Why Aixgo

Why we built Aixgo and what we believe about production AI. Our design principles, values, and commitment to production-grade tooling.

Production AI Deserves Production Tooling

We’re not trying to out-prototype Python. We’re trying to out-ship it.

For too long, production AI teams have been forced to choose between:

  • The velocity of Python frameworks (LangChain, CrewAI, AutoGen)
  • The reliability of production-grade infrastructure (Go, Rust, Java)

Aixgo exists to eliminate that choice. We believe AI agents should ship with the same performance, security, and simplicity as the rest of your production systems.


The Production Reality

What MattersPython FrameworksAixgoImpact
Container Size1.2GB+8MB150x smaller
Cold Start30-45 seconds<100ms450x faster
Dependencies200+ packages~10 packages95% fewer
Type SafetyRuntime discoveryCompile-timeZero production surprises
Memory Baseline512MB+50MB10x more efficient

The Problem We’re Solving

Python excels at AI research and prototyping. But production reveals fundamental limitations:

  • Bloated deployments: 1GB+ containers, 200+ dependencies, massive security surface
  • Runtime surprises: Type errors caught in production, not at compile time
  • GIL bottleneck: No true parallelism for multi-agent systems
  • Slow cold starts: 30-45 second startup kills serverless economics
  • Scaling complexity: Manual orchestration, heavy memory footprint

Go developers shouldn’t have to abandon their stack’s strengths—speed, security, simplicity, and scalability—just to build AI agents. That meant trading a 5MB binary for a 1.5GB container, type safety for runtime errors, and instant startup for 45-second cold starts.

Aixgo exists because production AI teams deserve better.


Our Design Principles

1. Production-First, Not Research-First

API stability over rapid iteration. Performance-driven decisions. Security and observability built-in from day one. We prioritize production-hardened primitives over research experiments—fewer features, but battle-tested at scale.

Key trade-off: YAML configuration instead of Python DSLs for declarative, reviewable, deployable workflows.

2. Single Binary Simplicity

Deploy AI agents in <10MB binaries with zero runtime dependencies. No Python interpreter, no virtual environments, no Docker required (though it works great with containers).

Real impact: 8MB total deployment vs 1.2GB Python containers. Deploy to edge devices, serverless, IoT, anywhere.

3. Type Safety as a Feature

Catch errors at compile time, not in production. Go’s type system enforces contracts between agents, tools, and workflows—your IDE tells you what’s broken before your customers do.

Team velocity: Less time debugging production runtime errors, more time building features. Refactor with confidence.

4. Go-Native Patterns

We don’t port Python concepts to Go. We embrace Go’s strengths: channels for local message passing, gRPC for distributed systems, goroutines for concurrency, context for cancellation.

The abstraction that matters: Same code works locally (channels) and distributed (gRPC). Runtime picks transport automatically.

5. Observable by Default

Every agent interaction is traceable via OpenTelemetry, logged with structured context, and measurable with metrics. No instrumentation code required—just configuration.

Built-in integrations: Prometheus, Grafana, Datadog, Langfuse, New Relic. Works out of the box.

6. Open and Permissive

MIT licensed. Use in commercial products without restrictions. No vendor lock-in, no surprise license changes. Your investment is protected.


When to Choose Aixgo

Choose Aixgo When:

Deploying to production, not experimenting

  • Predictable performance and resource usage matter
  • Container size and cold start times are critical (serverless, edge)
  • Multi-region or distributed deployments needed

Your team already uses Go

  • Backend services in Go, want AI agents in same stack
  • Value type safety and compile-time error detection
  • Want to avoid Python dependency management overhead

Performance is non-negotiable

  • Sub-100ms cold starts for serverless
  • High-throughput pipelines (10,000+ req/s)
  • Resource-constrained environments (IoT, edge)

You need production-grade guarantees

  • Compile-time type safety
  • Single binary deployments
  • Minimal dependency surface
  • Enterprise security requirements

Choose Python Frameworks When:

Doing exploratory research

  • Rapid prototyping with frequent pivots
  • Research workflows that don’t need production deployment
  • Throwaway scripts and notebooks

You need Python’s ML ecosystem

  • Training models with PyTorch, TensorFlow, JAX
  • Data analysis with pandas, numpy, scikit-learn
  • Integration with Jupyter notebooks

Your team is Python-native

  • No Go experience and no interest in learning
  • Existing Python infrastructure
  • Python-first organizational culture

Our Commitment

Stability First

When v1.0 releases, we guarantee API stability with semantic versioning, long-term support, and clear upgrade paths. No breaking changes without major version bumps.

See our v1.0 Compatibility Promise for details.

Open Development

Public roadmap, open issue tracking, community-driven feature prioritization, transparent decision-making. Your feedback shapes Aixgo.

Long-Term Vision

Enterprise-grade multi-agent orchestration with production-proven patterns. We’re building for what ships, not what trends.


Join the Movement

Aixgo is just getting started. We’re building this in the open, learning from the community, and evolving based on real-world production usage.

If you’re tired of wrestling with Python in production, if you believe AI agents should ship with the same simplicity as the rest of your Go services, or if you just want to see what production-grade AI looks like in pure Go—join us.

Get Started:

Get Involved:

  • GitHub - Star the repo, open issues, contribute
  • Discussions - Ask questions, share ideas
  • Roadmap - See what’s coming next

Where Python prototypes go to die in production, Go agents ship and scale.

This is our philosophy. Welcome to Aixgo.