Coding Agents

Trust every action your coding agents ship

Power agents with live and historic runtime evidence to simulate changes, verify behavior, investigate issues, and ship custom code with confidence.

Trusted by engineering teams at Fortune 500s

Inline Runtime Context for AI Coding Agents | Lightrun
Inline Runtime Context for AI Coding Agents | Lightrun
Inline Runtime Context for AI Coding Agents | Lightrun
Inline Runtime Context for AI Coding Agents | Lightrun
Inline Runtime Context for AI Coding Agents | Lightrun
Inline Runtime Context for AI Coding Agents | Lightrun

AI cannot solve
what it cannot see

Agents generate code faster than anyone can verify it. Reliability now depends on showing them how that code actually runs.

Code is shipping faster than teams can approve it

Agents are generating code at a pace no manual process can match. Verification has become the bottleneck.

Observability was built for human engineering

Observability shows what happened, but agents need a live feedback loop as they plan their next steps.

The missing layer is code-level runtime context

Give agents secure access to live and historic runtime evidence, so they can act on facts instead of assumptions.

AI is accelerating engineering. Now make every action reliable.

Instrument any line of code, on demand

Agents drop dynamic telemetry (logs, metrics, traces, and snapshots) on any line to investigate live behavior, with no restart required to collect data.

Harness an investigative runtime memory

Agents query stored execution history, comparing live behavior to a baseline to catch what changed and why.

See everything, change nothing

Agents run sandboxed, read-only instrumentation that cannot change application state or control flow.

Power every workflow
with live runtime truth

Deterministic engineering, where your AI validates its every decision in live runtime context.

Will this dependency break on deploy?
Did this branch execute at all last week?
What's the live value of this variable?
Has this error happened before?
What's causing this latency spike?
What changed here since the last deploy?
Is this cache key actually used?

New skills for your agents

Upgrade your agent workflows with expert techniques and runtime evidence.

Runtime-aware PR review

Simulate how a PR will behave before it ships

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Live runtime debugging

Debug production issues without redeploying

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Error remediation

Turn error alerts into verified fixes

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Slow execution diagnosis

Pinpoint why code runs slow in production

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See what your teams' agentic engineering can look like

Connect your AI agents and IDEs to the runtime sensor's execution data, so every change is designed and tested against real system behavior.

Build code that fits your system

Show coding agents real execution paths, dependencies, and runtime history, so the code they write and validate fits the existing system.

Base designs on real user flows, service interactions, and error patterns
Expose dependencies hidden from source code
Prevent rework caused by incorrect assumptions
real execution path hidden dependency hidden

Understand each change's impact

Let agents simulate the impact of proposed changes using live and baseline runtime evidence before deployment.

Map impact across functions and services
Surface edge cases absent from test environments
Confirm each ticket is fully resolved
proposed change edge case

Validate each release under real traffic

Agents verify service execution, inspect request flows, and compare new behavior with established baselines as changes enter production, catching anomalies before users feel them.

Detect regressions during rollout
Trace deviations to the affected function and code paths
Confirm deployed behavior remains within its baseline
baseline

Find what changed and why

Autonomous investigations combine application behavior with full operational context across the stack to prove the cause of deviations.

Correlate alerts and telemetry with deployments, code, and infrastructure changes
Compare the failing flow with historical healthy behavior
Trace the failure to the exact execution path
alerts telemetry changes

Fix the issue, then confirm it holds

Give agents the proven root cause and full system architecture context to generate a fix, then verify it against the exact conditions that caused the failure.

Generate a fix grounded using precise evidence
Test fix against the triggering conditions
Confirm normal behavior is restored
root cause generated fix

Power your workflows with your software's runtime context

Connect Lightrun to coding agents, development environments, your source-control and observability stack, and incident workflows.

Inline Runtime Context for AI Coding Agents | Lightrun
IntelliJ IDEA
Inline Runtime Context for AI Coding Agents | Lightrun
Inline Runtime Context for AI Coding Agents | Lightrun
Inline Runtime Context for AI Coding Agents | Lightrun
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Secure by design. Enterprise-grade.

Securely supporting the largest companies in the world across regulated industries

Inline Runtime Context for AI Coding Agents | Lightrun Inline Runtime Context for AI Coding Agents | Lightrun Inline Runtime Context for AI Coding Agents | Lightrun Inline Runtime Context for AI Coding Agents | Lightrun
Enterprise Compliance ISO 27001 and SOC 2 Type II certified with GDPR and HIPAA alignment. Full RBAC, SSO, and audit logging.
Tenant Isolation Logical tenant separation, dedicated secret storage & fully isolated AI sandboxes.
End-to-End Encryption TLS 1.3 in transit and AES-256 encryption at rest, backed by AWS KMS with annual key rotation.
Read-only by default Agents investigate and correlate data, but write actions require explicit approval.
Data Privacy Controls Configurable retention, PII redaction, prompt sanitization, and zero AI provider data retention.
IP & AI Protection No source code storage, no model training on customer data, and strict execution guardrails.
Explore security

Days hours

“When it comes to priority-one tickets, customers can't wait days for a fix. Lightrun helps us reduce that to hours.”

Hood Munaim, SVP, Head of Product Engineering

90% lower MTTR

AT&T reduced time to resolve incidents from five hours to thirty minutes, avoiding costly war rooms.

Enterprise incident response

+30% productivity

Priceline increased developer productivity across workflows spanning more than 2,000 services.

Enterprise engineering productivity

“The unique solutions that Lightrun is developing dramatically impact how developers operate”

+260 hours

Taboola saved 260 engineering hours monthly by cutting manual reproductions

Enterprise incident response

Weeks saved

"Lightrun provided an efficient approach to tackling complex issues in production"

Enterprise efficiency

Light up

how your software runs

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