From prompts to production content pipeline.
Monday: 3 prompts for product descriptions. Tuesday: automated generation code. Wednesday: team workflows for content ops. Thursday: complete technical architecture. Agents, ML pipeline, SEO optimization, and CMS integration for 100K+ products daily.
Key Assumptions
- •Catalog size: 1K-500K SKUs, growing 5-10% monthly
- •Update frequency: New products daily, refreshes quarterly
- •SEO requirements: Target keywords, readability scores, meta tags
- •Brand consistency: Voice guidelines, prohibited terms, templates
- •Integration: Shopify/Magento/BigCommerce or custom CMS API
System Requirements
Functional
- Generate product descriptions from attributes (title, specs, images)
- SEO optimization: keyword density, meta descriptions, alt text
- Brand voice enforcement: tone, style, prohibited words
- Bulk processing: 1K+ products in single batch
- CMS integration: Push to Shopify, Magento, or custom API
- A/B testing: Multiple variants per product
- Quality scoring: Readability, uniqueness, keyword coverage
Non-Functional (SLOs)
💰 Cost Targets: {"per_product_usd":0.02,"per_batch_1k_usd":15,"monthly_infra_usd":500}
Agent Layer
planner
L3Decompose product description task into steps: template selection, content generation, SEO optimization, quality check
🔧 template_selector, keyword_research_api, brand_policy_checker
⚡ Recovery: If no template found → fallback to generic template, If keyword API fails → use cached keywords from last 24h
executor
L2Execute the plan: generate description, apply template, call LLM, format output
🔧 openai_api, template_engine, image_analyzer
⚡ Recovery: If LLM timeout → retry 3x with exponential backoff, If generation fails → queue for human review
seo_agent
L3Optimize description for search: keyword density, readability, meta tags, structured data
🔧 semrush_api, readability_scorer, keyword_density_analyzer
⚡ Recovery: If SEMrush API down → use cached keyword data, If density too low → regenerate with keyword boost
evaluator
L4Validate output quality: brand voice, readability, uniqueness, keyword coverage
🔧 plagiarism_checker, brand_voice_classifier, readability_api
⚡ Recovery: If score < 80 → trigger regeneration with feedback, If plagiarism detected → block and flag
guardrail
L4Policy enforcement: prohibited terms, legal compliance, safety filters
🔧 prohibited_terms_checker, legal_compliance_api, toxicity_detector
⚡ Recovery: If violation found → block publish, queue for review, If legal API down → default to conservative blocking
template_agent
L2Select and populate category-specific templates with product data
🔧 template_db, variable_extractor, style_matcher
⚡ Recovery: If no category template → use generic, If missing variables → mark as optional
ML Layer
Feature Store
Update: Daily batch + real-time on product update
- • product_attribute_embeddings
- • historical_conversion_rate
- • category_avg_quality_score
- • brand_voice_vector
- • competitor_keyword_density
- • seasonal_keyword_trends
Model Registry
Strategy: Blue-green deployment with 10% canary
- • gpt-4o-mini
- • brand_voice_classifier
- • readability_scorer
- • keyword_ranker
Observability
Metrics
- 📊 generation_success_rate
- 📊 llm_latency_p95_ms
- 📊 quality_score_avg
- 📊 approval_rate_percent
- 📊 regeneration_rate_percent
- 📊 cost_per_product_usd
- 📊 seo_score_avg
- 📊 keyword_density_avg
Dashboards
- 📈 ops_dashboard
- 📈 ml_dashboard
- 📈 cost_dashboard
- 📈 quality_dashboard
Traces
✅ Enabled
Deployment Variants
🚀 Startup
Infrastructure:
- • Vercel/Netlify for frontend
- • Serverless functions (Lambda/Cloud Run)
- • Managed PostgreSQL (Supabase/Neon)
- • Redis Cloud
- • OpenAI API (pay-as-you-go)
- • Shopify integration (OAuth app)
→ Quick to ship, low upfront cost
→ Auto-scaling with serverless
→ Managed services reduce ops burden
→ Cost: ~$100-500/mo depending on volume
🏢 Enterprise
Infrastructure:
- • Kubernetes (EKS/GKE) for control plane
- • VPC isolation + private subnets
- • Aurora PostgreSQL (multi-AZ)
- • Redis Cluster (ElastiCache)
- • BYO LLM (self-hosted or Azure OpenAI)
- • KMS/HSM for encryption
- • SSO/SAML integration
- • Multi-region deployment
- • Dedicated support + SLA
→ Full control over infrastructure
→ Data residency compliance (GDPR, SOC2)
→ Private networking, no public internet
→ Cost: $5K-20K/mo depending on scale
📈 Migration: Start with startup stack. Migrate to enterprise when: (1) >10K products/day, (2) Need data residency, (3) Require 99.9% SLA, (4) Custom LLM or private deployment. Migration path: Lift-and-shift to containers → VPC setup → Multi-region replication → BYO LLM.
