Agent OS project details and every feature in one place

• - A logistics agent uses Filesystem (fs) to keep shipment data and job state inside one hosted runtime instead of juggling separate infrastructure services.
• - A customer support agent uses Filesystem (fs) to keep context, files, and automation steps available across every conversation handoff.

LangChain plus custom Redis, storage, and worker glue

Agent OS ships the primitive as a managed, isolated service instead of making teams wire multiple vendors together first.

• - A logistics agent uses Network (net) to keep shipment data and job state inside one hosted runtime instead of juggling separate infrastructure services.
• - A customer support agent uses Network (net) to keep context, files, and automation steps available across every conversation handoff.

LangChain plus custom Redis, storage, and worker glue

Agent OS ships the primitive as a managed, isolated service instead of making teams wire multiple vendors together first.

• - A logistics agent uses Process Execution (proc) to keep shipment data and job state inside one hosted runtime instead of juggling separate infrastructure services.
• - A customer support agent uses Process Execution (proc) to keep context, files, and automation steps available across every conversation handoff.

LangChain plus custom Redis, storage, and worker glue

Agent OS ships the primitive as a managed, isolated service instead of making teams wire multiple vendors together first.

• - A logistics agent uses Memory Cache (mem) to keep shipment data and job state inside one hosted runtime instead of juggling separate infrastructure services.
• - A customer support agent uses Memory Cache (mem) to keep context, files, and automation steps available across every conversation handoff.

LangChain plus custom Redis, storage, and worker glue

Agent OS ships the primitive as a managed, isolated service instead of making teams wire multiple vendors together first.

• - A logistics agent uses Database (db) to keep shipment data and job state inside one hosted runtime instead of juggling separate infrastructure services.
• - A customer support agent uses Database (db) to keep context, files, and automation steps available across every conversation handoff.

LangChain plus custom Redis, storage, and worker glue

Agent OS ships the primitive as a managed, isolated service instead of making teams wire multiple vendors together first.

• - A logistics agent uses Events (events) to keep shipment data and job state inside one hosted runtime instead of juggling separate infrastructure services.
• - A customer support agent uses Events (events) to keep context, files, and automation steps available across every conversation handoff.

LangChain plus custom Redis, storage, and worker glue

Agent OS ships the primitive as a managed, isolated service instead of making teams wire multiple vendors together first.

• - A treasury operations crew uses Consensus System before releasing a payment so one weak agent cannot approve a high-risk action alone.
• - A medical review workflow uses Consensus System to require multiple specialist agents to agree before a diagnosis summary is escalated.

CrewAI with app-level voting logic bolted on afterward

Agent OS makes consensus a platform rule with logging, thresholds, and failover instead of an optional prompt pattern.

• - A treasury operations crew uses Reputation Tracking before releasing a payment so one weak agent cannot approve a high-risk action alone.
• - A medical review workflow uses Reputation Tracking to require multiple specialist agents to agree before a diagnosis summary is escalated.

CrewAI with app-level voting logic bolted on afterward

Agent OS makes consensus a platform rule with logging, thresholds, and failover instead of an optional prompt pattern.

• - A treasury operations crew uses Chain Logging before releasing a payment so one weak agent cannot approve a high-risk action alone.
• - A medical review workflow uses Chain Logging to require multiple specialist agents to agree before a diagnosis summary is escalated.

CrewAI with app-level voting logic bolted on afterward

Agent OS makes consensus a platform rule with logging, thresholds, and failover instead of an optional prompt pattern.

• - A treasury operations crew uses Coordination before releasing a payment so one weak agent cannot approve a high-risk action alone.
• - A medical review workflow uses Coordination to require multiple specialist agents to agree before a diagnosis summary is escalated.

CrewAI with app-level voting logic bolted on afterward

Agent OS makes consensus a platform rule with logging, thresholds, and failover instead of an optional prompt pattern.

• - A treasury operations crew uses Validation before releasing a payment so one weak agent cannot approve a high-risk action alone.
• - A medical review workflow uses Validation to require multiple specialist agents to agree before a diagnosis summary is escalated.

CrewAI with app-level voting logic bolted on afterward

Agent OS makes consensus a platform rule with logging, thresholds, and failover instead of an optional prompt pattern.

• - A treasury operations crew uses Diversity Enforcement before releasing a payment so one weak agent cannot approve a high-risk action alone.
• - A medical review workflow uses Diversity Enforcement to require multiple specialist agents to agree before a diagnosis summary is escalated.

CrewAI with app-level voting logic bolted on afterward

Agent OS makes consensus a platform rule with logging, thresholds, and failover instead of an optional prompt pattern.

