Alloy vs Cursor
Alloy vs Cursor
Cursor is built for working with code. Alloy is built for understanding robot behavior across missions, fleets, and releases.
Investigate in Alloy. Hand engineering the evidence. Fix in Cursor. Check the next missions in Alloy.
Alloy
Alloy helps robotics teams investigate what happened before engineering has to step in, then gives engineers the evidence and context to go deeper in Cursor. Support and validation can work through the same findings in Alloy or Slack, so escalation starts with a useful handover instead of a symptom.
Choose Alloy when engineers are being pulled into first-line evidence gathering, handovers arrive without enough context, or the same investigation needs to be repeated after every release.
Cursor
Cursor is a coding-agent platform for understanding codebases, building features, debugging, testing, and reviewing changes. Its editor, CLI, cloud agents, automations, and MCP integrations support both interactive work and background workflows.
Choose Cursor when the work centers on changing software and your team has the data and tools needed to investigate it.
Alloy and Cursor compared
| What matters | Alloy | Cursor |
|---|---|---|
| Primary job | Investigate robot behavior across missions | Build, debug, test, and review software |
| Starting context | Recordings, telemetry, mission history, reports | Codebases, diffs, rules, terminals, connected tools |
| Fleet investigation | Mission search, replay, comparisons, source-linked analysis | Scripts and connected data tools, including Alloy via MCP |
| Reusable work | Reports and Scenarios tied to mission data | Rules, skills, automations, and persistent automation notes |
| Recurring checks | Scenarios across past missions and future uploads | Scheduled and event-driven agent workflows |
| What the next person gets | A supported investigation and better handover for support, validation, and engineering | Code changes, tests, artifacts, and pull requests |
| Working together | Supply field evidence and follow-up mission analysis | Use that evidence to investigate and implement fixes |
Accelerate the investigation engineering would otherwise have to do
By the time an issue reaches engineering, the first job is often not changing code. It is figuring out what actually happened: finding the right run, checking the relevant signals, comparing it with successful missions, and working out whether the problem is isolated or systemic.
Alloy accelerates that investigation before and after escalation. It finds the affected missions, compares successful runs, and keeps the supporting signals together. When engineering needs to go deeper, its MCP server brings the evidence into Cursor alongside the codebase.
The evidence stays available as the question changes. Queries run against the recordings in Mesh Storage and return the relevant results to Cursor. Engineers can dig deeper without downloading a fresh set of logs for every hypothesis.
Give engineering a better handover
A weak escalation gives engineering a symptom and makes the engineer reconstruct the investigation from scratch. A good handover gives them the question, the evidence already gathered, what has been ruled out, and a clear place to continue.
Alloy gives the team a shared investigation before the handover. Support and validation can explore interactive plots, inspect the supporting missions, and ask follow-ups in Alloy or Slack. When engineering takes over, the evidence and investigation so far come with the issue instead of being recreated.
The explanation outlasts the session. Alloy remembers reusable engineering context across conversations, building a shared knowledge base your team can inspect and correct. The next teammate can pick up the investigation with both the context and the evidence.
Keep learning after the fix ships
A passing test is one part of the answer. Your team still needs to know whether the change improved behavior in the field and whether the failure returns under different conditions.
Alloy compares releases and checks new missions for known failure patterns. Scenarios turn an investigation into a check that keeps running. Configured Slack support triggers can also start first-line investigation when a case is assigned or escalated, so evidence gathering begins before an engineer opens the editor.
Cursor Automations can run scheduled and event-driven work. Alloy supplies the robot data and recurring mission analysis those coding workflows can draw on.
One loop, from field evidence to software improvement
For a navigation problem that appears after a release:
Find affected and successful missions, compare conditions, and preserve the supporting signals in a report.
Retrieve the Alloy evidence through MCP, trace it into the code, and prepare a tested, reviewable change.
Compare new missions and use a Scenario to check whether the pattern returns.
The next release gives your team new evidence. Alloy makes it part of the investigation.
When to choose Alloy or Cursor
Choose Alloy if
- Engineers spend too much time finding and preparing recordings before debugging can begin.
- The answer requires comparing missions, robots, conditions, or releases.
- Support and validation need to do more of the first-line investigation themselves and hand engineering better evidence when they escalate.
- You want recurring robot-data analysis delivered as a product rather than maintaining the platform yourself.
Choose Cursor first if
- Your bottleneck is writing, understanding, testing, or reviewing code.
- Relevant data is already indexed and accessible through trusted internal tools.
- Your team already operates mission capture, historical search, replay, and recurring checks.
- You want a bespoke workflow and are prepared to own its integrations and maintenance.
What changes for robotics teams
Advanced Navigation
A day of analysis became ten minutes
With Alloy, Advanced Navigation reduced field-test analysis and reporting from about a full day to about ten minutes. Weekly validation capacity increased from roughly two tests to ten, and data-supported customer responses moved from one or two days to the same day.
Read the Advanced Navigation story →DroneForge
From fleet investigation to product improvement
With four employees and more than 300 drones, DroneForge uses Alloy alongside a coding agent to connect what happens in the field to what changes in the product. Alloy modeled remaining flight time from historical battery data; Codex helped implement the model in the application. Recurring Alloy reports then compared those estimates against later flights, carrying the loop from investigation to software change to field verification.
Read the DroneForge story →Questions teams ask before adding Alloy
What does Alloy add if we already use Cursor?
Cursor gives engineers a powerful place to understand and change software. Alloy gives that work the robotics context around it: connected mission history, robot data, evidence, recurring checks, shared investigations, and support workflows. Engineers can pull that context into Cursor through MCP instead of rebuilding it for every incident.
Why not just connect Cursor to our robot data ourselves?
You can. The question is whether your team wants to build and maintain the system around the agent: data capture and access, fleet search, mission context, evidence links, recurring analysis, shared handovers, model routing, evaluations, and integrations. Alloy is that maintained robotics investigation system, with engineers helping fit it to your workflow.
What happens before engineering gets involved?
Alloy can start the first-line investigation before an engineer opens Cursor. Support or validation can identify the relevant missions, inspect the signals, compare against previous incidents, and gather the evidence around the issue. When engineering takes over, it starts with a supported investigation instead of a symptom and a pile of logs.
What happens after the engineer ships the fix?
The investigation does not end at the pull request. Alloy can compare later missions, check whether the behavior improved, and turn a useful investigation into a Scenario that runs across future uploads. The loop becomes: investigate the field, change the software, then verify the result on real robots.
Does Alloy get better as our team uses it?
Yes. Useful engineering context, previous findings, investigation methods, and recurring checks stay available to the team. The next investigation can build on what the last one discovered, and colleagues can inspect and correct the shared knowledge rather than relying on one engineer to remember how the system behaves.
Does Alloy replace Cursor or our existing data stack?
No. Cursor can remain where engineers build and debug software. Alloy can connect to existing sources such as S3 and ClickHouse, work alongside replay tools, and expose its robot-data capabilities back into Cursor through MCP. Alloy owns the investigation layer around robot behavior; your team keeps the tools it already likes.
How should we evaluate Alloy alongside Cursor?
Use one real incident that pulled an engineer into evidence gathering or diagnosis. Measure time to a supported explanation, how much investigation support or validation can complete before escalation, the quality of the handover into engineering, and how easily the team can check future missions after the fix ships.
Bring us one incident that pulled an engineer off the roadmap
Choose a recent robot issue that pulled a senior engineer into evidence gathering or diagnosis. Walk through it with Alloy and Cursor: let Alloy do the first-line investigation and assemble the handover, then use Cursor for the engineering work and Alloy to check future runs.
