Mohammed Bukhari

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SCET

A clear glass light bulb with a threaded brass base, its filament lit.

SCET is UC Berkeley’s largest entrepreneurship center.

As its AI product manager, I built lead scoring, AI outreach and attribution for $50K in ad spend.

SCET now scores its program pages with the AI-search framework I created.

Role
AI product manager
Team
SCET’s marketing and programs team; in Riyadh, Gigi Wang, Noor Masri and me
When
Operations from June 2025, product manager since September 2025
Result
My AI-search framework is SCET’s standard for scoring program pages

Status In use at SCET. The Riyadh bootcamp ran in August 2026.

Context

SCET, the Sutardja Center for Entrepreneurship & Technology, is UC Berkeley’s largest entrepreneurship center, at the world’s top university for startup founders. Founded in 2005 in Berkeley’s College of Engineering, it teaches entrepreneurship to students and runs programs for universities and executives around the world.

I joined in operations in June 2025, as an intern: I standardized intern onboarding, training and operational documentation, and automated recurring administrative and coordination workflows. In September 2025 I became its AI product manager. My job is to make sure the right people hear about SCET’s programs, and to prove what brings them in.

UC Berkeley's Sather Tower in daylight, rising above a lawn and trees under a clear blue sky.

A lead engine

A program team’s time is best spent on the people most likely to say yes, so the first job was finding them.

  • Lead and email automations. I built lead and email automations with API integrations and LLM-powered personalization, supporting enrollment across concurrent SCET programs.

  • Lead scoring. I built a lead scoring and routing system in HubSpot that narrows hundreds of contacts to a short list of qualified prospects, so sales calls go to high-intent leads rather than the whole list.

  • Lead quality. Low-intent ad submissions were cluttering the lead forms and inflating the pipeline. I diagnosed them and fixed how they were scored, so sales sees real prospects rather than form noise.

Schematic. Counts are not to scale.

  • A contact
  • A qualified prospect
A lead engineSchematic: a field of hundreds of contacts passes through a scoring gate, is routed, low-intent form submissions are scored down and leave the line, and a short list of qualified prospects continues to the sales calls.A lead engineSchematic: a field of hundreds of contacts passes through a scoring gate, is routed, low-intent form submissions are scored down and leave the line, and a short list of qualified prospects continues to the sales calls.

Outreach, one to one

The goal: outreach that reads as personal, at a scale no one could research by hand.

  • Executives. I ran outreach to Fortune 500 CEOs for Berkeley’s AI Leadership Accelerator, an executive program for C-suite leaders, so the program opened conversations directly with decision-makers rather than through layers of staff.

  • Partners. I built an AI enrichment pipeline that researched and verified partner contacts for a new program, so every email was personalized on checked facts rather than guesswork.

  • LinkedIn. I designed an AI-assisted outreach system with personalized, multi-touch follow-ups, so outreach reads as one-to-one rather than a mass sequence.

Schematic, drawn for this site.

  • A step
  • The person it reaches
Outreach, one to oneSchematic of three outreach lanes. Executives: the line runs straight through the layers of staff to the decision-maker. Partners: research, then verification, then one personalized email on checked facts. LinkedIn: a first message and personalized follow-ups, each to one person.Outreach, one to oneSchematic of three outreach lanes. Executives: the line runs straight through the layers of staff to the decision-maker. Partners: research, then verification, then one personalized email on checked facts. LinkedIn: a first message and personalized follow-ups, each to one person.

Proof, not guesswork

It started with one question: where had a program’s enrollees come from? Tracing each enrollment’s first and last touch in the CRM showed that about half had come straight in through LinkedIn sign-up forms. From there, I built the tools that show what works.

  • Attribution. I built attribution across Google, Meta, LinkedIn and organic channels for $50K in ad spend, translating campaign performance into budget allocation decisions, and a model that shows the return on ad spend of executive education partnerships, so leadership can fund partnerships on proven return rather than lead volume. It showed a 12.3x return on ad spend.

  • SEO and AI search. I created the SEO and AI-search audit framework SCET now uses as its standard for scoring program pages, so pages get found by AI assistants as well as Google rather than tuned one at a time.

