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Broadcom Engineering

To build cutting-edge infrastructure technologies by powering cloud, enterprise and AI innovation through semiconductor and software excellence

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To build cutting-edge infrastructure technologies by powering cloud, enterprise and AI innovation through semiconductor and software excellence

Strengths

  • PORTFOLIO: Diverse product portfolio spanning hardware and software
  • FINANCIALS: Strong cash flow generation with 60%+ operating margin
  • CUSTOMERS: Deep relationships with leading technology enterprises
  • ACQUISITION: Proven track record of successful M&A integration
  • TALENT: World-class engineering talent with specialized expertise

Weaknesses

  • INTEGRATION: VMware acquisition complexity straining resources
  • TECHNICAL-DEBT: Legacy systems requiring modernization
  • AGILITY: Engineering processes slower than cloud-native competitors
  • TALENT: Skill gaps in emerging AI technologies and frameworks
  • ARCHITECTURE: Siloed technology stacks limiting cross-product synergy

Opportunities

  • AI: Explosive growth in AI infrastructure demand across cloud/edge
  • CLOUD: Hybrid cloud adoption driving infrastructure upgrades
  • SECURITY: Growing demand for integrated security solutions
  • EDGE: Expansion of edge computing requiring specialized solutions
  • SYNERGY: VMware integration enabling new product combinations

Threats

  • COMPETITION: NVIDIA dominance in AI accelerator market
  • REGULATION: Increased scrutiny of technology acquisitions
  • TALENT: Fierce competition for AI and cloud engineering talent
  • ECONOMIC: Potential enterprise spending slowdown affecting budgets
  • INNOVATION: Rapid pace of AI advancements requiring quick pivots

Key Priorities

  • AI-FIRST: Accelerate AI-optimized infrastructure development
  • INTEGRATION: Seamlessly combine VMware assets with existing stack
  • MODERNIZATION: Update engineering practices for cloud-native era
  • SECURITY: Build integrated security across the technology stack
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To build cutting-edge infrastructure technologies by powering cloud, enterprise and AI innovation through semiconductor and software excellence

AI ACCELERATION

Become the leading AI infrastructure platform provider

  • SILICON: Launch next-gen AI-optimized networking chips with 2x performance gain by Q4 2025
  • PLATFORM: Integrate VMware/Broadcom ML Ops platform used by 1000+ customers by Q3 2025
  • ECOSYSTEM: Establish 25+ AI infrastructure partnerships across cloud providers & startups
  • ADOPTION: Achieve $1B in revenue from AI-specific infrastructure products and solutions
SEAMLESS INTEGRATION

Create unified technology stack from all acquisitions

  • PLATFORM: Launch unified engineering platform used by 90% of teams across all divisions
  • ARCHITECTURE: Complete reference architecture connecting all major product lines by Q3
  • API: Publish comprehensive API gateway for all Broadcom+VMware services with 95% coverage
  • EFFICIENCY: Realize $500M in engineering cost synergies through platform consolidation
CLOUD NATIVE

Transform engineering for cloud-first development

  • DEVOPS: Implement CI/CD pipelines with 95% automation across all engineering teams by Q3
  • MICROSERVICES: Refactor 75% of core applications to microservices architecture by Q4
  • CONTAINERS: Containerize 90% of enterprise software offerings for hybrid cloud deployment
  • TALENT: Train 5,000 engineers on cloud-native development practices by end of Q2 2025
SECURE FOUNDATION

Build security into every product from the ground up

  • DEVSECOPS: Integrate automated security testing in 100% of CI/CD pipelines by Q2 2025
  • ZERO-TRUST: Implement zero-trust architecture across all products with 100% compliance
  • COMPLIANCE: Achieve SOC2, FedRAMP High & ISO 27001 certification for all cloud services
  • AI-SECURITY: Deploy AI-based threat detection with 99.5% accuracy in security products
METRICS
  • REVENUE GROWTH: 10-12% YoY by Q4 2025
  • AI REVENUE: $1B from AI-specific infrastructure solutions
  • ENGINEERING VELOCITY: 2x increase in feature delivery speed
VALUES
  • Innovation with purpose
  • Customer-first mindset
  • Execution excellence
  • Integrity and accountability
  • Collaboration across boundaries
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Align the learnings

Broadcom Engineering Retrospective

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To build cutting-edge infrastructure technologies by powering cloud, enterprise and AI innovation through semiconductor and software excellence

What Went Well

  • REVENUE: Q1 2024 revenue reached $11.96B, exceeding market estimates
  • VMWARE: Initial VMware integration proceeding according to timeline
  • MARGINS: Maintained impressive 60%+ operating margins despite market
  • CUSTOMERS: Retention of 95%+ of VMware enterprise customer accounts
  • NETWORKING: Strong demand for networking solutions in AI deployments

Not So Well

  • GUIDANCE: Forward guidance below analyst expectations for next qtr
  • COMPETITION: Lost AI accelerator market share to NVIDIA and others
  • INTEGRATION: Challenges in harmonizing engineering teams post-merger
  • INNOVATION: Some product roadmaps delayed due to resource allocation
  • TALENT: Higher than expected attrition in key engineering positions

Learnings

  • SPEED: Need to accelerate decision-making in engineering leadership
  • FOCUS: Clear prioritization of AI initiatives required across teams
  • SYSTEMS: Improved integration between acquired engineering systems
  • FEEDBACK: Better customer feedback loops needed for emerging needs
  • CLOUD: Cloud-native transformation must be accelerated post-merger

Action Items

  • PLATFORM: Develop unified engineering platform across all divisions
  • TALENT: Launch aggressive AI engineering recruitment & training program
  • ROADMAP: Create integrated product roadmap for AI infrastructure stack
  • PROCESS: Implement agile engineering practices across all teams
  • INVESTMENT: Reallocate 25% of R&D budget to AI-focused initiatives
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To build cutting-edge infrastructure technologies by powering cloud, enterprise and AI innovation through semiconductor and software excellence

Strengths

  • SILICON: Custom silicon design expertise applicable to AI workloads
  • DATA: Access to vast customer deployment data for AI training
  • ECOSYSTEM: Broad customer base for rapid AI solution deployment
  • CAPITAL: Financial resources to invest heavily in AI capabilities
  • NETWORKING: AI-optimized networking technologies for data centers

Weaknesses

  • TALENT: Limited specialized AI research engineering talent
  • FOCUS: Resources divided between legacy maintenance and AI R&D
  • FRAMEWORKS: Lack of proprietary AI development frameworks
  • CULTURE: Engineering culture not fully embracing AI-first approach
  • COMPETITION: Late entry compared to cloud hyperscalers

Opportunities

  • ACCELERATION: AI-optimized silicon for specialized workloads
  • OBSERVABILITY: AI-powered monitoring and management solutions
  • AUTOMATION: Infrastructure automation using AI for optimization
  • SECURITY: AI-enhanced threat detection and prevention
  • INTEGRATION: AI-driven integration between VMware and core products

Threats

  • PACE: Rapid evolution of AI technology requiring constant updates
  • PLATFORM: Hyperscalers creating end-to-end AI stacks
  • TALENT: Aggressive recruitment of AI engineering talent
  • INNOVATION: Open-source AI advances disrupting proprietary models
  • INVESTMENT: Competitors making multi-billion dollar AI investments

Key Priorities

  • AI-SILICON: Develop specialized AI accelerator chips and systems
  • AI-PLATFORM: Create unified AI development environment for products
  • AI-OPERATIONS: Apply AI to infrastructure management and security
  • AI-TALENT: Aggressively recruit and develop AI engineering expertise