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AI consultation vs enterprise automation: Which do you need?
A practical comparison of AI consultation and enterprise automation, including when to choose each and when you need both.
Read article ↗Dreamcode insights
Ideas for systems that have to work.
Practical notes on AI, automation and software delivery, written for the people who will operate what gets built.
Custom Software vs Off-the-Shelf Tools: How to Choose
Compare custom software and off-the-shelf tools by fit, speed, cost, integration, ownership, and long-term operating burden.
How to Scope the First Version of an AI or Automation Project
A step-by-step framework for defining a small, measurable first release without ignoring data, exceptions, review, and operations.
Design human review into AI workflows: a practical risk framework
Use this risk-based framework to decide when AI can act, when humans should review, and where escalation is essential.
What Does a Good Workflow Handoff Look Like?
A good workflow handoff transfers context, ownership, timing, and exception rules—not just a task notification.
Why AI Projects Can Fail at Adoption, Not Technology
AI projects stall when the new workflow lacks trust, ownership, incentives, useful feedback, and a clear place in daily work.
Why Automation Projects Fail: 7 Problems to Fix Early
Seven common reasons automation projects fail, from unclear ownership and unstable processes to missing exception handling and adoption.
What should you automate first? Start with the handoffs
A practical way to choose the best first automation by looking for repetition, context loss, exception volume, and clear ownership.
A safer invoice automation pattern with n8n
How to structure invoice capture, validation, human review and accounting sync without hiding operational risk.