• - A sales operations agent uses MCP Server to reach Gmail, Slack, and Drive through one consistent API surface.
• - A DevOps agent uses MCP Server to update GitHub, fetch run context, and notify Slack without building custom connectors for each tool.

Direct MCP wiring in each client or Claude Desktop-only setups

Agent OS adds shared routing, policy checks, and consensus-aware execution on top of standard MCP access.

• - A sales operations agent uses MCP Tool Listing to reach Gmail, Slack, and Drive through one consistent API surface.
• - A DevOps agent uses MCP Tool Listing to update GitHub, fetch run context, and notify Slack without building custom connectors for each tool.

Direct MCP wiring in each client or Claude Desktop-only setups

Agent OS adds shared routing, policy checks, and consensus-aware execution on top of standard MCP access.

• - A sales operations agent uses MCP Tool Execution to reach Gmail, Slack, and Drive through one consistent API surface.
• - A DevOps agent uses MCP Tool Execution to update GitHub, fetch run context, and notify Slack without building custom connectors for each tool.

Direct MCP wiring in each client or Claude Desktop-only setups

Agent OS adds shared routing, policy checks, and consensus-aware execution on top of standard MCP access.

• - A sales operations agent uses MCP Client to reach Gmail, Slack, and Drive through one consistent API surface.
• - A DevOps agent uses MCP Client to update GitHub, fetch run context, and notify Slack without building custom connectors for each tool.

Direct MCP wiring in each client or Claude Desktop-only setups

Agent OS adds shared routing, policy checks, and consensus-aware execution on top of standard MCP access.

• - A sales operations agent uses MCP Router to reach Gmail, Slack, and Drive through one consistent API surface.
• - A DevOps agent uses MCP Router to update GitHub, fetch run context, and notify Slack without building custom connectors for each tool.

Direct MCP wiring in each client or Claude Desktop-only setups

Agent OS adds shared routing, policy checks, and consensus-aware execution on top of standard MCP access.

• - A sales operations agent uses Universal MCP Access to reach Gmail, Slack, and Drive through one consistent API surface.
• - A DevOps agent uses Universal MCP Access to update GitHub, fetch run context, and notify Slack without building custom connectors for each tool.

Direct MCP wiring in each client or Claude Desktop-only setups

Agent OS adds shared routing, policy checks, and consensus-aware execution on top of standard MCP access.

• - A legal intake agent uses Browse Skills to add document parsing or clause extraction without rebuilding those capabilities from scratch.
• - A growth team agent uses Browse Skills to install SEO, scraping, or enrichment skills as reusable production modules.

Zapier AI actions or ad hoc private tool registries

Agent OS treats extensions as installable runtime capabilities with analytics, reviews, and revenue sharing built in.

• - A legal intake agent uses Install Skills to add document parsing or clause extraction without rebuilding those capabilities from scratch.
• - A growth team agent uses Install Skills to install SEO, scraping, or enrichment skills as reusable production modules.

Zapier AI actions or ad hoc private tool registries

Agent OS treats extensions as installable runtime capabilities with analytics, reviews, and revenue sharing built in.

• - A legal intake agent uses Use Skills to add document parsing or clause extraction without rebuilding those capabilities from scratch.
• - A growth team agent uses Use Skills to install SEO, scraping, or enrichment skills as reusable production modules.

Zapier AI actions or ad hoc private tool registries

Agent OS treats extensions as installable runtime capabilities with analytics, reviews, and revenue sharing built in.

• - A legal intake agent uses Skill Execution Engine to add document parsing or clause extraction without rebuilding those capabilities from scratch.
• - A growth team agent uses Skill Execution Engine to install SEO, scraping, or enrichment skills as reusable production modules.

Zapier AI actions or ad hoc private tool registries

Agent OS treats extensions as installable runtime capabilities with analytics, reviews, and revenue sharing built in.

• - A legal intake agent uses Publish Skills to add document parsing or clause extraction without rebuilding those capabilities from scratch.
• - A growth team agent uses Publish Skills to install SEO, scraping, or enrichment skills as reusable production modules.

Zapier AI actions or ad hoc private tool registries

Agent OS treats extensions as installable runtime capabilities with analytics, reviews, and revenue sharing built in.

• - A legal intake agent uses Reviews & Ratings to add document parsing or clause extraction without rebuilding those capabilities from scratch.
• - A growth team agent uses Reviews & Ratings to install SEO, scraping, or enrichment skills as reusable production modules.

Zapier AI actions or ad hoc private tool registries

Agent OS treats extensions as installable runtime capabilities with analytics, reviews, and revenue sharing built in.