  • Website audit. I ran an accessibility and content audit across the SCET website ahead of a compliance deadline, so fixes were ready in batches rather than handled page by page.

Schematic, drawn for this site.

  1. 1 Attribution

    Each enrollment traced from first touch to last, so ad spend can be set against the return it brought in.

    Return on ad spend12.3x

  2. 2 SEO and AI search

    One framework scores every program page for Google and for AI assistants. It is now SCET’s standard.

  3. 3 Website audit

    Accessibility and content checked across the site, with the fixes grouped in batches before the compliance deadline.

Programs, Riyadh to Silicon Valley

With Gigi Wang leading the program, we brought a five-day UC Berkeley entrepreneurship bootcamp to Prince Sultan University. It began in September 2025 with eleven questions from the host, which we answered within three days.

From the signed contract through speaker outreach, bilingual materials in Arabic and English, and logistics, I helped coordinate the week, so it opened with a signed partner and its speakers and judges in place. It ran from August 2 to 6, 2026, the first time the host had offered it, and seven student teams pitched their startups to a judging panel. I was in Riyadh for the week. It was the first UC Berkeley bootcamp hosted by a university in Saudi Arabia.

Closer to home, I sourced AI speakers for a national bank’s Silicon Valley executive tour, matching each one to the client’s real problems, so the agenda was practical rather than generic AI talks.

Across these programs I have worked on about 12 partnerships, on projects that received $100K+ in payments.

Eleven questions

  1. 1What does the price cover?
  2. 2Who would teach?
  3. 3How would five days run?
  4. 4How many students per instructor?
  5. 5What happens on the last day?
  6. 6Do students get a certificate?
  7. 7What happens after the week?
  8. 8What materials come with it?
  9. 9How many students can join?
  10. 10What does the faculty lead do?
  11. 11What would cost extra?

Five days

  1. Day 1
  2. Day 2
  3. Day 3
  4. Day 4
  5. Pitch day
The Riyadh bootcamp, drawn for this site. The questions are paraphrased, and the week is a simplified schedule, not the exact agenda.

Schematic, drawn for this site.

Programs, Riyadh to Silicon ValleySchematic of two lanes. Riyadh: eleven questions in September 2025, then the signed contract, speakers and judges, bilingual materials, logistics, the week of August 2 to 6, 2026, and pitch day with seven teams. Silicon Valley: a bank’s real problems matched one to one with AI speakers into a practical agenda.Programs, Riyadh to Silicon ValleySchematic of two lanes. Riyadh: eleven questions in September 2025, then the signed contract, speakers and judges, bilingual materials, logistics, the week of August 2 to 6, 2026, and pitch day with seven teams. Silicon Valley: a bank’s real problems matched one to one with AI speakers into a practical agenda.

The dated stops are the case’s own facts. The steps between them are evenly spaced, not to a calendar, and the problems, speakers and sessions are counts for the drawing only.

Outcome

SCET now uses my SEO and AI-search framework as its standard for scoring program pages.

  • Attribution across Google, Meta, LinkedIn and organic channels for $50K in ad spend.

    SourceMohammed Bukhari’s résumé, October 2026

  • About 12 partnerships, on projects that received $100K+ in payments.

    SourceMohammed Bukhari’s résumé, October 2026

  • The bootcamp ran in Riyadh, August 2–6, 2026. It was the first time the host university had offered it.

    SourceHost university’s thank-you email to the Berkeley program team, August 9, 2026

  • Seven student teams pitched their startups on the last afternoon.

    SourceLead instructor’s pitch-day schedule, August 5, 2026 (seven teams listed)

  • The first UC Berkeley bootcamp hosted by a university in Saudi Arabia.

    SourceMohammed Bukhari, October 6, 2026

What’s next

Talks about a bootcamp have started with two more universities in Saudi Arabia. Nothing is planned yet, and the lead instructor has asked whether Noor Masri and I can help again.

Credits

Organization
Sutardja Center for Entrepreneurship & Technology (SCET), UC Berkeley
Built with
HubSpot, API integrations and LLM-powered personalization for research, enrichment and outreach
Riyadh team
Gigi Wang (SCET faculty, who designed, led and taught the program), Noor Masri and me
Riyadh host
Prince Sultan University, International Affairs Office