High-density technical training

Electi Foundation.

Foundation is not a "course." It is a structured environment for engineers who prioritize technical depth and long-term consistency.

Small-Group Workshops

Limited to 8 peers per group. Weekly sessions focused on deep-dive pattern recognition and live execution with FAANG software engineers. 10 core workshops in the first 6 months.

Performance Tracking

A proprietary system to benchmark your technical proficiency. Track your solving velocity, identify pattern gaps, and measure your progress toward interview readiness in real-time.

Staff-Level Curriculum

The exact internal roadmaps used in our Accelerator. From advanced Graph Theory to System Design for distributed environments.

The Repository

A private collection of solved tasks and architectural breakdowns. Focus on engineering logic, not just solutions.

Direct Path to Accelerator

Foundation serves as our internal vetting ground. High-performers receive priority placement and fast-track onboarding for 1:1 mentorship.

Engineering Pedigree

Learn from those who have successfully cleared the loops at the world's most competitive firms.

Vladimir

Vladimir

Backend Engineer @Meta

London, UK

Ex-AmazonEx-The Trade Desk

Backend engineer specializing in low-latency systems and performance optimization. At The Trade Desk, he worked on bidding algorithms at 10M+ QPS, designed services processing hundreds of TBs daily, and drove infra cost reduction through low-level optimizations. Previously at Amazon improving availability of high-throughput Prime Video services.

Sultan

Sultan

Software Engineer @Meta

London, UK

Bloomberg LondonBloomberg NYGoogle Kraków

Full-stack engineer with a textbook Big Tech arc: rejected by Meta and Yandex in Year 1, he doubled down on algorithms and LeetCode. Within a year: Bloomberg London → Bloomberg NY → Google Kraków → offers from Meta, Google, and Bloomberg — all in London.

I wasn't an olympiad winner, didn't get straight A's, and wasn't the smartest. But at some point I had a strong desire to become better. I put in a lot of effort and that opened many doors.
Timur

Timur

Engineering Manager @Google

London, UK

Ex-MetaEx-Booking.com

Leads a mobile product team at Google London. Each career move — from Booking.com to Meta to Google — was a deliberate bet on growth. Chose London for its dense tech ecosystem and the calibre of engineers around him.

Preparation should become a habit. What matters most is the candidate's inner drive to constantly improve.
2 active FAANG-tier interviews

Real progress. In their own words.

Messages from students currently in the program.

Before this I could barely solve algorithm problems, my background was mostly ML and SQL. Now I'm getting through every topic we cover. The mock interview part especially. And I manage to combine it with full-time work.

Shokhrukh

Foundation · Month 2

If you already know some DSA it moves fast, which is good. The only hard part is finding time when you work and study simultaneously. But the intensity, that's exactly the point.

Yernur

Foundation student

Main thing I'm realizing: I need to stop relying on test runs to debug, interviews don't allow that. Mentor caught that gap before I even noticed it. Algorithm stage feels close to handled now.

Galym

Accelerator student

Netflix Interview · Revolut Interview

3 months in and I'm already in interview loops at Netflix and Revolut. First time doing a FAANG-style interview. My mentor called the exact problem that came up in the coding round. I just executed what we practiced.

R

Roma

Accelerator · Month 3

Infrastructure for growth.

We provide the system. You provide the execution.

Peer-to-Peer Network

A private community of highly motivated engineers. Collaborative problem solving and collective intelligence.

Career Architecture

Professional resume deconstruction, LinkedIn optimization, and direct referral network access.

Placement Support

Access to our network of mentors and alumni at top-tier firms. We help you get your profile in front of the right people.

Foundation Roadmap

A structured 7-month path from algorithms to placement-ready.

1

Months 1–5

Phase 1: Technical Foundation

21 weeks of structured DSA. You don't just solve problems — you master the patterns.

  • Topics: Arrays, Hashing, Linked Lists, Stacks & Queues, Trees & Graphs, Heaps, Greedy, Binary Search, Backtracking, Dynamic Programming.
  • Weekly routine: 15–20 LeetCode problems focused on the current topic. Peer-to-peer mocks every 2 weeks.
2

Month 6

Phase 2: Behavioral & Placement Strategy

Your story matters as much as your code. We craft your resume, strategy, and STAR stories.

  • Focus: ATS resume rewrite, application strategy, 5–10 STAR leadership stories.
  • Milestone: Peer-to-peer mock interviews with written feedback.
3

Month 7

Phase 3: System Design

Learn to design scalable distributed systems from first principles.

  • Focus: Vertical vs. Horizontal scaling, Load Balancers, Caching, Databases.
  • Cases: Design a URL shortener or a Messenger API.

Your career, in numbers

See how your preparation pays off in your first year after getting hired.

Using default $10,800/yr (approx $900/mo)

You invest$17,548total
First-year salary increase+$149,200
Your net upside
+$131,652
After deducting all training costs

Estimates are based on public market salary data and typical preparation timelines. Your actual result depends on your experience and effort.

Simple, performance-based pricing.

We invest in your career trajectory. Our model is built on mutual success.

Foundation

Popular choice for building confidence & core skills.

$129/mo

+10% Success Fee.

Limited to 8 spots per group to maintain high-signal workshops.

  • 1 workshop per week with material deep dives
  • Bi-weekly personal written feedback from your dedicated mentor
  • Access to private Electi community & mentor group chat
  • Behavioral interview preparation
  • Job application support & referrals

How Success Fee works

Success Fee means we win only when you win.

You pay a percentage of your first-year salary only after you accept a job offer.

This model ensures our goals are perfectly aligned. We invest in your potential, and we only see a return when you succeed.

Why we use this model

  • It lowers your upfront cost
  • It aligns our incentives with your result
  • Train with top mentors without full price

How it works

1

You prepare with mentors

2

You get an offer

3

Pay only after signing

No payments if

  • You do not get hired
  • You stop before reaching interviews

You choose how to pay

  • Low monthly payment + Success Fee
  • Higher monthly payment + 0% Success Fee
Same mentorship. Different payment timing.

FAQ