Jingway: Agent-Native by Design
Every action — AI-generated or human-guided — flows through agents. Every decision is faithfully recorded. Over time, agents need less hand-holding: they grow more domain-aware, more aligned, and smarter with every interaction. That's the path from steerable AI to progressive autonomy.
Agent-First Architecture
Every state change — whether AI generation or a button click — routes through a unified conversation system. No separate code paths. All actions are auditable, reproducible, and reversible.
Hierarchical Code-Executing Agents
Multi-level agent hierarchies where parent agents spawn typed children. Agents emit composable JavaScript in sandboxed V8 isolates — eliminating tool explosion while enabling dynamic, branching workflows.
Complete Lineage Tracing
Every piece of data is an immutable snapshot linked through transforms. Three transform types — AI-generated, human, and computed — create a complete, traversable graph of how any output was produced.
Progressive Steering
Rather than all-or-nothing AI output, the framework supports granular human oversight — patch approval workflows, incremental review, and approval at every level of the agent hierarchy.
Applicable Scenarios
Domain-Specific AI ApplicationsBuild agent-powered applications for any domain — content creation, research, operations — with progressive steering that works naturally with existing knowledge and data.
Complex Multi-Step WorkflowsOrchestrate sophisticated pipelines where agents branch, loop, and compose operations — with hierarchical control flow and clear parent-child data passing.
Auditable AI SystemsWhen you need to know exactly how every output was produced — complete lineage from input through every agent decision and human approval to final result.
Collaborative Human-AI SystemsReal-time co-creation where humans and AI agents work on the same content simultaneously — with CRDT-based sync, content-addressed versioning, and instant undo/redo.