The SRE Approach to AI: Why Reliability Engineering Is the Missing Piece in Business Automation
The AI industry has a delivery problem, not a capability problem. Models can do incredible things, but most AI projects fail because nobody built the operational scaffolding to keep them working. SRE is that scaffolding.
Event-Driven Architecture for Small Business: S3 + Lambda + DynamoDB
Small businesses don’t need Kafka. S3 + Lambda + DynamoDB makes resilient, near-zero-cost event-driven automation pipelines you can build in an afternoon.
Why I Don’t Use LangChain (And What I Use Instead)
Why I avoid LangChain for production LLM systems. Abstraction leakage, debugging hell, and the explicit-Python alternative I use with the Anthropic SDK.
AI for Healthcare Admin: Automating Prior Authorizations and Intake Forms
Automate prior authorizations and intake forms with AI. HIPAA-compliant document extraction, validation, and routing on AWS that cuts 40% of manual processing time.
The Solo Consultant’s Guide to Production-Grade Deployments
Build a production-grade deployment system as a solo consultant using GitHub Actions, Terraform, and AWS OIDC. No stored credentials, automated rollbacks, environment promotion — one person, production-grade.
How to Calculate ROI on an Automation Project Before You Build It
A practical framework for calculating the ROI of automation projects before you build them. Includes formulas, real numbers, and a reusable template for presenting to your CFO.
Stop Building AI Features. Start Automating Workflows.
AI features impress in demos. AI-automated workflows deliver ROI. Here’s how to identify, scope, and prioritize the workflows worth automating in your business.
Serverless vs. Containers for AI Workloads: When to Use Which
A practical decision framework for choosing between AWS Lambda and ECS/Fargate for AI workloads, with real cost comparisons and architecture patterns.
The Runbook: Your AI System’s Most Important Document
A runbook is the difference between “we hope someone knows what to do” and “we have a plan.” Here’s how to build one for your AI system before 2am hits.
AI for Retail: Demand Forecasting Without a Data Science Team
You have 18 months of sales history and no data scientist. Here’s how to build a practical demand forecasting system on AWS using Claude, Lambda, and DynamoDB for about $30/month.
Building Idempotent Data Pipelines on AWS
Idempotency is the difference between a data pipeline and a nightmare. Here’s how to build pipelines on AWS that handle retries, duplicate events, and network failures without corrupting your data.
Prompt Engineering Is Not Software Engineering (And That’s the Problem)
Prompt engineering is instruction writing. Software engineering is architecture. Here’s how structured outputs, validation layers, and schema contracts bridge the gap for production AI systems.
How I Structure Client Projects for Zero-Downtime Handoff
Most AI consulting projects fail at handoff. Here’s the six-phase structure — repo layout, documentation, monitoring, CI/CD, training, and warranty — that lets clients own their system from day one.
Monitoring AI Systems: What to Measure and Why
Your AI system is up but silently degrading. Here are the five metrics — token cost, validation rate, latency percentiles, model drift, and end-to-end success — that catch problems before users do.
The Small Business Guide to AWS Costs (It’s Cheaper Than You Think)
AWS will bankrupt us — said every SMB owner before seeing the real numbers. Here’s what serverless automation actually costs, with a free tier that covers most small businesses entirely.
Why Your AI Chatbot Needs a Kill Switch
Customer-facing AI will have an off day. Here’s the real-time confidence threshold architecture — validation rules, escalation routing, and CloudWatch alarms — that keeps you out of PR trouble.
AI for Professional Services: 3 Automations Every Accounting Firm Needs
Three practical AI automations for accounting firms — client document intake, reconciliation validation, and report generation — with real costs, real ROI, and production architecture on AWS.
API Rate Limits Will Wreck Your AI Project (Here's How to Handle Them)
Rate limits will break your AI automation if you're not prepared. Here's the production architecture — exponential backoff, token buckets, and queue patterns — that keeps your system running.
The $5,000 Automation That Replaced a $60,000 Process
A real case study: how a $5,000 AWS automation replaced 700 hours/year of manual invoice processing — with an ROI of 1,190% in year one.
Terraform for Non-Engineers: Why Your AI System Needs Infrastructure-as-Code
Your AI automation isn't just code — it's infrastructure. Here's why Terraform matters and how Infrastructure-as-Code keeps your AI systems running.
How to Evaluate an AI Consultant (Without Being Technical)
Seven questions every business owner should ask before hiring an AI consultant — from success metrics and pricing models to handoff plans and red flags.
The Real Cost of "Free" AI Tools for Your Business
No-code AI platforms sound great until you hit rate limits, vendor lock-in, and zero observability. Here's what "free" actually costs — and what to build instead.
My Claude-Assisted Development Workflow
How a solo consultant delivers production-grade automations in days instead of weeks — using AI-assisted coding backed by a decade of SRE discipline.
5 Processes Every Small Business Should Automate in 2026
Invoice processing, support triage, report generation, onboarding, and inventory alerts — five high-ROI automation targets with real architecture patterns and expected savings.
Why Your AI Automation Breaks at 2am (And How to Fix It)
Most AI automations are built like demos: they work perfectly during the presentation, then silently fail in production. The difference isn't intelligence — it's operational discipline.