The Build vs. Buy Decision for AI Infrastructure

The AI Infrastructure Stack

When people say "AI infrastructure," they usually mean:

Layer 5: Application (Your product)
Layer 4: Agent Orchestration (Workflows, multi-step reasoning)
Layer 3: Context Layer (RAG, retrieval, structured knowledge)
Layer 2: Model Access (API wrappers, model routing)
Layer 1: Foundation Models (GPT, Claude, open source)

Most build vs. buy decisions are about Layers 2-4.
Layer 1: Almost always buy (few train their own LLMs)
Layer 5: Almost always build (it's your product)

The Decision Framework

Build If:

• It's your core differentiator. If AI infrastructure IS your product, you probably need to build it.
• Existing solutions don't fit. Your use case is genuinely unique and can't be adapted.
• You have the team. ML engineers who want to work on infra, not just product.
• You have the time. 6-12 months before you need production-ready AI.
• Control is critical. Regulatory, security, or performance requirements that vendors can't meet.

Buy If:

• AI is a feature, not the product. Your value is in the application layer, not the infrastructure.
• Speed matters more than control. Need to ship AI features in weeks, not quarters.
• Your team is product-focused. Engineers want to build features, not maintain infra.
• Standard use cases. RAG, context retrieval, basic agents—these are solved problems.

Layer-by-Layer Analysis

Layer 2: Model Access

// Build
const response = await openai.chat.completions.create({
  model: "gpt-4",
  messages: [{ role: "user", content: prompt }]
})

// Verdict: Almost always build this yourself.
// It's just API calls. Simple abstraction layer.
// Time to build: 1-2 days for basics, 1-2 weeks for robust.

Layer 3: Context Layer

// Build: Custom RAG pipeline
class ContextPipeline {
  async embed(text) { ... }        // Vector embeddings
  async store(embedding) { ... }   // Vector database
  async retrieve(query) { ... }    // Similarity search
  async rerank(results) { ... }    // Quality filtering
}

// Time to build: 2-3 months for production-ready
// Ongoing: Continuous optimization, tuning, monitoring

// Buy: Use a context platform
const context = await xtended.retrieve(query, { table: "customers" })

// Time to integrate: 1-2 weeks
// Ongoing: Platform handles optimization

This is where the decision matters most. Context layer is:

• Complex to get right (chunking, embedding, retrieval quality)
• Requires ongoing optimization
• Not usually your core differentiator

Layer 4: Agent Orchestration

// Build: Custom agent framework
class Agent {
  async plan(task) { ... }
  async execute(step) { ... }
  async reflect(result) { ... }
}

// Time to build: 3-6 months for sophisticated agents
// Risk: Agents are hard. Edge cases are endless.

// Buy/Adapt: Use existing frameworks
import { createAgent } from 'agent-framework'

const agent = createAgent({
  tools: [...],
  context: contextProvider,
  constraints: [...]
})

The Hidden Costs of Building

// What you think building costs
build_cost = {
  "initial_development": "3 engineer-months",
  "total": "~$75,000"
}

// What building actually costs
real_build_cost = {
  "initial_development": "3 engineer-months",
  "debugging_edge_cases": "2 engineer-months",
  "optimization": "Ongoing, ~0.5 FTE",
  "security_review": "1 engineer-month",
  "documentation": "1 engineer-month",
  "oncall_support": "Ongoing",
  "opportunity_cost": "What else could they build?",
  "total": "~$300,000+ first year"
}

The Hidden Costs of Buying

// What you think buying costs
buy_cost = {
  "subscription": "$500/month",
  "total": "$6,000/year"
}

// What buying actually costs
real_buy_cost = {
  "subscription": "$500/month",
  "integration_time": "2 engineer-weeks",
  "vendor_dependency": "Risk if they pivot/fail",
  "customization_limits": "Some things you can't do",
  "data_concerns": "Your data on their servers",
  "total": "~$15,000/year + constraints"
}

Decision Matrix

The Hybrid Approach

Most successful AI products use a mix:

infrastructure = {
  "foundation_models": "Buy (OpenAI, Anthropic)",
  "model_abstraction": "Build (simple layer)",
  "context_layer": "Buy (focus on product)",
  "orchestration": "Adapt (use frameworks, customize)",
  "application": "Build (your differentiator)"
}

// Principle: Buy the commodity, build the differentiator.

Questions to Ask Yourself

1. Where's our moat? Build there. Buy everywhere else.
2. What's the opportunity cost? What could your team build instead?
3. How fast do we need to move? Building takes time you might not have.
4. What's the worst case? If vendor fails? If custom solution fails?
5. What do we actually enjoy? Engineers building unwanted infra deliver poor results.

The best decision isn't always "build" or "buy." It's knowing which layers deserve your engineering investment and which don't.