Pika takes a platform approach built on three core principles: leverage AWS for proven infrastructure, define agents as configuration to keep codebases clean, and include production intelligence from day one. This combination gets you from idea to production-ready AI in weeks instead of months.
Three Core Principles
Section titled “Three Core Principles”Pika is built on architectural decisions that directly address the gap between prototype and production:
AWS Foundation
Use proven, enterprise-grade infrastructure instead of building your own. AWS handles scale, security, and operations.
Agent-as-Config
Define agents declaratively instead of tangling them with your codebase. Keep clean boundaries and deploy like any other configuration.
Production-Ready
Ship with UI, security, and operational tooling included instead of building them yourself. Focus on agent intelligence, not infrastructure.
From Toy to Tool
Bridge the demo-to-production gap with built-in capabilities for reliability, feedback, and continuous improvement.
Why This Approach Works
Section titled “Why This Approach Works”These aren't independent choices - they work together:
AWS + Config = Safe Deployments: Infrastructure as Code plus configuration-based agents means version control, review, and rollback for everything.
Config + Production Features = Rapid Iteration: Change agent behavior by deploying new config. Built-in observability shows you what's working.
Production Features + AWS = Enterprise Ready: Security, compliance, and scale are included because we build on AWS services that already provide them.
The Result
Section titled “The Result”Teams using Pika typically:
- Deploy their first agent in days, not months
- Ship new agents in hours, not weeks
- Focus engineering time on intelligence, not infrastructure
- Scale confidently from prototype to production
Explore each principle to understand how Pika makes production AI achievable: