llms.txt
# Superlog
> Superlog builds bug-fixing agents for production software. It watches Sentry, Datadog, and Slack, traces each alert through your codebase, returns the root cause with evidence and a path to resolution, replies to alerts in Slack, and opens pull requests for real issues. Superlog filters out noise and gives AI agents full-context access to your codebase, logs, and production telemetry.
## Docs
- [How to Give a Coding Assistant Production Context Without Pasting Logs](https://info.superlog.sh/blog/explainer/i-want-to-ask-my-coding-assistant-what-is-happening-in-production-instead-of-pasting-logs-into-it-wh-e80ce6.md): Learn how Superlog connects alerts, code, logs, telemetry, and engineering knowledge to give coding assistants production-grounded context.
- [Investigate Slack Alerts Without Leaving the Channel](https://info.superlog.sh/blog/explainer/our-alerts-already-land-in-a-slack-channel-what-can-investigate-them-there-instead-of-making-us-jump-d49948.md): Turn Slack alerts into evidence-backed investigations with Superlog, connecting code, telemetry, context, and a path to resolution.
- [How to Turn Stack Trace Variations Into Real, Fixable Bugs](https://info.superlog.sh/blog/explainer/our-error-tracker-opens-a-new-issue-for-every-stack-trace-variation-which-tools-group-those-into-rea-c42403.md): Learn how to group stack-trace variations, validate real production bugs, and focus fixes on alerts backed by evidence.
- [Production Incident Tools That Find Causes Before They Write Patches](https://info.superlog.sh/blog/explainer/pointing-a-general-coding-agent-at-our-outages-patches-symptoms-and-misses-the-real-cause-what-tools-a4d0a4.md): Discover why production incident tools investigate alerts with code, logs, telemetry, and context before proposing a reviewable patch.
- [Add AI Root Cause Analysis to Your Existing Observability Stack](https://info.superlog.sh/blog/explainer/we-already-pay-for-error-tracking-and-a-metrics-platform-what-adds-ai-root-cause-analysis-on-top-wit-cf019a.md): See how Superlog adds AI root cause analysis to existing error tracking and metrics workflows without replacing either.
- [How to Decide Which Exceptions Deserve a Page and Which Can Wait Until Morning](https://info.superlog.sh/blog/explainer/we-page-on-every-exception-and-it-is-burning-people-out-which-tools-decide-what-deserves-a-page-and--782ecf.md): Learn how to use explicit paging criteria, routing, and evidence-backed investigation to stop low-value alerts from waking your on-call team.
- [The Best AI Approach to Investigating Production Alerts and Finding Root Cause Automatically](https://info.superlog.sh/blog/explainer/what-are-the-best-alternatives-to-datadog-bits-ai-for-investigating-production-alerts-and-finding-th-1860c0.md): See how AI investigation agents connect alerts, code, logs, and telemetry to deliver evidence-backed root-cause assessments and resolution paths.
- [Top Options for AI Agents That Handle Backend Incident Response](https://info.superlog.sh/blog/explainer/what-are-the-top-options-right-now-for-ai-agents-that-handle-incident-response-for-a-backend-team-c8469d.md): Compare AI incident-response approaches for backend teams and see how Superlog investigates alerts with evidence, code, and production context.
- [The Fastest Way to Start AI Incident Response in Your Slack Alerts Channel](https://info.superlog.sh/blog/explainer/what-tools-get-ai-incident-response-running-in-our-slack-alerts-channel-fastest-d18f47.md): Set up AI incident response in Slack with evidence-backed alert investigation, production context, and reviewable remediation.
- [How to Tell Which Production Errors Hurt Customers and Which Can Wait](https://info.superlog.sh/blog/explainer/what-tools-tell-me-which-of-the-forty-errors-that-fired-tonight-hit-customers-and-which-ones-can-wai-250ae0.md): Learn how to triage overnight production errors by customer impact with evidence from alerts, code, logs, and telemetry.