• - A legal intake agent uses Developer Dashboard to add document parsing or clause extraction without rebuilding those capabilities from scratch.
• - A growth team agent uses Developer Dashboard to install SEO, scraping, or enrichment skills as reusable production modules.

Zapier AI actions or ad hoc private tool registries

Agent OS treats extensions as installable runtime capabilities with analytics, reviews, and revenue sharing built in.

• - A legal intake agent uses Revenue Sharing to add document parsing or clause extraction without rebuilding those capabilities from scratch.
• - A growth team agent uses Revenue Sharing to install SEO, scraping, or enrichment skills as reusable production modules.

Zapier AI actions or ad hoc private tool registries

Agent OS treats extensions as installable runtime capabilities with analytics, reviews, and revenue sharing built in.

• - A legal intake agent uses Skill Analytics to add document parsing or clause extraction without rebuilding those capabilities from scratch.
• - A growth team agent uses Skill Analytics to install SEO, scraping, or enrichment skills as reusable production modules.

Zapier AI actions or ad hoc private tool registries

Agent OS treats extensions as installable runtime capabilities with analytics, reviews, and revenue sharing built in.

• - A healthcare intake agent uses JWT-Based Auth to keep patient data isolated while automating record lookups and file processing.
• - A finance operations agent uses JWT-Based Auth to block unsafe outbound calls and prevent cross-tenant data leaks.

Homegrown API key checks plus patchwork network rules

Agent OS enforces identity, isolation, rate controls, and outbound safety in the platform, not as optional middleware.

• - A healthcare intake agent uses API Key Management to keep patient data isolated while automating record lookups and file processing.
• - A finance operations agent uses API Key Management to block unsafe outbound calls and prevent cross-tenant data leaks.

Homegrown API key checks plus patchwork network rules

Agent OS enforces identity, isolation, rate controls, and outbound safety in the platform, not as optional middleware.

• - A healthcare intake agent uses Agent Isolation to keep patient data isolated while automating record lookups and file processing.
• - A finance operations agent uses Agent Isolation to block unsafe outbound calls and prevent cross-tenant data leaks.

Homegrown API key checks plus patchwork network rules

Agent OS enforces identity, isolation, rate controls, and outbound safety in the platform, not as optional middleware.

• - A healthcare intake agent uses Rate Limiting to keep patient data isolated while automating record lookups and file processing.
• - A finance operations agent uses Rate Limiting to block unsafe outbound calls and prevent cross-tenant data leaks.

Homegrown API key checks plus patchwork network rules

Agent OS enforces identity, isolation, rate controls, and outbound safety in the platform, not as optional middleware.

• - A healthcare intake agent uses SSRF Protection to keep patient data isolated while automating record lookups and file processing.
• - A finance operations agent uses SSRF Protection to block unsafe outbound calls and prevent cross-tenant data leaks.

Homegrown API key checks plus patchwork network rules

Agent OS enforces identity, isolation, rate controls, and outbound safety in the platform, not as optional middleware.

• - A healthcare intake agent uses Sandbox Security to keep patient data isolated while automating record lookups and file processing.
• - A finance operations agent uses Sandbox Security to block unsafe outbound calls and prevent cross-tenant data leaks.

Homegrown API key checks plus patchwork network rules

Agent OS enforces identity, isolation, rate controls, and outbound safety in the platform, not as optional middleware.

• - A startup founder uses Landing Page to onboard an internal agent in minutes without reading low-level infrastructure docs first.
• - A platform engineer uses Landing Page to hand product teams a self-serve control surface instead of a collection of shell commands.

Internal admin panels or CLI-only developer tooling

Agent OS gives teams a production-grade self-serve experience instead of forcing them to live in scripts and dashboards they built themselves.

• - A startup founder uses Signup Flow to onboard an internal agent in minutes without reading low-level infrastructure docs first.
• - A platform engineer uses Signup Flow to hand product teams a self-serve control surface instead of a collection of shell commands.

Internal admin panels or CLI-only developer tooling

Agent OS gives teams a production-grade self-serve experience instead of forcing them to live in scripts and dashboards they built themselves.

• - A startup founder uses Marketplace UI to onboard an internal agent in minutes without reading low-level infrastructure docs first.
• - A platform engineer uses Marketplace UI to hand product teams a self-serve control surface instead of a collection of shell commands.

Internal admin panels or CLI-only developer tooling

Agent OS gives teams a production-grade self-serve experience instead of forcing them to live in scripts and dashboards they built themselves.

• - A startup founder uses Skill Detail Pages to onboard an internal agent in minutes without reading low-level infrastructure docs first.
• - A platform engineer uses Skill Detail Pages to hand product teams a self-serve control surface instead of a collection of shell commands.