Risks & Mitigations
⚠️ LLM generates off-brand content
Medium✓ Mitigation: Multi-layer validation: brand voice classifier (94% accuracy), human review queue for low-confidence outputs, regular fine-tuning on approved content
⚠️ Hallucinated product features
Medium✓ Mitigation: Attribute validation against product DB, fact-checking layer, confidence scoring, 100% human review for high-value products (>$500)
⚠️ SEO keyword stuffing (Google penalty)
Low✓ Mitigation: Keyword density limits (2-3%), readability scoring (Flesch-Kincaid >60), A/B test against human-written baseline
⚠️ API rate limits (OpenAI, Shopify)
High✓ Mitigation: Multi-LLM failover, exponential backoff, queue-based retry, rate limiter (10 req/sec), caching for 24h
⚠️ Cost overruns (LLM API costs)
Medium✓ Mitigation: Cost tracking per product, alerts at $1K/day, auto-throttle at $5K/day, monthly budget caps, cheaper models for low-priority products
⚠️ Data privacy violation (PII in descriptions)
Low✓ Mitigation: PII detection + redaction, no customer data in prompts, audit logs (2yr retention), privacy-by-design
⚠️ Competitor trademark infringement
Medium✓ Mitigation: Trademark database check, prohibited terms blocklist (500+ brands), legal review for high-risk categories, guardrail agent enforcement
Evolution Roadmap
Phase 1: MVP (0-3 months)
Q1 2025- → Launch with 3 core agents (Executor, Evaluator, Guardrail)
- → Shopify integration only
- → 100-500 products/day capacity
- → 90% quality score target
Phase 2: Scale (3-6 months)
Q2 2025- → Add Planner, SEO, Template agents
- → Multi-platform support (Magento, BigCommerce)
- → 1K-10K products/day capacity
- → A/B testing framework
- → 95% approval rate
Phase 3: Enterprise (6-12 months)
Q3-Q4 2025- → 10K-100K products/day capacity
- → Multi-region deployment
- → 99.9% SLA
- → Custom LLM support
- → Enterprise security (SSO, RBAC, audit)
Complete Systems Architecture
End-to-end layer view
Sequence Diagram - Product Description Flow
E-commerce Product Description - Agent Orchestration
7 ComponentsE-commerce Product Description - External Integrations
9 ComponentsData Flow - Product to Published Description
End-to-end flow in 4.5 seconds
Scaling Patterns
Key Integrations
Shopify API
SEMrush API
OpenAI API
Image Analysis (AWS Rekognition)
Security & Compliance
Failure Modes & Fallbacks
| Failure | Fallback | Impact | SLA |
|---|---|---|---|
| OpenAI API down | Switch to backup LLM (Anthropic Claude) or queue for retry | Degraded performance, 10% slower | 99.5% |
| SEMrush API timeout | Use cached keywords from last 24h or generic keywords | Slightly lower SEO optimization | 99.0% |
| Quality score < 80 | Regenerate with feedback or queue for human review | Delayed publication, maintains quality | 95% auto-approval |
| Guardrail detects policy violation | Block publication, flag for review | Safety maintained, no bad content published | 100% enforcement |
| Shopify API rate limit | Exponential backoff, queue remaining products | Delayed sync, eventual consistency | 99.0% |
| Database connection loss | Read from replica, queue writes | Read-only mode for up to 5 minutes | 99.9% |
| Template not found for category | Use generic fallback template | Less customized output | 100% coverage |
Multi-Agent Architecture
6 specialized agents collaborate autonomously
┌──────────────┐
│ Planner │ ← Orchestrates all agents
└──────┬───────┘
│
┌───┴────┬──────────┬──────────┬──────────┐
│ │ │ │ │
┌──▼──┐ ┌─▼──┐ ┌────▼────┐ ┌──▼───┐ ┌──▼────┐
│Temp │ │Exec│ │ SEO │ │Eval │ │Guard │
│Agent│ │utor│ │ Agent │ │uator │ │rail │
└─────┘ └────┘ └─────────┘ └──────┘ └───────┘
│ │ │ │ │
└───────┴──────────┴──────────┴──────────┘
│
┌───▼────┐
│Shopify │
│Adapter │
└────────┘Agent Collaboration Flow
Reactive Agent
Reflexive Agent
Deliberative Agent
Orchestrator Agent
Levels of Autonomy
Advanced ML/AI Patterns
Production ML engineering beyond basic API calls