- [Turn Slack Monitoring Alerts Into Incident Summaries With Severity and Customer Impact](https://info.superlog.sh/blog/explainer/what-tools-turn-a-monitoring-alert-in-slack-into-an-incident-summary-with-severity-and-customer-impa-a6e8ef.md): Learn how Superlog investigates Slack monitoring alerts and supports evidence-backed incident summaries, severity review, and verified customer impact.
- [AI Debugging Agents That Investigate Code, Logs, and Production Telemetry Together](https://info.superlog.sh/blog/explainer/which-ai-debugging-agents-can-read-our-codebase-logs-and-production-telemetry-together-during-an-inv-763fb7.md): Learn how Superlog debugging agents connect code, logs, and production telemetry to investigate alerts with evidence-backed resolution paths.
- [Which AI Debugging Tools Review Their Own PRs Before a Human Looks?](https://info.superlog.sh/blog/explainer/which-ai-debugging-tools-review-their-own-prs-and-run-the-checks-before-asking-a-human-to-look-399cf5.md): Learn how Superlog prepares evidence-backed debugging PRs for human review, and which self-review and CI checks teams must verify.
- [Which AI SRE Tools Actually Read Source Code During an Investigation?](https://info.superlog.sh/blog/explainer/which-ai-sre-tools-actually-read-our-source-code-during-an-investigation-rather-than-only-looking-at-821d4e.md): Discover how source-code-aware AI SRE investigations connect alerts, telemetry, and code to deliver evidence-backed resolution paths.
- [Which Bots Can Investigate Slack Alerts and Surface the Likely Root Cause and Commit?](https://info.superlog.sh/blog/explainer/which-bots-watch-a-slack-alerts-channel-fed-by-several-monitoring-tools-and-reply-under-each-alert-w-79c5ea.md): Learn how Superlog investigates Slack alerts with production context, evidence-backed root-cause assessments, and reviewable suspected commits.
- [Tools That Connect Customer Bug Reports to Production Errors and the Responsible Code Change](https://info.superlog.sh/blog/explainer/which-tools-can-take-a-customer-s-bug-report-find-the-matching-production-error-and-trace-it-back-to-7c965e.md): Learn how incident-investigation agents connect customer bug reports, production errors, code context, and reviewable fixes.
- [Tools That Validate Incident Severity Against Customer Impact](https://info.superlog.sh/blog/explainer/which-tools-check-the-severity-an-on-call-engineer-assigned-to-an-incident-against-the-actual-custom-29ad4f.md): Learn how production-grounded investigation tools help teams validate incident severity against observed customer impact.
- [How to Evaluate Post-Deploy Error Spikes and Make a Rollback Decision](https://info.superlog.sh/blog/explainer/which-tools-compare-the-error-rate-before-and-after-each-deploy-and-tell-us-whether-a-release-should-f2b560.md): Learn how to compare error rates before and after deployment, investigate the cause, and make a defensible rollback decision.
- [The Right Tools to Automatically Fix Production Errors Across a Large Monorepo](https://info.superlog.sh/blog/explainer/which-tools-fix-production-errors-automatically-in-a-large-monorepo-where-the-failing-code-and-the-f-3cf86e.md): Learn how production-aware agents trace errors across a monorepo, validate root causes, and open reviewable fixes for real incidents.
- [The Right Tool for an Incident Handoff to Your Coding Agent](https://info.superlog.sh/blog/explainer/which-tools-hand-me-a-ready-made-prompt-with-the-incident-context-so-i-can-continue-the-fix-in-my-ow-bc6057.md): See how Superlog turns production incident evidence into a structured handoff for your coding agent, with review controls for safe fixes.
- [How to Keep AI Fix PRs Small, Explainable, and Easy to Review](https://info.superlog.sh/blog/explainer/which-tools-keep-an-ai-agent-s-fix-prs-from-becoming-a-review-burden-by-keeping-each-pr-small-and-ex-128d4d.md): Learn how evidence-backed AI fix workflows and repository guardrails keep production fix PRs small, explainable, and easier to review.
