AI Workflow Automation: Decisions Are Cheap, Actions Are Expensive
The trick to AI workflow automation is simple: let the model decide, let deterministic code act, and never confuse the two.
Automation
Definition
Automation coverage in this archive spans 4 posts from Jul 2017 to Aug 2025 and leans into practical engineering craft: interfaces, testing, and maintainable implementation details. The strongest adjacent threads are devops, ci/cd, and ai. Recurring title motifs include actions, patterns, ai, and workflow.
What the archive argues
- The through-line is clarity first: simple designs that survive change beat clever abstractions.
- The consistent theme from 2017 to 2025 is disciplined execution over hype cycles.
- This topic repeatedly intersects with devops, ci/cd, and ai, so design choices here rarely stand alone.
Execution checklist
- Keep interfaces small, automate regressions early, and make operational assumptions explicit in code.
- Start with the newest post to calibrate current constraints, then backtrack to older entries for first principles.
- When boundary questions appear, cross-read devops and ci/cd before committing implementation details.
Common failure modes
- Abstracting before usage patterns are stable enough to justify indirection.
- Treating style consistency as optional until quality and velocity both degrade.
- Applying guidance from 2017 to 2025 without revisiting assumptions as context changed.
Suggested reading path
- Start here (current state): AI Workflow Automation: Decisions Are Cheap, Actions Are Expensive
- Then read (operating middle): The GitHub Actions Patterns I Actually Use in Production
- Finish with (foundational context): Stop Doing Security Reviews by Hand
Related posts
- AI Workflow Automation: Decisions Are Cheap, Actions Are Expensive
- Infrastructure as Code Patterns That Actually Scale
- The GitHub Actions Patterns I Actually Use in Production
- Stop Doing Security Reviews by Hand
References
Infrastructure as Code Patterns That Actually Scale
Practical Terraform patterns for teams that have outgrown the tutorial stage: module design, state management, environment promotion, and policy enforcement.
The GitHub Actions Patterns I Actually Use in Production
Matrix builds, dependency caching, gated deploys, and the security gotchas I hit building Decloud's CI/CD pipeline on GitHub Actions.
Stop Doing Security Reviews by Hand
Your manual security gate is a bottleneck pretending to be a process. Here's how I moved security checks into the pipeline at the fintech startup so we could ship fast without shipping stupid.