Mainline vs Temporal AI

Side-by-side comparison of features, pricing, and ratings

Analysis reviewed Live tool data as of 2026-10-18
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At a glance

DimensionMainlineTemporal AI
PricingFree (open source Git-native tool)Cloud free tier + usage-based billing (see latest news)
Primary UseGit-native intent memory for coding agentsDurable execution for reliable AI agents & workflows
Key FeatureIntent records in Git refs/notes, agent hooks, conflict detectionAutomatic state capture & recovery, retries, visibility UI
Best ForAI-heavy engineering teams using multiple coding agentsTeams building crash-resistant AI agents & long-running processes
Integration HighlightsGitHub, Codex, Claude Code, Cursor, Copilot, WindsurfOpenAI Agents SDK, Google ADK, Slack, AWS, Azure
Latest NewsMultilingual site + new essays on repo memory (2026-05-04)Usage-based billing launched (2026-06-25), Custom Roles pre-release

Choose Temporal if you need to orchestrate AI agents or multi-step workflows that must survive failures without losing state—it's built for durability at scale. Choose Mainline if your biggest pain point is coding agents forgetting context or decisions; Mainline embeds intent directly into Git, making it a lightweight fit for agent-heavy teams that already live in Git. They solve different problems: Temporal is a runtime platform, Mainline is a memory layer.

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Mainline
Mainline

Mainline is Git-native agent memory: coding agents save developer intent and decisions as Git refs and notes so the next agent inherits

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Temporal AI
Temporal AI

Durable execution platform that keeps AI agents and long-running workflows alive through crashes, retries, and abandoned sessions.

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Pricing
Freemium
Freemium
Plans
$0/mo
Planned
Planned
$150 credits for 90 days
Starting at $50 per million actions
Greater of $500/mo or 10% of usage
Custom
Popularity
2 views
7.5k views
Skill Level
Intermediate
Advanced
API Available
Platforms
CLI
WebAPI
Categories
💻 Code & Development🧠 Agent Memory & Runtimes
🕸️ Agent Frameworks & Orchestration⚙️ Developer Infrastructure
Features
Stores developer intent records as Git refs and notes inside your repo
Human CLI: mainline preflight --json, start, append, and seal
Inspection CLI: mainline hub open, log, show <intent_id>, and gaps
Agent protocol: mainline context --current --json, start, append, seal
Agent hooks pull repo intents into context at task start and before handoff
Skill framework teaches agents when to read, when to write, and when to stop for human judgment
Records tried-and-abandoned approaches so future agents skip dead ends
Detects logic conflicts from recorded intent before they become Git conflicts
Annotates high-risk code traps and module constraints before an agent edits
Shows reviewers the original goal, reasoning path, and key decisions behind a diff
Intent travels through fetch, branch, merge, and fork without a separate database
mainline init --actor-name writes .mainline/config.toml, configures Git refs, creates an actor identity, installs agent
mainline doctor --setup verifies the install; installer checks the GitHub Release archive against checksums
Live self-dogfooded Hub (272 intents, 236 merged, 4 proposed as of Jun 19, 2026)
Public site available in English, Chinese, and Spanish
Durable execution captures Workflow state at every step with no checkpointing or recovery code
Native SDKs for Go, Java, Python, TypeScript, .NET, PHP, Ruby, and Rust
Activities retry automatically with backoff, four timeout classes, and heartbeating
Signals, Queries, and Updates read and mutate running Workflows mid-flight
Workflow Streams for real-time interactivity with running executions
Durable AI agents via OpenAI Agents SDK and Google ADK running LLM and tool calls as Activities
Serverless Workers host durable AI agents on Amazon Bedrock AgentCore
Serverless Workers on AWS Lambda (public preview) and GCP Cloud Run (pre-release)
Standalone Activities as a durable job-queue pattern, GA across six SDKs (2026-09-15)
Native Task Queue priority and fair distribution without a custom queueing layer
Durable Timers sleep for months; cron Schedules support backfill and Continue-As-New
Saga pattern via compensating transactions that read like try/catch
Worker Versioning pins Workflows to a version so deploys don't corrupt in-flight runs
Cloud UI Strict Session Mode enforces 15-min inactivity timeout and 12-hour max session (GA 2026-09-18)
Replay tests validate against real histories; time-skipping tests fast-forward long timers in CI
Integrations
GitHub
Codex
Claude Code
Cursor
GitHub Copilot
Windsurf
OpenAI Agents SDK
Google ADK
AWS Lambda
Google Cloud Run
Amazon Bedrock AgentCore
Kubernetes
GitHub Actions
GCP Marketplace
Azure

Who should pick which

  • AI agent developer building reliable multi-step agents
    Pick: Temporal AI

    Temporal's durable execution ensures agents survive crashes and retries automatically, with visibility UI and human-in-the-loop—exactly what you need for production AI agents.

  • Engineering team using multiple coding agents (Codex, Claude, Cursor)
    Pick: Mainline

    Mainline stores intent directly in Git, so every agent understands past decisions and avoids dead ends—essential for teams where agent context keeps getting lost.

  • Developer automating long-running financial workflows
    Pick: Temporal AI

    Temporal's Saga pattern, compensating transactions, and automatic retries make it ideal for financial systems that require exactly-once execution and rollback.

  • Team reviewing AI-generated code changes
    Pick: Mainline

    Mainline's 'review behind intent' shows the original goal, reasoning, and key decisions behind every diff, making code reviews faster and more informed.

Frequently Asked Questions

Mainline vs Temporal AI: which should you choose?

Choose Temporal if you need to orchestrate AI agents or multi-step workflows that must survive failures without losing state—it's built for durability at scale. Choose Mainline if your biggest pain point is coding agents forgetting context or decisions; Mainline embeds intent directly into Git, making it a lightweight fit for agent-heavy teams that already live in Git. They solve different problems: Temporal is a runtime platform, Mainline is a memory layer.

Can Mainline work without a cloud service?

Yes, Mainline is fully local and Git-native; all data stays in your repo. Team Cloud is planned but not yet available.

Does Temporal require a specific programming language?

Temporal provides SDKs for Python, Go, TypeScript, Ruby, C#, Java, PHP, and Rust (public preview)—most major languages are supported.

Which tool is better for simple cron jobs?

Neither is ideal. Temporal is overkill and Mainline doesn't schedule tasks. For simple cron, use a traditional scheduler.

Can Mainline integrate with GitHub Copilot?

Yes, integration docs for GitHub Copilot are listed, along with Codex, Claude Code, Cursor, and Windsurf.

Does Temporal support human-in-the-loop workflows?

Yes, via signals, pause/resume, and the Saga pattern for compensating transactions—Temporal is built for human oversight.

Is Mainline suitable for non-Git version control systems?

No, Mainline is designed specifically for Git. Teams using other VCS tools would not benefit.

What does Temporal's usage-based billing mean?

Introduced in June 2026, it charges based on billable actions (e.g., workflow runs, activities). Use the Billable Action Count metric to optimize.

Can I use Temporal for stateless microservices?

Not recommended. Temporal is for stateful, long-running workflows; stateless request-response patterns are better served by traditional APIs.

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Explore each tool further

Mainline
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Temporal AI
View Temporal AI reviewTemporal AI alternatives

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Last reviewed: July 5, 2026