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If you’re a HotBot member, you can connect Rootly directly inside HotBot, and the assistant will start working with your actual Rootly data \u2014 incidents, timelines, past retros, all of it. This rootly ai integration<\/strong> turns a chat window into an incident co-pilot that reviews code, writes queries, triages errors, and drafts postmortems. No copy-paste between tabs.<\/p>\n\n\n\n Anyone who’s spent enough late nights in incident channels knows the alert isn’t the hard part. It’s everything after: correlating the deploy, writing the update, drafting the retro while your brain runs on fumes. That’s the work an ai coding assistant with rootly<\/strong> context can take off your plate. Below is the setup and the workflows that actually pull their weight.<\/p>\n\n\n\n One clarification first. HotBot is an independent AI chat service. It is not an official Rootly product, and it’s not affiliated with or endorsed by Rootly. The Rootly name only identifies the app you’re connecting.<\/p>\n\n\n\n What you’ll need before you start:<\/p>\n\n\n\n Estimated time:<\/strong> 10\u201315 minutes to connect and run your first workflow.\nDifficulty level:<\/strong> Beginner. If you can chat, you can do this.<\/p>\n\n\n\n Once you’re signed in as a member, connect Rootly from inside HotBot. The connector links HotBot to your Rootly workspace so the assistant reads your incident context directly, with no manual paste and no exporting timelines to a text file.<\/p>\n\n\n\n This guide won’t walk you through specific menu screens it can’t verify. Connector setup lives inside the app and it’s a couple of clicks once you’re a member. Go to the HotBot login<\/a>, sign in, and connect it from there.<\/p>\n\n\n\n The reason to use the connector at all comes down to context. Rootly’s whole value is keeping the incident channel, on-call data, past-incident history, telemetry, and code repositories in one place, according to Rootly’s own 2026 platform writeup<\/a>. When HotBot reads that directly, its answers stop being generic and start being about your Sev1 from last Tuesday.<\/p>\n\n\n\n This is where most HotBot time goes. Pull a PR or a suspicious commit into the conversation and ask for a real review \u2014 not “looks good,” but the kind a tired senior engineer gives.<\/p>\n\n\n\n Try a prompt like:<\/p>\n\n\n\n Because the connector ties into your incident history, HotBot can cross-reference the code against the actual failure. A standalone linter can’t do that. Rootly’s AI correlates code changes, deploys, and past incidents to surface root cause hypotheses, and pulling that same context into a code review is the natural extension.<\/p>\n\n\n\n Model tier:<\/strong> For everyday PR passes, HotBot Chat<\/a> is fast and does the job. For a gnarly multi-file refactor where the assistant has to reason through call chains, bump up to Chat Pro. Its 1M-token context swallows big diffs whole.<\/p>\n\n\n\n You already write your own queries. But at 2 a.m., when you need to slice incident data by service and time window, describing it in plain English beats fighting syntax.<\/p>\n\n\n\n Ask something like:<\/p>\n\n\n\n The connector means it’s querying your real Rootly incident data, not a hypothetical schema. The “explain what the numbers suggest” part is where it earns its keep, turning a table into a next action.<\/p>\n\n\n\n Model tier:<\/strong> Chat Plus is the pick here. It reasons step-by-step, which matters when a query has three joins and a window function. For a quick one-liner, plain HotBot Chat is faster.<\/p>\n\n\n\n This is the marquee workflow. When something’s on fire, you don’t want a chatbot. You want a responder who’s already read the channel. With Rootly connected, that’s closer to what you get.<\/p>\n\n\n\n A triage prompt worth keeping around:<\/p>\n\n\n\n Rootly’s AI already does live summaries, related-incident correlation, and probable root cause analysis while keeping responders in control (Rootly, 2026<\/a>). Running this through HotBot lets you pull a different reasoning model over the same context, which helps when you want a second opinion from something other than the engine that made the first call.