Best AI engineering tools

EditionSeptember 2026

Best AI stack for engineering, ranked by effect on the work, with the risk read beside each one.

Oximy ResearchUpdated 19 September 20263 min read

TL;DR

  1. 01Choose one primary coding assistant before adding another tool with the same repository access.
  2. 02Keep tests and human pull-request approval between generated code and production.
  3. 03Use review and security tools for distinct checks, with clear ownership for findings.
  4. 04Measure cycle time, review turnaround, escaped defects and remediation time.

We picked these tools for engineering leaders managing coding, review, security, incidents, production issues, and planned work.

The stack at a glance

Recommended tools with level, Oximy grade, and training
#ToolGrade
1CursorCursorA
2Claude CodeClaude CodeA
3GitHub CopilotA+
4CodeRabbitCodeRabbitA+
5GraphiteGraphiteA
6SnykSnykA+
7Sentry with SeerSentry with SeerB-
8LinearLinearA

Oximy grade and training readings are shown on the assessment date. We do not show prices: vendor pricing is mostly quote-only, and we print a number only with a source and a date.

The recommended tools

In rank order. Named customers come from the vendor's own published stories, which we opened and checked. They show the tool is used for that job, not that it worked.

Cursor

Rank 01

Cursor

Workflow tools
A

Cursor reads codebases and completes multi-file tasks from its editor.

What it should move: it shortens the path from an issue to a reviewable change.

Best fit

  • It fits teams with tests, disciplined reviews, and written repository instructions.
  • Box uses Cursor for code guardrails, tests and large codebase migrations.[1]
  • Vercel uses Cursor to build and test event-streaming infrastructure against cloud environments.[2]

The catch

Cursor sends code context to model services and can change many files. Teams must control data settings, diffs, and commands.

Trains on your data: No training on user dataIncidents: 3
SOC 2ISO 27001GDPRHIPAAAIUC-1ISO 42001

Assessed SEP 21, 2026

Claude Code

Rank 02

Claude Code

Workflow toolsAnthropic
A

Claude Code inspects repositories, edits code, and runs commands from the terminal.

What it should move: engineers spend less time implementing changes, writing tests, and maintaining codebases.

Best fit

  • It fits teams with reliable tests, scoped permissions, and written repository rules.
  • Rakuten uses Claude Code for tests, API mocks, refactoring, bug fixes and documentation.[3]
  • Ramp uses Claude Code for application development, internal tools and incident investigation.[4]

The catch

Claude Code can read files and run commands. Limit access to repositories and secrets, set command permissions, and review changes before wider use.

Trains on your data: Free: Yes, Paid: NoIncidents: 7
SOC 2ISO 27001GDPRHIPAACSA STARISO 27017ISO 27018

Assessed SEP 21, 2026

Rank 03

GitHub Copilot

Workflow toolsGitHub
A+

GitHub Copilot suggests code, explains repositories, and reviews changes.

What it should move: it shortens implementation, reviews, and repetitive coding work.

Best fit

  • It fits teams that want assistance inside GitHub's source control and reviews.
  • ASOS uses GitHub Copilot to navigate codebases, prepare features and conduct initial code reviews.[5]
  • Duolingo uses GitHub Copilot for code consistency, boilerplate and routine engineering work.[6]

The catch

Generated code can repeat insecure or unsuitable patterns. Teams still need repository rules, licence checks, tests, and pull-request approval.

Trains on your data: Free: Yes, Paid: NoIncidents: 2
SOC 2ISO 27001GDPR

Assessed SEP 21, 2026

CodeRabbit

Rank 04

CodeRabbit

Workflow tools
A+

CodeRabbit reviews pull requests for defects, policy issues, and code quality.

What it should move: it shortens reviews and catches basic defects before merge.

Best fit

  • It fits teams with documented coding rules that want an automated first review.
  • Abnormal AI uses CodeRabbit for automated code review and policy checks across generated and human-written changes.[7]
  • LeoLabs uses CodeRabbit for pull-request feedback, edge-case review and security checks.[8]

The catch

Automated review comments can create noise or false confidence. Set repository permissions and review policies, and assign responsibility for merging changes.

Trains on your data: No training on user dataIncidents: 1
SOC 2ISO 27001GDPRHIPAA

Assessed SEP 21, 2026

Graphite

Rank 05

Graphite

Workflow tools
A

Graphite manages stacked pull requests across dependent code changes.

