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Joshua Wendt

Articles by Joshua Wendt on AI implementation, workflow automation, and software engineering.

171 articles · Page 14 of 15

Insight9 min read

Developer Experience Is a Business Metric

Slow builds, flaky tests, and painful deploys are measurable drags on revenue. Learn how to quantify and improve developer experience.

Insight9 min read

Why Automation Projects Fail (And How to Avoid It)

Automation projects fail due to unclear scope, broken processes, and missing feedback loops — not technology. Here's how to avoid the common pitfalls.

Insight10 min read

Measuring Automation ROI Beyond Time Saved

Time savings alone understate automation ROI. Learn to measure error reduction, data quality, scalability, and employee satisfaction.

Insight9 min read

Right-Sizing Your Architecture

Monolith vs. microservices is a false binary. Match your architecture to your team size, product maturity, and actual complexity.

Insight11 min read

Managing Stakeholder Expectations in AI Projects

Learn how to bridge the gap between AI demos and production systems. Set realistic expectations and maintain stakeholder trust throughout your AI project.

Insight9 min read

Integration Patterns That Don't Break at Scale

Webhooks, polling, message queues, or event-driven architecture? How to choose the right integration pattern and avoid the point-to-point trap.

Insight8 min read

API Design Principles That Stand the Test of Time

APIs outlive the code that calls them. A practical guide to designing HTTP APIs that stay stable, intuitive, and maintainable as your product scales.

Insight9 min read

Build vs Buy: An AI Solution Framework

When should you build custom AI solutions vs. leverage existing tools? A practical framework for making this critical decision.

Insight10 min read

Build vs. Buy: Workflow Automation Guide

iPaaS, RPA, or custom code? A practical framework for choosing the right workflow automation approach for your business.

Insight9 min read

Data Quality: The Make or Break Factor in AI

Why data quality matters more than model choice for AI success. Learn practical steps to assess, clean, and improve your data before any AI initiative.

Insight9 min read

The Case for Boring Technology

Proven tools beat shiny frameworks. How boring technology choices compound into faster delivery, fewer outages, and real competitive advantage.

Insight8 min read

AI-Assisted Development: Beyond the Hype

An honest look at AI coding assistants like GitHub Copilot and Claude. Learn where they excel, where they fail, and how to use them effectively.