AI Agents articles

Build an AI agent infrastructure stack with Polyaxon

Map an AI agent stack to Polyaxon services, jobs, sandboxes, queues, connections, tracking, and versioned components without conflating their responsibilities.

Tune RAG retrieval with Polyaxon experiment matrices

Compare RAG chunk sizes, retrieval depth, and model choices with Polyaxon experiment matrices, fixed evaluation inputs, and quality-aware run comparisons.

Deploy AI agents as Polyaxon services

Package and deploy an AI agent as a Polyaxon service with explicit ports, health checks, scoped connections, and release evidence.

Connect agent tool calls to Polyaxon execution

Translate agent tool requests into authorized Polyaxon sandbox execution with bounded commands, structured results, and explicit lifecycle ownership.

Track AI-generated code provenance and review

Use Polyaxon run metadata, source revisions, artifact hashes, and independent review to establish provenance for AI-generated code.

Build data-analysis agents on Polyaxon

Build data-analysis agents with Polyaxon jobs and sandboxes, versioned data inputs, deterministic checks, and reviewable analysis artifacts.

Secure LLM data flows with Polyaxon

Design LLM data flows around scoped Polyaxon connections, isolated execution responsibilities, redacted evidence, and explicit output retention.

LLM agents: architecture and production operations

Map LLM agent reasoning, tools, execution, evaluation, and release workflows to Polyaxon services, sandboxes, jobs, components, and DAGs.

Run Polyaxon AI workloads from GitHub Actions

Use GitHub Actions to validate and submit traceable AI, ML, and agent workloads to Polyaxon without turning CI runners into training infrastructure.