Stanford Graduate School of BusinessApplication Week 2026: Letters of Recommendation (For Applicants)
Stanford Graduate School of Business
Recapping Application Week Questions 0:00
The session opens by revisiting questions submitted earlier in application week. Cecilia had worried that her example, drawn from communicating with teammates on her volleyball team, felt too small compared to something more impressive. The response is that the point isn't the scale of the example but the practice of recalling, reflecting, processing, and connecting patterns of behavior, since those same skills can later be deployed in the admissions journey.
Dark Past, Bright Future 2:30
Sneigha's question asked whether a difficult or "dark" past could still indicate a bright future, not just a positive one. The answer draws on social cognitive career theory, which links background, learning experiences, beliefs about capability, and outcomes into goals and actions. Challenging or formative experiences are valid material for an application as long as they help the reader learn who you are and how they shape your trajectory, without needing to be shared as a trauma dump.
One Example or Several 4:32
Sylvia asked whether behavioral questions should be answered with one strong example or several. The advice is to prepare multiple examples during reflection to build familiarity and rapid recall, but when actually answering, to focus on directly answering the question asked rather than forcing an anecdote to prove a specific skill. The Stanford GSB application allows up to three examples, and interview questions may call for a more targeted single story.
Where Recommendations Fit 7:01
The agenda shifts to letters of recommendation, split into a segment for applicants and a separate recorded segment for recommenders that applicants can share. The admissions process is described as holistic, with no minimums, formulas, quotas, or benchmarks. Every part of the application, including recommendations, is treated as equally important, and context such as school or employer is used only to understand, not to judge, the applicant. What admissions looks for is how you think, how you lead, and how you see the world, with clarity of purpose mattering especially for the one-year MSx program.
People Who Shape Your Journey 11:01
Before getting tactical, the discussion reframes recommenders as long-term partners rather than a transactional checkbox. Mentors, role models, sponsors, advocates, and sounding boards can help you see yourself differently, much like personal relationships do earlier in life. Resources from Stanford's Life Design Lab, an informational interview video and a networking reframe video, are shared to help applicants build these relationships through curiosity rather than forced networking, so that asking for a recommendation later feels natural.
What Recommenders Are Asked 14:30
Recommenders answer three open-ended questions: how the applicant performed relative to equally qualified peers, a time involving feedback and the applicant's response, and anything else worth knowing. These questions are not Stanford-specific, since recommenders often write for multiple schools. Procedurally, applicants submit recommender information early, the recommender receives instructions and a portal, and fills out short relationship questions, a leadership competency ratings form, and a document upload, all completed independently by the recommender.
Choosing the Right Two People 18:30
Two letters are required: ideally a current direct supervisor or the next best alternative, plus another person who has supervised the applicant. The "next best alternative" option exists because a current supervisor may not be supportive or aware of a job search. Supervisors are preferred because they can speak to performance relative to peers and to feedback within an organizational setting.
Frequently Asked Recommender Questions 20:30
A rapid set of questions addresses common concerns. A professor can work if they've seen you in an organizational, not just academic, setting. Family members should be avoided due to bias, even though personal endorsements from familiar people often lack concrete behavioral detail. Seniority or title of the recommender doesn't matter more than their ability to give specific examples, and a recommender's Stanford connection carries no extra weight. A new supervisor is acceptable, and applicants can indicate in the application that they aren't using their current direct supervisor. Recommenders from years past can still work if they've stayed connected to your recent growth, and any unusual or complicated situations can be explained in the additional information section.
Preparing Your Recommenders 25:00
Applicants are pointed to the letters of recommendation webpage, a recommender information page, and a new downloadable resource with guiding questions like identifying moments of going above and beyond. Talking with recommenders about accomplishments and expectations is encouraged, but applicants are reminded to judge for themselves what conversations are appropriate given workplace norms and personal comfort, while sharing helpful tools and resources, especially if it's the recommender's first time writing this kind of letter.
Avoid over-directing recommenders 28:01
Telling a recommender exactly what to write about can backfire, since it may cause them to stick closely to your suggested points and leave out other observations or context about you that would actually be valuable.
Share values, not scripts 28:32
Instead of dictating topics, help recommenders understand what the admissions team values, such as how you think, lead, and see the world, and let them choose their own examples to illustrate it, including any feedback that supports your growth.
Trust the relationship and yourself 29:01
The letter should remain the recommender's own work, and any questions can be emailed to the admissions team. Requesting a recommendation can honor and even strengthen your relationships, since inviting someone into this process is a form of mutual trust, and you are told simply to trust yourself.
AI-generated summary. It can be wrong or incomplete - check anything that matters against the original.
