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Anticipate and fix bugs with Devin and Swiftask

Stop letting bugs slow down your production. Swiftask orchestrates Devin to identify, analyze, and propose fixes in real time.

Result:

Drastically reduce technical debt and ensure a seamless user experience.

Bug hunting slows down your delivery cycle

Reactive debugging is a financial drain. Your developers spend too much time reproducing errors instead of creating value. The result: delayed deployments and constant operational fatigue.

Main negative impacts:

  • Long feedback loops: Between bug discovery and fix, precious hours are lost in manual investigation.
  • Accumulation of technical debt: Pressure to meet deadlines leads to quick but fragile fixes, creating cascading new bugs.
  • Constant pressure on teams: 'Firefighting' mode prevents developers from focusing on innovation and core features.

Swiftask connects Devin to your logs and monitoring tools. As soon as an anomaly is detected, Devin analyzes the code, isolates the source, and proposes a fix ready for testing.

BEFORE / AFTER

What changes with Swiftask

Traditional debugging

A system alert triggers. A developer must stop, open logs, attempt to reproduce the error locally, then search for a fix. Meanwhile, service is degraded.

Proactive debugging with Devin

The alert automatically triggers Devin via Swiftask. The agent analyzes the stack trace, identifies the faulty commit, and prepares a fix PR. The developer only needs to approve.

Setting up your debugging workflow in 4 steps

STEP 1 : Connect log sources

Link your monitoring tools (Sentry, Datadog, etc.) to Swiftask to centralize alerts.

STEP 2 : Configure Devin agent

Define Devin's permissions on your Git repositories so it can analyze and propose patches.

STEP 3 : Define criticality thresholds

Configure Swiftask to trigger Devin only on critical or recurring errors.

STEP 4 : Intelligent human validation

Review Devin's proposed fixes in your interface and validate deployment with one click.

Devin's code analysis capabilities

Devin doesn't just read logs: it understands the business logic behind the code to prevent regressions.

  • Target connector: The agent performs the right actions in devin based on event context.
  • Automated actions: Complex stack trace analysis. Correlation between code changes and errors. Unit test generation to validate fixes. Automated patch PR generation.
  • Native governance: Swiftask ensures every action Devin takes is logged, providing total visibility over your codebase evolution.

Each action is contextualized and executed automatically at the right time.

Each Swiftask agent uses a dedicated identity (e.g. agent-devin@swiftask.ai ). You keep full visibility on every action and every sent message.

Key takeaway: The agent automates repetitive decisions and leaves high-value actions to your teams.

Strategic advantages for your engineering

1. Increased resolution speed

Go from identification to fix in minutes, without heavy manual intervention.

2. Higher product stability

Proactive detection prevents minor bugs from becoming major incidents.

3. Unlocking creative time

Your developers finally focus on architecture and new features.

4. Standardized fixes

Devin applies coding best practices to every proposed correction.

5. Seamless CI/CD integration

Fixes naturally fit into your existing pipeline for secure deployment.

Security and code control

Swiftask applies enterprise-grade security standards for your devin automations.

  • Restricted repo access: Devin only accesses the branches and files necessary for its debugging tasks.
  • Mandatory human validation: No code is merged without your explicit approval via the Swiftask interface.
  • Change traceability: Every Devin intervention is documented and linked to the corresponding initial alert.
  • SOC2 compliance: The entire process meets the strictest security standards for your source data.

To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.

RESULTS

Measurable operational impact

MetricBeforeAfter
Mean Time To Repair (MTTR)Several hoursUnder 15 minutes
Production bugsHighSignificant reduction
Developer focus30% on debuggingLess than 5%
Deployment reliabilityRegression riskAutomatically tested

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Drastically reduce technical debt and ensure a seamless user experience.

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