Agents Never Sleep vs Fullstory: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Agents Never Sleep and Fullstory — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Agents Never Sleep
Agents Never Sleep
A tiny $4.99 Mac menu bar app that keeps long-running AI agents alive with the laptop lid closed, using one three-level slider.
Key features
- Closed-Lid Operation: Keeps agents and background jobs running with the MacBook lid shut, which the built-in caffeinate command cannot do.
- Three-Level Slider: One control with Sleepy, Awake, and Never sleeps settings, so changing sleep behavior takes a single drag rather than a terminal command.
- Menu Bar Only: Lives entirely in the menu bar with no window, dock icon, or configuration screens to manage.
- Native and Tiny: A small native macOS binary rather than a wrapped web app, minimizing overhead on a machine already running agents.
- Zero Data Collection: No telemetry, analytics, or tracking; what runs on the machine stays on the machine.
- Safe Revert: Toggling back down restores normal sleep behavior, avoiding the common mistake of leaving sudo pmset -a disablesleep 1 permanently enabled.
- No-Questions Refund: A 14-day money-back guarantee with no form to fill in and no reason required.
Best for
- Overnight Agent Runs: Letting a coding agent work through a long task while the laptop is closed and put away.
- Long Builds and Tests: Preventing a multi-hour build, test suite, or data job from being interrupted mid-run by sleep.
- Mobile Working: Carrying a MacBook between rooms or offices without propping the lid open to keep a job alive.
- Model Downloads and Training: Keeping large model downloads or local fine-tuning runs going unattended.
- Avoiding pmset Mistakes: Replacing manual sudo pmset toggles that are easy to enable and easy to forget to undo.
- Remote Sessions: Keeping a Mac reachable and working for a remote session or background service while it sits closed on a desk.
Fullstory
FullStory
Behavioral data platform that records user sessions and surfaces sentiment and insights to improve product experience.
Key features
- Session Replay: Continuously records user sessions (clicks, scrolls, page transitions, input) into replayable, timestamped videos with direct links to review exact user interactions for debugging and UX analysis.
- Behavioral Event Capture: Captures rich event streams and structured custom events with properties and schemas, enabling teams to track actions, attributes, and conversion steps across web and mobile.
- SDKs & APIs: Provides official Browser, NodeJS, and mobile SDKs plus HTTP/server APIs for initializing capture, tracking custom events, creating users/events, and programmatic access to session and segment data.
- Searchable Segments & Event Querying: Lets users search and filter sessions by custom event properties, user attributes, and behavior to build segments of users who experienced specific flows or issues.
- Warehouse & Data Integration: Offers tooling and packages (including an official dbt package and export utilities) to move FullStory events into data warehouses and integrate behavioral data into BI workflows.
- Privacy Controls & Data Governance: Includes privacy and masking controls, allowlists/deny-lists, and per-session privacy settings to protect sensitive user data while still collecting actionable behavioral signals.
- Developer Tooling & Middleware: Supplies middleware (e.g., Segment middleware), SPA-friendly browser SDKs, and client/server libraries to simplify integration into single-page apps, mobile apps, and analytics stacks.
- Session replay capturing full user interactions (clicks, scrolls, inputs) for playback
- Custom event tracking with schema overrides and searchable events
- Browser SDK (@fullstory/browser) with init() and FullStory global/API (FS) usage
- Server-side NodeJS SDK for server-to-server HTTP API calls (users, events, batch import jobs)
- Mobile SDKs and mobile-specific APIs (iOS, Android, React Native)
- HTTP APIs and developer documentation for capturing data, retrieving sessions, and managing privacy
- Integrations and middleware (e.g., Segment middleware for Android) to forward events and embed replay links
- Data export and warehouse integrations (Anywhere: Warehouse) and a dbt package for downstream analytics
- Real-time activation integrations (Anywhere: Activation) for driving experiences
- Privacy controls and mobile-only methods (setting/removing attributes, resetting idle timer, class management)
Best for
- Bug reproduction and triage: Engineers and QA replay exact user sessions to reproduce errors, observe the sequence of actions leading to a bug, and correlate with console or custom event data.
- Conversion funnel optimization: Product teams identify where users drop off in multi-step flows by filtering sessions and events, then iterating on UX changes informed by real behavior.
- Product research and UX validation: Researchers observe real user interactions and sentiment patterns to validate hypotheses, discover friction points, and prioritize features or design changes.
- Analytics enrichment and BI: Data teams export FullStory events to warehouses using the dbt package and export utilities to join behavioral data with product and transactional datasets for deeper analysis.
- SPA and mobile instrumentation: Developers integrate the FullStory Browser SDK or mobile SDKs (and Segment middleware) to ensure accurate session capture in single-page apps and native mobile applications.
- Customer support augmentation: Support teams attach session replay links to tickets, quickly see what a user experienced, and provide faster, more context-aware resolutions.
- Feature rollout monitoring: Product and engineering monitor adoption and unexpected behaviors after releases by tracking custom events and segmenting affected sessions or cohorts.
- Product analytics and feature usage measurement via custom events and properties
- UX research and usability testing using session replay to reproduce user flows and issues
- Customer support and troubleshooting by locating sessions that match search criteria and viewing replays
- Conversion funnel analysis by correlating events and session behaviors
- Data engineering and analytics: exporting FullStory events to data warehouses and modeling with dbt
- Real-time personalization and activation by integrating FullStory session context into downstream systems
- Server-to-server automation for user and event management using the NodeJS SDK and HTTP APIs