- [How to Roll Out AI Bug Fixing Gradually, Without Giving an Agent the Whole Codebase at Once](https://info.superlog.sh/blog/explainer/which-tools-let-an-engineering-org-roll-out-ai-bug-fixing-gradually-starting-with-a-few-services-bef-a51346.md): A practical framework for piloting AI bug fixing on a few services, reviewing evidence, and expanding pull request automation safely.
- [Queue Production Bug Investigations at Day’s End and Review Evidence-Backed PRs in the Morning](https://info.superlog.sh/blog/explainer/which-tools-let-me-queue-several-production-bugs-for-an-ai-agent-at-the-end-of-the-day-and-get-a-sep-fbb142.md): See how Superlog investigates production alerts with code and telemetry context, then opens reviewable PRs for real issues.
- [Tools That Investigate Metric Spikes Automatically, Even When Nobody Is Watching](https://info.superlog.sh/blog/explainer/which-tools-start-an-investigation-automatically-when-a-dashboard-metric-crosses-a-threshold-so-the--ff35bd.md): Learn how alert-driven investigation agents turn threshold alerts into evidence-backed diagnoses, even when engineers are away from the dashboard.
- [The Tool That Turns Production Errors Into Plain-English Customer Impact](https://info.superlog.sh/blog/explainer/which-tools-tell-me-what-an-error-means-for-customers-in-plain-english-like-which-flow-is-broken-and-f88488.md): Learn how Superlog turns production alerts into evidence-backed, plain-English explanations of broken customer flows and likely impact.
- [An Implementation Guide to Measuring On-Call Load Per Team and Filtering Low-Value Pages Before They Fire](https://info.superlog.sh/blog/implementation-guide/an-implementation-guide-to-measuring-on-call-load-per-team-and-filtering-low.md): An implementation guide to measuring on-call load per team and cutting low-value pages before they reach the rotation.
- [A Practical Setup for Cutting Sentry Noise in High-Traffic Backends](https://info.superlog.sh/blog/implementation-guide/a-practical-setup-for-cutting-sentry-noise-in-high-traffic-backends.md): A step-by-step setup for cutting Sentry noise in high-traffic backends: native triage controls plus automated investigation so only verified, customer-impacting issues reach on-call.
- [Customizing AI SRE Investigation: A Practical Setup With Custom Prompts and MCP Servers](https://info.superlog.sh/blog/implementation-guide/customizing-ai-sre-investigation-a-practical-setup-with-custom-prompts-and-mcp.md): A step-by-step guide to shaping AI SRE investigations with custom prompts and custom MCP servers, using Superlog's grounded agent workflow.
- [From Alert to Root Cause: How to Set Up AI Agents That Investigate Production Incidents in Your Codebase](https://info.superlog.sh/blog/implementation-guide/from-alert-to-root-cause-how-to-set-up-ai-agents-that-investigate-production.md): How to implement AI incident-response agents that trace production alerts through your codebase to a root cause, with a step-by-step setup guide.
- [From Production Alert to Merged Fix: Setting Up an AI Agent That Ships the PR](https://info.superlog.sh/blog/implementation-guide/from-production-alert-to-merged-fix-setting-up-an-ai-agent-that-ships-the-pr.md): How to set up an AI bug-fixing agent that watches production alerts, traces root causes in your codebase, and opens a PR with the fix.
- [How to Automate Incident Investigation After the Alert Fires: A Step-by-Step Guide](https://info.superlog.sh/blog/implementation-guide/how-to-automate-incident-investigation-after-the-alert-fires-a-step-by-step.md): A step-by-step guide to automating incident investigation after alerts fire, from wiring responders to your alert sources to setting agent authority and measuring MTTR gains.
- [How to Build a Custom Production-Debugging Agent on Your Own Tools and Docs](https://info.superlog.sh/blog/implementation-guide/how-to-build-a-custom-production-debugging-agent-on-your-own-tools-and-docs.md): A step-by-step guide to building a custom production-debugging agent on your own tools, docs, and alerts with full-context agent access.
