kanpur, or IIT Kharagpur

  4. Previously held one of the following titles: Teaching Assistant, Research Assistant, Researcher

  5. Up to 5 years of experience

  6. Has a Bachelor's or Master's degree in Computer Science

Product Design Leader

Software product design leaders at companies with a high design bar

  1. Located in California

  2. Currently holds the title Staff Product Designer, Principal Product Designer, Product Design Manager, Design Manager, Product Design Lead, Head of Design, Director of Design, Director of Product Design, or Head of Product Design at one of Airbnb, Airtable, Amazon, Asana, Brex, Bumble, Calm, Canva, Carta, Chime, Coinbase, DoorDash, Dropbox, Duolingo, Etsy, Eventbrite, Facebook, Faire, Figma, Google, Grubhub, Gusto, Harvey, Headspace, Hinge, Houzz, Instagram, Instacart, Kickstarter, Linear, Loom, Lyft, Mercury, Meta, Microsoft, Miro, Netflix, Nextdoor, OpenAI, OpenTable, Patreon, Peloton, Perplexity, Quora, Ramp, Reddit, Rippling, Roblox, Robinhood, Shopify, Slack, Snapchat, Spotify, Square, StitchFix, Stripe, SuperHuman, The Browser Company, TikTok, Tinder, Turo, Twitter, Uber, Venmo, WeWork, WhatsApp, Yelp, YouTube, Zillow, or Zoom

  3. At least 9 months of tenure in current role

  4. Profile does not mention the following keywords: "mechanical", "hardware"

Early-Career Business Operations

Candidates with consulting internship experience and who are not currently in finance

  1. Located in the United States

  2. Completed undergraduate degree at an Ivy League university between 2020 and 2023

  3. Interned at McKinsey, BCG, or Bain

  4. Not currently working at McKinsey, BCG, or Bain

  5. Not currently working in any of the following industries: Management Consulting, Investment Banking, Investment Management, Venture Capital and Private Equity

Mid-Career Software Engineer

Software engineers with early-stage startup experience

  1. Located in Seattle

  2. Currently holds one of the following job titles: Software Engineer, SWE, Backend Engineer, Back End Engineer, Fullstack Engineer, Full Stack Engineer, Frontend Engineer, Front End Engineer, Founding Engineer, Member of Technical Staff, Developer, Platform Engineer

  3. Bachelor's or Master's degree in Computer Science or Computer Engineering

  4. Total experience is between 3 and 8 years

  5. Earned a Bachelor's degree between 2019 and 2023

  6. Has experience at a Seed through Series B company

Senior Accounting Professional

Senior accounting professionals with experience in K-12 schools

  1. Located in the US

  2. Has never held a CFO or Chief Financial Officer role

  3. Current job title is one of the following: Controller, Director of Finance, Finance Director, Treasurer, Accounting Manager

  4. Previously held one of the following titles: Senior Accountant, Staff Accountant, Accounting Manager, Audit Associate, Accountant, or Auditor

  5. Latest experience duration is at most 5 years

  6. Most recently worked at Academy, High School, School District, Private School, or Independent School

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