App Development Studio for AI Agents, Mobile & Web Apps

Architecting State Management for Generative UI in React Native

Avoid state bloat in AI-driven mobile apps by enforcing strict boundaries between server state, ephemeral UI state, and client-side persistence.

React Native Architecture: Performance Benchmarks in 2026

The legacy bridge is gone. New performance data shows how React Native's architectural overhaul impacts production app speed and frame stability.

Scaling AI Agent Architecture: Moving Beyond Simple Loops

Production-ready AI agents require structured coordination patterns to manage state, cost, and failure boundaries. Learn how to move beyond basic loops to system designs.

Multi-Agent AI Architecture: Moving Beyond Monolithic Design Patterns

Monolithic AI agents often fail at scale due to latency and reasoning degradation. Adopting a multi-agent architecture with isolated, single-responsibility agents improves performance.

Securing AI Agent Tool Access with MCP Gateways

As AI agents gain autonomous access to enterprise systems, traditional API security models fail. Implementing MCP gateways provides the necessary governance and audit trails.

React Native in 2026: Building High-Performance Cross-Platform Apps with New Architecture

Modern React Native architecture eliminates the bridge bottleneck. By integrating Fabric and Skia, developers can achieve native-speed performance for complex graphics.

Human-in-the-Loop AI Agents: When Approval Gates Matter

Production AI agents require intentional oversight. Learn why embedding approval gates directly into the execution runtime prevents context loss and improves reliability.

Architecting Trust in AI Workflows with Policy-Driven Guardrails

Moving AI agents to production requires moving beyond simple prompts. Implement policy-driven evaluation and runtime controls to manage agent behavior.

React Native 2026: Prioritizing Performance with the New Architecture

Transitioning to the New Architecture is no longer optional for high-performance React Native apps. Learn how to audit native modules and synchronous JSI communication.

Building AI Agents with Google ADK (Agent Development Kit)

Google's open-source Agent Development Kit provides a code-first framework for building deterministic AI agent workflows. Learn how to structure agents, tools, and safety callbacks.

Implementing Security Guardrails in Agent Development Kit (ADK) Architectures

Secure your AI agents by implementing granular identity management and tool-level access controls within the Agent Development Kit framework.

State Management in AI Agents: Lessons from 1000+ Tasks

Production AI agents often fail due to fragmented state. Learn how to architect memory and synchronization patterns that scale beyond simple demos.

Moving Beyond APM: Kafka-First Observability for Multi-Agent Systems

Standard APM tools fail to capture the complexity of multi-agent systems. A Kafka-first architecture enables session replay and decision context for production agents.

Choosing the Right AI Agent Orchestration Pattern for Production

Moving from single-agent demos to production systems requires selecting the correct orchestration pattern. Learn how to evaluate sequential, hierarchical, and swarm models.

Treating AI Agents as Production Workloads: The Governance Gap

Most enterprises run AI agents on infrastructure never built for them. Platform teams must bridge the governance gap to move from experimental pilots to production-ready systems.

Implementing LLM Evaluation Quality Gates in CI/CD Pipelines

How to integrate LLM evaluation into CI/CD pipelines by managing non-determinism and setting meaningful thresholds for quality gates.

AI coding agents and governance gaps: what teams need to fix

AI coding agent rollouts often fail when governance and review standards are defined after experimentation. Teams must establish clear approval rights and audit trails to prevent policy debt.

Architecting Production AI Agent Workflows for Reliability

Transitioning from prompt chains to agentic workflows requires graph-based runtimes and explicit state management. Learn how to build reliable, tool-calling systems.

practical AI Agents: Integrating OpenTelemetry Traces into Unity Catalog

Move beyond siloed observability by streaming OpenTelemetry traces directly into Unity Catalog. This architecture enables governed, analytics-ready AI agent monitoring.

Standardizing React Native Architecture for AI Coding Agents

Standardizing project context and architecture patterns allows AI coding agents to deliver consistent, high-quality React Native code across platforms.

Benchmarking AI Coding Agents on Multi-Million Line Codebases

Engineering teams must move beyond generic benchmarks to evaluate AI coding agents. Internal testing against real-world codebases reveals critical performance and cost trade-offs.