The Aixgo Proverbs

15 production-tested principles for building AI agents that ship and scale. Inspired by Go Proverbs and The Zen of Go.

The Aixgo Proverbs

Inspired by Go Proverbs and The Zen of Go

1. Production AI deserves production tooling

Research frameworks are built for notebooks. Production frameworks are built for uptime. Choose tools that match your deployment target, not your prototype.

2. Don’t prototype in Python and hope it ships; ship in Go and know it works

Prototyping velocity matters, but shipping velocity matters more. Type safety, compile-time errors, and single binaries eliminate the “hope it works in prod” phase.

3. A single binary is better than a thousand dependencies

Every dependency is a liability—security patches, version conflicts, build complexity. A single 8MB binary has zero runtime dependencies and infinite deployment flexibility.

4. Type safety at compile time beats hope at runtime

AttributeError in production is a failure of tooling. If your IDE can’t tell you what breaks, your users will. The compiler is your first line of defense.

5. Ship megabytes, not gigabytes

1.5GB containers kill serverless economics. 8MB binaries enable edge deployment, multi-region rollouts, and sub-100ms cold starts. Size is a feature.

6. Observability is not optional

If you can’t trace it, you can’t debug it. Built-in OpenTelemetry means every agent is observable from day one. Configuration, not instrumentation.

7. Clear configuration is better than clever code

YAML files are reviewable, deployable without rebuilding, and shareable across teams. Python DSLs are flexible until you need to audit what’s actually running.

8. Go-native patterns, not Python ports

Goroutines, channels, contexts, and interfaces are Go’s strengths. Don’t port Python concepts—embrace the language you’re shipping in.

9. Channels orchestrate agents; gRPC orchestrates systems

Local mode uses channels for zero-latency message passing. Distributed mode uses gRPC for cross-service orchestration. Same code, different transport.

10. Fast cold starts enable real serverless

45-second Python cold starts mean you’re paying for idle compute or pre-warming instances. Sub-100ms Go cold starts mean serverless actually scales to zero.

11. The best deployment is one you never debug

When your binary runs the same everywhere—dev, staging, prod—“works on my machine” disappears. Static compilation eliminates environment drift.

12. Errors are values; handle them before production does

Go’s explicit error handling forces you to think about failure cases at write time, not runtime. Every if err != nil is a production incident prevented.

13. If it doesn’t compile, it doesn’t ship

Compilation failures are cheaper than production failures. Type errors, interface mismatches, and API breaks surface before deployment, not after.

14. Simplicity scales; complexity fails

Clever abstractions break under load. Clear, explicit code survives oncall at 3 AM. Optimize for the engineer debugging in production.

15. Where prototypes go to die, Go agents ship and thrive

Python excels at research. Go excels at production. Pick the tool that matches the environment your code will run in, not the environment it’s written in.

The Aixgo Proverbs