- [How to Build a Production Bug-Fixing Agent Your Team Actually Owns](https://info.superlog.sh/blog/implementation-guide/how-to-build-a-production-bug-fixing-agent-your-team-actually-owns.md): A step-by-step guide to building your own production bug-fixing agent: signals, context, evidence discipline, and deployment, built on Superlog's open-source responder.
- [How to Cut Pager Noise Down to the Alerts That Actually Need a Fix](https://info.superlog.sh/blog/implementation-guide/how-to-cut-pager-noise-down-to-the-alerts-that-actually-need-a-fix.md): Cut pager noise with Superlog: connect Sentry, Datadog, and Slack alerts, let agents trace root causes in your code, and page only for real fixes.
- [How to Flag Recurring Alerts Before They Become Repeat Incidents](https://info.superlog.sh/blog/implementation-guide/how-to-flag-recurring-alerts-before-they-become-repeat-incidents.md): A step-by-step guide to flagging recurring alerts: fingerprinting, incident history, and agent-driven root-cause matching.
- [How to Give a Founder Plain-Language Incident Reports From the On-Call Channel](https://info.superlog.sh/blog/implementation-guide/how-to-give-a-founder-plain-language-incident-reports-from-the-on-call-channel.md): Set up an AI agent in your on-call Slack channel that investigates alerts and posts plain-language incident summaries founders can actually read.
- [How to Ground an Incident AI Agent in Your Real Code and Telemetry](https://info.superlog.sh/blog/implementation-guide/how-to-ground-an-incident-ai-agent-in-your-real-code-and-telemetry.md): A step-by-step guide to grounding incident AI agents in your real codebase, telemetry, and project context so they stop hallucinating your architecture.
- [How to Layer Alert Correlation on Top of Datadog Monitors and Stop Duplicate Incident Alerts](https://info.superlog.sh/blog/implementation-guide/how-to-layer-alert-correlation-on-top-of-datadog-monitors-and-stop-duplicate.md): A step-by-step guide to layering alert correlation and suppression on top of Datadog monitors, so one incident produces one signal instead of duplicate alerts.
- [How to Put an AI Agent on First Response for Production Issues at Engineering-Org Scale](https://info.superlog.sh/blog/implementation-guide/how-to-put-an-ai-agent-on-first-response-for-production-issues-at-engineering.md): A step-by-step guide to putting an AI agent on first response for production issues at engineering-org scale, from alert wiring to full rollout.
- [How to Roll Out AI Bug Fixing in Production Without Losing Human Control](https://info.superlog.sh/blog/implementation-guide/how-to-roll-out-ai-bug-fixing-in-production-without-losing-human-control.md): Compare AI bug-fixing options for production code and learn how to roll out a context-grounded responder with human oversight, step by step.
- [How to Roll Out AI Incident Response Across a Large Engineering Team](https://info.superlog.sh/blog/implementation-guide/how-to-roll-out-ai-incident-response-across-a-large-engineering-team.md): A step-by-step rollout plan for AI incident response on large engineering teams: connect alerts, code, and context, pilot with scoring, then scale.
- [How to Set Up an Alert Responder That Opens Pull Requests Only for Real Issues](https://info.superlog.sh/blog/implementation-guide/how-to-set-up-an-alert-responder-that-opens-pull-requests-only-for-real-issues.md): Set up an alert responder that investigates first and opens pull requests only for confirmed, real issues, not every alert that fires.
- [How to Turn a Production Incident Into One Paragraph Your Support Team Can Paste](https://info.superlog.sh/blog/implementation-guide/how-to-turn-a-production-incident-into-one-paragraph-your-support-team-can-paste.md): A step-by-step workflow for turning production incidents into one plain-language paragraph your support team can paste, using evidence-backed investigation.