Internal admin panels or CLI-only developer tooling

Agent OS gives teams a production-grade self-serve experience instead of forcing them to live in scripts and dashboards they built themselves.

• - A startup founder uses Developer Publishing UI to onboard an internal agent in minutes without reading low-level infrastructure docs first.
• - A platform engineer uses Developer Publishing UI to hand product teams a self-serve control surface instead of a collection of shell commands.

Internal admin panels or CLI-only developer tooling

Agent OS gives teams a production-grade self-serve experience instead of forcing them to live in scripts and dashboards they built themselves.

• - A startup founder uses Agent Dashboard to onboard an internal agent in minutes without reading low-level infrastructure docs first.
• - A platform engineer uses Agent Dashboard to hand product teams a self-serve control surface instead of a collection of shell commands.

Internal admin panels or CLI-only developer tooling

Agent OS gives teams a production-grade self-serve experience instead of forcing them to live in scripts and dashboards they built themselves.

• - A platform team uses Health Monitoring to spot degradation early and keep autonomous agent services online without manual babysitting.
• - A B2B SaaS team uses Health Monitoring to track incidents, queue pressure, and failover events from one operations console.

Datadog plus custom cron scripts and spreadsheets

Agent OS keeps operational coverage in the same product surface as agent execution, so the control plane and runtime stay aligned.

• - A platform team uses Alerting to spot degradation early and keep autonomous agent services online without manual babysitting.
• - A B2B SaaS team uses Alerting to track incidents, queue pressure, and failover events from one operations console.

Datadog plus custom cron scripts and spreadsheets

Agent OS keeps operational coverage in the same product surface as agent execution, so the control plane and runtime stay aligned.

• - A platform team uses Queue Management to spot degradation early and keep autonomous agent services online without manual babysitting.
• - A B2B SaaS team uses Queue Management to track incidents, queue pressure, and failover events from one operations console.

Datadog plus custom cron scripts and spreadsheets

Agent OS keeps operational coverage in the same product surface as agent execution, so the control plane and runtime stay aligned.

• - A platform team uses Task Scheduling to spot degradation early and keep autonomous agent services online without manual babysitting.
• - A B2B SaaS team uses Task Scheduling to track incidents, queue pressure, and failover events from one operations console.

Datadog plus custom cron scripts and spreadsheets

Agent OS keeps operational coverage in the same product surface as agent execution, so the control plane and runtime stay aligned.

• - A platform team uses Incident Timeline to spot degradation early and keep autonomous agent services online without manual babysitting.
• - A B2B SaaS team uses Incident Timeline to track incidents, queue pressure, and failover events from one operations console.

Datadog plus custom cron scripts and spreadsheets

Agent OS keeps operational coverage in the same product surface as agent execution, so the control plane and runtime stay aligned.

• - A platform team uses Failover Automation to spot degradation early and keep autonomous agent services online without manual babysitting.
• - A B2B SaaS team uses Failover Automation to track incidents, queue pressure, and failover events from one operations console.

Datadog plus custom cron scripts and spreadsheets

Agent OS keeps operational coverage in the same product surface as agent execution, so the control plane and runtime stay aligned.

• - A platform team uses Standby Capacity to spot degradation early and keep autonomous agent services online without manual babysitting.
• - A B2B SaaS team uses Standby Capacity to track incidents, queue pressure, and failover events from one operations console.

Datadog plus custom cron scripts and spreadsheets

Agent OS keeps operational coverage in the same product surface as agent execution, so the control plane and runtime stay aligned.

• - A platform team uses Agent Heartbeats to spot degradation early and keep autonomous agent services online without manual babysitting.
• - A B2B SaaS team uses Agent Heartbeats to track incidents, queue pressure, and failover events from one operations console.

Datadog plus custom cron scripts and spreadsheets

Agent OS keeps operational coverage in the same product surface as agent execution, so the control plane and runtime stay aligned.

• - A platform team uses Metrics Dashboard to spot degradation early and keep autonomous agent services online without manual babysitting.
• - A B2B SaaS team uses Metrics Dashboard to track incidents, queue pressure, and failover events from one operations console.

Datadog plus custom cron scripts and spreadsheets

Agent OS keeps operational coverage in the same product surface as agent execution, so the control plane and runtime stay aligned.

• - A platform team uses Usage Analytics to spot degradation early and keep autonomous agent services online without manual babysitting.
• - A B2B SaaS team uses Usage Analytics to track incidents, queue pressure, and failover events from one operations console.

Datadog plus custom cron scripts and spreadsheets

Agent OS keeps operational coverage in the same product surface as agent execution, so the control plane and runtime stay aligned.