What it should move: it shortens review cycles and time from completed code to merge.

Best fit

  • It fits teams that split changes into small, dependent pull requests.
  • Shopify uses Graphite for stacked pull requests and code review workflows.[9]

The catch

Engineers must learn the stacked-change process. Teams must agree on branch rules and fallback Git workflows.

Trains on your data: No training on user dataIncidents: 0
SOC 2GDPR

Assessed SEP 21, 2026

Snyk

Rank 06

Snyk

Workflow tools
A+

Snyk finds vulnerabilities in code, dependencies, containers, and infrastructure definitions.

What it should move: it shortens remediation and finds more security issues before release.

Best fit

  • It fits teams that assign findings inside repositories and delivery pipelines.
  • Salesforce uses Snyk to scan repositories for open-source vulnerabilities during software review.[10]
  • Pearson uses Snyk for automated dependency scanning across application development.[11]

The catch

Scanning can create a large backlog. Teams need rules for access, false positives, priorities, and remediation owners.

Trains on your data: No training on user dataIncidents: 0
SOC 2ISO 27001GDPR

Assessed SEP 21, 2026

Sentry with Seer

Rank 07

Sentry with Seer

Systems of recordSentry
B-

Seer connects production errors to code context, causes, and proposed fixes.

What it should move: it shortens the path from a production error to a reviewable fix.

Best fit

  • It fits teams that want investigations based on telemetry, releases, and source maps.
  • Bolt uses Sentry Seer to investigate errors and provide context to coding agents preparing fixes.[12]
  • Factory uses Sentry Seer to give production error context to agents that triage issues and draft fixes.[13]

The catch

Telemetry can contain customer and operations data. Control access and retention, and require engineers to review proposed fixes.

Trains on your data: YesIncidents: 9
SOC 2ISO 27001GDPRHIPAAData Privacy Frameworkhipaa_attestationgdpr_compliant

Assessed SEP 21, 2026

Linear

Rank 08

Linear

Systems of record
A

Linear stores engineering issues, projects, roadmaps, and delivery status.

What it should move: teams resolve issues sooner, keep backlogs clear, and coordinate releases.

Best fit

  • It fits teams that want one issue and project record for development work.
  • Automattic uses Linear for product roadmaps, cross-team execution and bug triage.[14]
  • Retool uses Linear to manage engineering work, triage issues and connect customer feedback to quality tasks.[15]

The catch

Linear cannot fix unclear priorities or large backlogs. Assign owners for issue migration, project workflows, and connections to development tools.

Trains on your data: No training on user dataIncidents: 2
SOC 2ISO 27001GDPRHIPAA

Assessed SEP 21, 2026

Where to start

Developers work mainly in editors

Compare Cursor and GitHub Copilot on your repositories, languages, and review process.

Developers work mainly in terminals

Use Claude Code for scoped tasks where engineers can review commands, tests, and file changes together.

Pull requests wait for review

Use CodeRabbit for the first review, and use Graphite when dependent pull requests create delays.

Incidents take too much time

Connect Sentry context to code, but keep diagnosis and production changes inside your incident and review process.

Questions

References

  1. 01Box: how it uses CursorCursorVendor-published
  2. 02Vercel: how it uses CursorCursorVendor-published
  3. 03Rakuten: how it uses Claude CodeAnthropicVendor-published
  4. 04Ramp: how it uses Claude CodeAnthropicVendor-published
  5. 05ASOS: how it uses GitHub CopilotGitHubVendor-published
  6. 06Duolingo: how it uses GitHub CopilotGitHubVendor-published
  7. 07Abnormal AI: how it uses CodeRabbitCodeRabbitVendor-published
  8. 08LeoLabs: how it uses CodeRabbitCodeRabbitVendor-published
  9. 09Shopify: how it uses GraphiteGraphiteVendor-published
  10. 10Salesforce: how it uses SnykSnykVendor-published
  11. 11Pearson: how it uses SnykSnykVendor-published
  12. 12Bolt: how it uses Sentry with SeerSentryVendor-published
  13. 13Factory: how it uses Sentry with SeerSentryVendor-published
  14. 14Automattic: how it uses LinearLinearVendor-published
  15. 15Retool: how it uses LinearLinearVendor-published
See Oximy for Engineering teams