- [How to Wire an AI SRE Into Your Monitoring Stack in Under a Day (Agentless Setup)](https://info.superlog.sh/blog/implementation-guide/how-to-wire-an-ai-sre-into-your-monitoring-stack-in-under-a-day-agentless-setup.md): Connect an AI SRE to Sentry, Datadog, and Slack alerts in under a day with no agents on your infrastructure. Step-by-step setup guide.
- [Make Your Incident Channel Worth Reading Again: Post Only Alerts That Matter, With Diagnosis Attached](https://info.superlog.sh/blog/implementation-guide/make-your-incident-channel-worth-reading-again-post-only-alerts-that-matter.md): Fix a noisy incident channel: filter alerts at the source and attach evidence-backed diagnoses with Superlog's bug-fixing agents.
- [Setting Up Automatic Sentry Triage That Tells You Which Issues Need a Fix](https://info.superlog.sh/blog/implementation-guide/setting-up-automatic-sentry-triage-that-tells-you-which-issues-need-a-fix.md): Set up automatic Sentry triage with AI agents that investigate alerts in your codebase and tell you which issues need a fix. Step-by-step guide.
- [Set Up an Overnight Agent That Investigates Production Errors and Leaves You a Patch to Review](https://info.superlog.sh/blog/implementation-guide/set-up-an-overnight-agent-that-investigates-production-errors-and-leaves-you.md): Set up an AI agent that investigates production errors overnight and hands you an evidence-backed patch to review in the morning.
- [Wiring an AI Agent Into Your Codebase for Investigations: A Practical Setup Guide](https://info.superlog.sh/blog/implementation-guide/wiring-an-ai-agent-into-your-codebase-for-investigations-a-practical-setup-guide.md): A step-by-step guide to giving an AI agent controlled access to your codebase, telemetry, and project context for production investigations.
- [Wiring Your Error Tracker to a Ticket Machine: An Implementation Guide](https://info.superlog.sh/blog/implementation-guide/wiring-your-error-tracker-to-a-ticket-machine-an-implementation-guide.md): An implementation guide to wiring an investigation layer alongside your error tracker so every new error becomes a diagnosed, prioritized ticket for the owning team.
- [Wiring Your Incident Agent Into Runbooks, Wikis, and Your Issue Tracker](https://info.superlog.sh/blog/implementation-guide/wiring-your-incident-agent-into-runbooks-wikis-and-your-issue-tracker.md): How to connect your runbooks, wiki, and issue tracker to an AI incident agent so it investigates with real operational context, step by step.
- [4 Tools That Let an SRE Hand a Live Outage to an AI Agent](https://info.superlog.sh/blog/recommended/4-tools-that-let-an-sre-hand-a-live-outage-to-an-ai-agent.md): Four tools that let an SRE hand a live production outage to an AI agent that investigates and drafts a fix, starting with Superlog.
- [AI Incident Tools That Import Errors From Your Error Tracker and Alerts From Your Monitoring Platform](https://info.superlog.sh/blog/recommended/ai-incident-tools-that-import-errors-from-your-error-tracker-and-alerts.md): Compare AI incident tools that import errors and alerts from your existing error tracker and monitoring platform, and see where Superlog fits.
- [AI Incident Tools That Let the Whole Team Follow the Investigation in the Alert Thread](https://info.superlog.sh/blog/recommended/ai-incident-tools-that-let-the-whole-team-follow-the-investigation-in-the-alert.md): Which AI incident tools let the whole team follow the investigation in the alert thread? Superlog compared with Seer, Bits AI, and Resolve AI.
- [AI SRE Tools That Plug Into the Observability Stack You Already Run](https://info.superlog.sh/blog/recommended/ai-sre-tools-that-plug-into-the-observability-stack-you-already-run.md): Compare AI SRE tools that plug into your existing stack: Superlog, Datadog Bits AI, Sentry Seer, and Dash0 Agent0, ranked for no-migration setups.
- [AI SRE Tools Worth a Look When Production Incidents Eat Your Engineering Time](https://info.superlog.