• - A platform team uses Error Triage to spot degradation early and keep autonomous agent services online without manual babysitting.
• - A B2B SaaS team uses Error Triage to track incidents, queue pressure, and failover events from one operations console.

Datadog plus custom cron scripts and spreadsheets

Agent OS keeps operational coverage in the same product surface as agent execution, so the control plane and runtime stay aligned.

• - A platform team uses Audit Explorer to spot degradation early and keep autonomous agent services online without manual babysitting.
• - A B2B SaaS team uses Audit Explorer to track incidents, queue pressure, and failover events from one operations console.

Datadog plus custom cron scripts and spreadsheets

Agent OS keeps operational coverage in the same product surface as agent execution, so the control plane and runtime stay aligned.

• - A platform team uses Config Registry to spot degradation early and keep autonomous agent services online without manual babysitting.
• - A B2B SaaS team uses Config Registry to track incidents, queue pressure, and failover events from one operations console.

Datadog plus custom cron scripts and spreadsheets

Agent OS keeps operational coverage in the same product surface as agent execution, so the control plane and runtime stay aligned.

• - A platform team uses Release Gates to spot degradation early and keep autonomous agent services online without manual babysitting.
• - A B2B SaaS team uses Release Gates to track incidents, queue pressure, and failover events from one operations console.

Datadog plus custom cron scripts and spreadsheets

Agent OS keeps operational coverage in the same product surface as agent execution, so the control plane and runtime stay aligned.

• - A platform team uses Secret Rotation to spot degradation early and keep autonomous agent services online without manual babysitting.
• - A B2B SaaS team uses Secret Rotation to track incidents, queue pressure, and failover events from one operations console.

Datadog plus custom cron scripts and spreadsheets

Agent OS keeps operational coverage in the same product surface as agent execution, so the control plane and runtime stay aligned.

• - A platform team uses Feature Catalog to spot degradation early and keep autonomous agent services online without manual babysitting.
• - A B2B SaaS team uses Feature Catalog to track incidents, queue pressure, and failover events from one operations console.

Datadog plus custom cron scripts and spreadsheets

Agent OS keeps operational coverage in the same product surface as agent execution, so the control plane and runtime stay aligned.

• - A platform team uses Crew Orchestrator to spot degradation early and keep autonomous agent services online without manual babysitting.
• - A B2B SaaS team uses Crew Orchestrator to track incidents, queue pressure, and failover events from one operations console.

Datadog plus custom cron scripts and spreadsheets

Agent OS keeps operational coverage in the same product surface as agent execution, so the control plane and runtime stay aligned.

• - A research team uses Vercel Deployment to launch globally reachable agents without hiring an infrastructure team first.
• - A SaaS platform uses Vercel Deployment to absorb traffic spikes during product launches without manual scaling work.

Self-managed Kubernetes, Redis, and Postgres stacks

Agent OS uses modern managed infrastructure so teams get global scale and safer defaults without operating every moving part themselves.

• - A research team uses Supabase Backend to launch globally reachable agents without hiring an infrastructure team first.
• - A SaaS platform uses Supabase Backend to absorb traffic spikes during product launches without manual scaling work.

Self-managed Kubernetes, Redis, and Postgres stacks

Agent OS uses modern managed infrastructure so teams get global scale and safer defaults without operating every moving part themselves.

• - A research team uses Redis Caching to launch globally reachable agents without hiring an infrastructure team first.
• - A SaaS platform uses Redis Caching to absorb traffic spikes during product launches without manual scaling work.

Self-managed Kubernetes, Redis, and Postgres stacks

Agent OS uses modern managed infrastructure so teams get global scale and safer defaults without operating every moving part themselves.

• - A research team uses Docker Sandboxing to launch globally reachable agents without hiring an infrastructure team first.
• - A SaaS platform uses Docker Sandboxing to absorb traffic spikes during product launches without manual scaling work.

Self-managed Kubernetes, Redis, and Postgres stacks

Agent OS uses modern managed infrastructure so teams get global scale and safer defaults without operating every moving part themselves.

• - A fraud detection pipeline uses Multi-Stage Workflows to coordinate specialist agents and route high-risk cases through controlled review steps.
• - A content operations team uses Multi-Stage Workflows to schedule, test, and roll back agent behavior safely as traffic changes.

LangGraph workflows plus custom experimentation tooling

Agent OS connects orchestration, versioning, scheduling, and rollback into one runtime instead of leaving teams to stitch them together.

• - A fraud detection pipeline uses Reputation Weighting to coordinate specialist agents and route high-risk cases through controlled review steps.
• - A content operations team uses Reputation Weighting to schedule, test, and roll back agent behavior safely as traffic changes.

