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.
AI Agents
devin
Connector devin · Secure OAuth 2.0
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
1
STEP 1 : Connect log sources
Link your monitoring tools (Sentry, Datadog, etc.) to Swiftask to centralize alerts.
2
STEP 2 : Configure Devin agent
Define Devin's permissions on your Git repositories so it can analyze and propose patches.
3
STEP 3 : Define criticality thresholds
Configure Swiftask to trigger Devin only on critical or recurring errors.
4
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
Increased resolution speed
Go from identification to fix in minutes, without heavy manual intervention.
Higher product stability
Proactive detection prevents minor bugs from becoming major incidents.
Unlocking creative time
Your developers finally focus on architecture and new features.
Standardized fixes
Devin applies coding best practices to every proposed correction.
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
| Metric | Before | After |
|---|---|---|
| Mean Time To Repair (MTTR) | Several hours | Under 15 minutes |
| Production bugs | High | Significant reduction |
| Developer focus | 30% on debugging | Less than 5% |
| Deployment reliability | Regression risk | Automatically tested |
Take action with devin
Drastically reduce technical debt and ensure a seamless user experience.