<\/p>\n\n\n\n Model tier:<\/strong> Go Chat Pro for live triage. Deep reasoning over messy, incomplete context is exactly what it’s built for. This is also where picking a specific third-party model pays off \u2014 different models catch different things, and you’ve got 800+ to choose from.<\/p>\n\n\n\n The postmortem: the thing everyone agrees matters and nobody wants to write at the end of a six-hour incident.<\/p>\n\n\n\n Because HotBot reads the actual timeline through the connector, the timeline section writes itself. You edit for tone and accuracy instead of reconstructing events from memory, which is half-wrong by hour six anyway.<\/p>\n\n\n\n Model tier:<\/strong> Chat Plus handles most retros well. For a high-stakes exec-facing writeup, Chat Pro’s deeper reasoning produces something you’ll barely need to touch. Rootly’s own docs cover postmortem generation and meeting-note features too, and HotBot complements that rather than replacing your Rootly workflow.<\/p>\n\n\n\n No membership yet? You can still get a lot done. It’s just more manual.<\/p>\n\n\n\n Copy the relevant Rootly content \u2014 an incident timeline, a PR diff, a query result \u2014 and paste it into HotBot with your prompt. Same workflows from Steps 2\u20135, minus the automatic context fetch. For a one-off retro, this works fine.<\/p>\n\n\n\n The catch is that you become the connector. Every time you want fresh data, you paste again. That copy-paste tax is exactly what a membership removes. When you’re ready, pricing is here<\/a>: free tier, $7.95\/week, or $39.95\/quarter.<\/p>\n\n\n\n “HotBot’s answer feels generic.”<\/strong> You’re probably on the free tier without the connector, or you pasted too little context. Give it the full timeline, not a two-line summary.<\/p>\n\n\n\n “The model’s reasoning is shallow for a hard incident.”<\/strong> Wrong tier. Move from HotBot Chat to Chat Plus or Chat Pro. Fast models are for fast tasks.<\/p>\n\n\n\n “I want a different take on the root cause.”<\/strong> Switch models. That’s the point of having 800+ models<\/a> on one subscription \u2014 rerun the same prompt on a different engine.<\/p>\n\n\n\n Privacy note:<\/strong> Only connect data you’re comfortable processing through an AI assistant. Incident data can contain customer details, internal hostnames, and secrets, so sanitize the sensitive bits and follow your team’s data-handling policy. The connector reads what you point it at, so point it deliberately.<\/p>\n\n\n\n Once you’ve run a triage or a retro through HotBot, try building it into a routine. One that works: PR review on Chat before merge, triage on Chat Pro during incidents, retro on Chat Plus after. Same context, right tool each time.<\/p>\n\n\n\nPrerequisites<\/h2>\n\n\n\n
Step 1: Connect Rootly Inside HotBot<\/h2>\n\n\n\n
Step 2: Review Code and Pull Requests<\/h2>\n\n\n\n
Review this PR against the incident it's meant to fix.\nFlag risky changes, missing error handling, and anything\nthat could reintroduce the root cause from incident INC-2043.\n<\/code><\/code><\/pre>\n\n\n\nStep 3: Write and Explain Queries<\/h2>\n\n\n\n
Write a query to pull every incident tagged 'checkout-service'\nin the last 90 days, grouped by root cause category, with MTTR\nper group. Then explain what the numbers suggest.\n<\/code><\/code><\/pre>\n\n\n\nStep 4: Triage Incidents and Errors<\/h2>\n\n\n\n
Summarize the current state of incident INC-2043: what broke,\nwhat we've tried, what's still unknown. Correlate recent deploys\nand suggest the three most likely root causes, ranked by confidence.\n<\/code><\/code><\/pre>\n\n\n\nStep 5: Draft Docs, Retros, and Changelogs<\/h2>\n\n\n\n
Draft a postmortem for INC-2043 using our incident timeline:\nsummary, impact, root cause, timeline of events, action items\nwith owners. Keep it blameless. Then generate a one-line\nchangelog entry for the fix.\n<\/code><\/code><\/pre>\n\n\n\nWithout the Connector: The Free-Tier Workaround<\/h2>\n\n\n\n
Common Issues<\/h2>\n\n\n\n
What’s Next<\/h2>\n\n\n\n