LangGraph workflows plus custom experimentation tooling

Agent OS connects orchestration, versioning, scheduling, and rollback into one runtime instead of leaving teams to stitch them together.

• - A fraud detection pipeline uses Cryptographic Proofs to coordinate specialist agents and route high-risk cases through controlled review steps.
• - A content operations team uses Cryptographic Proofs to schedule, test, and roll back agent behavior safely as traffic changes.

LangGraph workflows plus custom experimentation tooling

Agent OS connects orchestration, versioning, scheduling, and rollback into one runtime instead of leaving teams to stitch them together.

• - A fraud detection pipeline uses Agent Networks to coordinate specialist agents and route high-risk cases through controlled review steps.
• - A content operations team uses Agent Networks to schedule, test, and roll back agent behavior safely as traffic changes.

LangGraph workflows plus custom experimentation tooling

Agent OS connects orchestration, versioning, scheduling, and rollback into one runtime instead of leaving teams to stitch them together.

• - A fraud detection pipeline uses Skill Dependencies to coordinate specialist agents and route high-risk cases through controlled review steps.
• - A content operations team uses Skill Dependencies to schedule, test, and roll back agent behavior safely as traffic changes.

LangGraph workflows plus custom experimentation tooling

Agent OS connects orchestration, versioning, scheduling, and rollback into one runtime instead of leaving teams to stitch them together.

• - A fraud detection pipeline uses Skill Versioning to coordinate specialist agents and route high-risk cases through controlled review steps.
• - A content operations team uses Skill Versioning to schedule, test, and roll back agent behavior safely as traffic changes.

LangGraph workflows plus custom experimentation tooling

Agent OS connects orchestration, versioning, scheduling, and rollback into one runtime instead of leaving teams to stitch them together.

• - A fraud detection pipeline uses Skill Permissions to coordinate specialist agents and route high-risk cases through controlled review steps.
• - A content operations team uses Skill Permissions to schedule, test, and roll back agent behavior safely as traffic changes.

LangGraph workflows plus custom experimentation tooling

Agent OS connects orchestration, versioning, scheduling, and rollback into one runtime instead of leaving teams to stitch them together.

• - A fraud detection pipeline uses Webhook Support to coordinate specialist agents and route high-risk cases through controlled review steps.
• - A content operations team uses Webhook Support to schedule, test, and roll back agent behavior safely as traffic changes.

LangGraph workflows plus custom experimentation tooling

Agent OS connects orchestration, versioning, scheduling, and rollback into one runtime instead of leaving teams to stitch them together.

• - A fraud detection pipeline uses Scheduled Tasks to coordinate specialist agents and route high-risk cases through controlled review steps.
• - A content operations team uses Scheduled Tasks to schedule, test, and roll back agent behavior safely as traffic changes.

LangGraph workflows plus custom experimentation tooling

Agent OS connects orchestration, versioning, scheduling, and rollback into one runtime instead of leaving teams to stitch them together.

• - A fraud detection pipeline uses A/B Testing to coordinate specialist agents and route high-risk cases through controlled review steps.
• - A content operations team uses A/B Testing to schedule, test, and roll back agent behavior safely as traffic changes.

LangGraph workflows plus custom experimentation tooling

Agent OS connects orchestration, versioning, scheduling, and rollback into one runtime instead of leaving teams to stitch them together.

• - A recommendation agent uses mem_set to cache user context between requests without writing direct Redis code.
• - A fraud scoring agent uses mem_set to keep fast counters and temporary state during a live review window.

Raw Redis SDK calls in custom app code

Agent OS exposes memory operations behind agent-aware quotas, namespacing, and audit logging by default.

• - A recommendation agent uses mem_get to cache user context between requests without writing direct Redis code.
• - A fraud scoring agent uses mem_get to keep fast counters and temporary state during a live review window.

Raw Redis SDK calls in custom app code

Agent OS exposes memory operations behind agent-aware quotas, namespacing, and audit logging by default.

• - A recommendation agent uses mem_delete to cache user context between requests without writing direct Redis code.
• - A fraud scoring agent uses mem_delete to keep fast counters and temporary state during a live review window.

Raw Redis SDK calls in custom app code

Agent OS exposes memory operations behind agent-aware quotas, namespacing, and audit logging by default.

• - A recommendation agent uses mem_list to cache user context between requests without writing direct Redis code.
• - A fraud scoring agent uses mem_list to keep fast counters and temporary state during a live review window.

Raw Redis SDK calls in custom app code

Agent OS exposes memory operations behind agent-aware quotas, namespacing, and audit logging by default.

• - A recommendation agent uses mem_incr to cache user context between requests without writing direct Redis code.
• - A fraud scoring agent uses mem_incr to keep fast counters and temporary state during a live review window.

