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CUT THE

HYPE

Practical AI strategy for startups who need results, not buzzwords. From integration to custom development.

8+Years AI/ML
LLMs toComputer Vision
3-6 WeeksPOC to Production

Let's Be Honest About AI

Every week, I talk to founders who've been sold on AI solutions they don't need. Chatbot wrappers dressed up as "intelligent automation." RAG systems that could be a simple database query. Custom models when off-the-shelf APIs would work fine.

Here's the thing: AI done wrong doesn't just waste money. It wastes time. It creates technical debt. And in a market moving this fast, six months building the wrong thing can mean missing your window entirely.

I help startups figure out what AI actually makes sense for their product. Sometimes that's a simple ChatGPT integration. Sometimes it's a sophisticated RAG pipeline. Sometimes it's "don't use AI here at all." The goal isn't to build AI. The goal is to ship value.

  1. Audit — Understand your product and where AI could genuinely help
  2. Advise — Recommend the simplest solution that solves the problem
  3. Architect — Design model-agnostic implementation (no vendor lock-in)
  4. Execute — Build it right the first time, or train your team to
AI Integration Deep Dive - Coming Soon

Experience

8+ yrs in AI/ML15+ AI integrations

RAG, Agents & Fine-tuning

"The best AI implementation is the one that's invisible to users and obvious in results."

Not Sure If AI Is Right for Your Product?

Book a 30-minute AI Reality Check. I'll review your product, identify where AI could add genuine value, and tell you what not to build. No pitch, just honest advice.

AI System Architecture

Building AI from core to scale

All components of a complete AI system. Click a level to see what's needed — everything else stays dim.

$1K-5K/mo · 6-10 weeks · 1-2 engineers
User Input
Text · Voice · Image
Prompt Template
System prompt + context
LLM Core
OpenAI · Anthropic · Gemini · Open Source
Output Formatting
JSON · Markdown · Stream
AI Response
Streamed to user
Data / RAG pipeline
Document Store
S3 · PostgreSQL · files
Chunking Engine
Semantic · fixed · recursive
Embedding Model
OpenAI · Cohere · local
Vector Store
pgvector · Qdrant · Pinecone
Retrieval + Reranking
Similarity search · context injection
Agent orchestration
Reasoning Loop
Plan → Act → Observe
Planner
Task decomposition
Reflector
Self-verify + correct
Short-term Memory
Conversation · task state
Structured Output
Pydantic AI schemas
Basic Guardrails
Content filter · cost cap
Tool registry (MCP)
Database
Read/write queries
Email / Slack
Send notifications
External APIs
REST · GraphQL
Code Execution
Sandbox · eval · deploy
Calendar
Book · check slots
Search / Browse
Web · internal docs
Multi-agent coordination
Supervisor Agent
Routes to specialists
Handoff Protocol
Context passing
Domain Agent A
Research · analysis
Domain Agent B
Writing · formatting
Long-term Memory
User history · learned patterns · episodic
Guardrails + safety
HITL Gate
Human approves: send email · transfer $ · delete data · external writes
Input Guardrails
Prompt injection defense · PII detection · topic filtering
Output Guardrails
Action allow-list · schema validation · toxicity filter
Observability
Tracing
Langfuse · LangSmith · full chain
Cost Tracking
Token usage · per-query cost
Decision Logs
Why agent chose X · replay
Training pipeline
Dataset Management
Labeling · cleaning · versioning
Training Engine
PyTorch · LoRA · QLoRA
Experiment Tracking
MLflow · Weights & Biases
Evaluation Suite
Benchmarks · human eval
Model Registry
Versions · lineage · promote
GPU Cluster
NVIDIA · TPU · distributed
Serving + deployment
Inference Servers
vLLM · TFServing · KServe
Load Balancing
Traffic routing · autoscale
A/B + Canary
Blue-green · gradual rollout
Edge / On-device
ONNX · TFLite · quantize
API Gateway
Rate limit · auth · metering
Feature Store
Online + offline features
Infrastructure + governance
CI/CD + CT
Continuous training loop
Data Lake
Raw + processed + stream
Drift Monitor
Data drift · model drift
Security
RBAC · audit trails
Compliance
HIPAA · GDPR · SOC2
Model Cards
Bias · fairness · docs
Not sure which level your product needs? Book an AI Reality Check →
Find Your AI Zone
Answer 6 quick questions to get your personalized AI architecture recommendation.

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Ready to Build AI That Actually Works?

Whether you need a simple ChatGPT integration or a custom multimodal system, there's a clear path forward.

  • Honest assessment of what you actually need (and don't)
  • Complete ownership - code, models, IP + knowledge transfer to your team
  • Architecture that ships value and scales with your growth