Raw Redis SDK calls in custom app code

Agent OS exposes memory operations behind agent-aware quotas, namespacing, and audit logging by default.

• - A recommendation agent uses mem_expire to cache user context between requests without writing direct Redis code.
• - A fraud scoring agent uses mem_expire to keep fast counters and temporary state during a live review window.

Raw Redis SDK calls in custom app code

Agent OS exposes memory operations behind agent-aware quotas, namespacing, and audit logging by default.

• - A compliance agent uses fs_write to store policy exports and signed reports in an isolated tenant path.
• - A document processing agent uses fs_write to read uploaded PDFs and write normalized outputs without direct bucket management.

Direct S3 or Blob storage SDK calls

Agent OS wraps storage with path safety, isolation, and audit trails so teams do not rebuild file governance themselves.

• - A compliance agent uses fs_read to store policy exports and signed reports in an isolated tenant path.
• - A document processing agent uses fs_read to read uploaded PDFs and write normalized outputs without direct bucket management.

Direct S3 or Blob storage SDK calls

Agent OS wraps storage with path safety, isolation, and audit trails so teams do not rebuild file governance themselves.

• - A compliance agent uses fs_list to store policy exports and signed reports in an isolated tenant path.
• - A document processing agent uses fs_list to read uploaded PDFs and write normalized outputs without direct bucket management.

Direct S3 or Blob storage SDK calls

Agent OS wraps storage with path safety, isolation, and audit trails so teams do not rebuild file governance themselves.

• - A compliance agent uses fs_delete to store policy exports and signed reports in an isolated tenant path.
• - A document processing agent uses fs_delete to read uploaded PDFs and write normalized outputs without direct bucket management.

Direct S3 or Blob storage SDK calls

Agent OS wraps storage with path safety, isolation, and audit trails so teams do not rebuild file governance themselves.

• - A compliance agent uses fs_mkdir to store policy exports and signed reports in an isolated tenant path.
• - A document processing agent uses fs_mkdir to read uploaded PDFs and write normalized outputs without direct bucket management.

Direct S3 or Blob storage SDK calls

Agent OS wraps storage with path safety, isolation, and audit trails so teams do not rebuild file governance themselves.

• - A compliance agent uses fs_stat to store policy exports and signed reports in an isolated tenant path.
• - A document processing agent uses fs_stat to read uploaded PDFs and write normalized outputs without direct bucket management.

Direct S3 or Blob storage SDK calls

Agent OS wraps storage with path safety, isolation, and audit trails so teams do not rebuild file governance themselves.

• - A pricing agent uses db_query to store quote history and retrieve past decisions during renewals.
• - A support analytics agent uses db_query to keep issue trends and resolution stats in a private schema.

Direct SQL clients and hand-built tenancy rules

Agent OS gives each agent a scoped database surface with validation and audit logging instead of open-ended shared SQL access.

• - A pricing agent uses db_transaction to store quote history and retrieve past decisions during renewals.
• - A support analytics agent uses db_transaction to keep issue trends and resolution stats in a private schema.

Direct SQL clients and hand-built tenancy rules

Agent OS gives each agent a scoped database surface with validation and audit logging instead of open-ended shared SQL access.

• - A pricing agent uses db_create_table to store quote history and retrieve past decisions during renewals.
• - A support analytics agent uses db_create_table to keep issue trends and resolution stats in a private schema.

Direct SQL clients and hand-built tenancy rules

Agent OS gives each agent a scoped database surface with validation and audit logging instead of open-ended shared SQL access.

• - A pricing agent uses db_insert to store quote history and retrieve past decisions during renewals.
• - A support analytics agent uses db_insert to keep issue trends and resolution stats in a private schema.

Direct SQL clients and hand-built tenancy rules

Agent OS gives each agent a scoped database surface with validation and audit logging instead of open-ended shared SQL access.

• - A pricing agent uses db_update to store quote history and retrieve past decisions during renewals.
• - A support analytics agent uses db_update to keep issue trends and resolution stats in a private schema.

Direct SQL clients and hand-built tenancy rules

Agent OS gives each agent a scoped database surface with validation and audit logging instead of open-ended shared SQL access.

• - A pricing agent uses db_delete to store quote history and retrieve past decisions during renewals.
• - A support analytics agent uses db_delete to keep issue trends and resolution stats in a private schema.

Direct SQL clients and hand-built tenancy rules

Agent OS gives each agent a scoped database surface with validation and audit logging instead of open-ended shared SQL access.

• - A market data agent uses net_http_get to poll exchange APIs without exposing the platform to unsafe internal addresses.
• - A procurement agent uses net_http_get to call vendor APIs while staying inside approved outbound domains.

Native fetch plus custom SSRF protection

Agent OS makes outbound calls policy-aware, rate-limited, and auditable instead of trusting raw network access.

• - A market data agent uses net_http_post to poll exchange APIs without exposing the platform to unsafe internal addresses.
• - A procurement agent uses net_http_post to call vendor APIs while staying inside approved outbound domains.

Native fetch plus custom SSRF protection

Agent OS makes outbound calls policy-aware, rate-limited, and auditable instead of trusting raw network access.

• - A market data agent uses net_http_put to poll exchange APIs without exposing the platform to unsafe internal addresses.
• - A procurement agent uses net_http_put to call vendor APIs while staying inside approved outbound domains.

Native fetch plus custom SSRF protection

Agent OS makes outbound calls policy-aware, rate-limited, and auditable instead of trusting raw network access.

• - A market data agent uses net_http_delete to poll exchange APIs without exposing the platform to unsafe internal addresses.
• - A procurement agent uses net_http_delete to call vendor APIs while staying inside approved outbound domains.

Native fetch plus custom SSRF protection

Agent OS makes outbound calls policy-aware, rate-limited, and auditable instead of trusting raw network access.

• - A market data agent uses net_dns_resolve to poll exchange APIs without exposing the platform to unsafe internal addresses.
• - A procurement agent uses net_dns_resolve to call vendor APIs while staying inside approved outbound domains.

Native fetch plus custom SSRF protection

Agent OS makes outbound calls policy-aware, rate-limited, and auditable instead of trusting raw network access.

• - A trading signal agent uses events_publish to publish alerts that downstream execution agents can subscribe to in real time.
• - A support workflow agent uses events_publish to hand off escalations between intake, routing, and resolution workers.

Custom Redis pub-sub wrappers or queue glue code

Agent OS turns events into a first-class agent primitive with isolation and operational visibility already attached.

• - A trading signal agent uses events_subscribe to publish alerts that downstream execution agents can subscribe to in real time.
• - A support workflow agent uses events_subscribe to hand off escalations between intake, routing, and resolution workers.

Custom Redis pub-sub wrappers or queue glue code

Agent OS turns events into a first-class agent primitive with isolation and operational visibility already attached.

• - A trading signal agent uses events_unsubscribe to publish alerts that downstream execution agents can subscribe to in real time.
• - A support workflow agent uses events_unsubscribe to hand off escalations between intake, routing, and resolution workers.

Custom Redis pub-sub wrappers or queue glue code

Agent OS turns events into a first-class agent primitive with isolation and operational visibility already attached.

• - A trading signal agent uses events_list_topics to publish alerts that downstream execution agents can subscribe to in real time.
• - A support workflow agent uses events_list_topics to hand off escalations between intake, routing, and resolution workers.

Custom Redis pub-sub wrappers or queue glue code

Agent OS turns events into a first-class agent primitive with isolation and operational visibility already attached.

• - A research agent uses proc_execute to run Python analysis code inside a time-limited sandbox.
• - A revenue operations agent uses proc_execute to schedule recurring reconciliation jobs and controlled child workflows.

Background workers plus ad hoc shell execution

Agent OS wraps process execution in time limits, isolation, scheduling hooks, and audit logs instead of raw worker access.

• - A research agent uses proc_schedule to run Python analysis code inside a time-limited sandbox.
• - A revenue operations agent uses proc_schedule to schedule recurring reconciliation jobs and controlled child workflows.

Background workers plus ad hoc shell execution

Agent OS wraps process execution in time limits, isolation, scheduling hooks, and audit logs instead of raw worker access.

• - A research agent uses proc_spawn to run Python analysis code inside a time-limited sandbox.
• - A revenue operations agent uses proc_spawn to schedule recurring reconciliation jobs and controlled child workflows.

Background workers plus ad hoc shell execution

Agent OS wraps process execution in time limits, isolation, scheduling hooks, and audit logs instead of raw worker access.

• - A research agent uses proc_kill to run Python analysis code inside a time-limited sandbox.
• - A revenue operations agent uses proc_kill to schedule recurring reconciliation jobs and controlled child workflows.

Background workers plus ad hoc shell execution

Agent OS wraps process execution in time limits, isolation, scheduling hooks, and audit logs instead of raw worker access.

• - A research agent uses proc_list to run Python analysis code inside a time-limited sandbox.
• - A revenue operations agent uses proc_list to schedule recurring reconciliation jobs and controlled child workflows.

Background workers plus ad hoc shell execution

Agent OS wraps process execution in time limits, isolation, scheduling hooks, and audit logs instead of raw worker access.