A few years into her operations job, an engineer I’ll call Meera decided to master AIOps. She collected courses, bookmarked papers, and spent her evenings with correlation engines and anomaly detectors. Eighteen months later she could define everything and ship almost nothing. What finally moved her forward was not another tutorial but an AIOps mentor: one seasoned practitioner who reviewed her work every week, questioned her assumptions, and steered her around mistakes he had already made. Her story keeps repeating across IT teams, yet the myths that kept her stuck for a year and a half are still everywhere. Let’s walk through them.

Myth 1: AIOps is too new for mentors to exist

It feels plausible. If the discipline is young, who could possibly have grey hair in it? But AIOps did not appear from nowhere; it grew out of monitoring, event management, and automation work that veterans have been doing since long before the label existed. People like Rajesh Kumar, a principal architect who also trains and mentors engineers across introducing AIOps to an existing IT team and neighbouring fields such as DevOps and SRE, carry over fifteen years of operational scar tissue into every conversation. The pattern-recognition a learner needs most — which alerts matter, which models mislead — predates the buzzword entirely.

Myth 2: Good documentation replaces a guide

Meera owned every well-reviewed book on the subject. What none of them could do was look at her event pipeline and say, “this correlation rule will bury your on-call team by Friday.” Documentation describes the general case; a mentor responds to your specific one. The feedback loop is the difference: you act, someone who has done this for a living reacts, and you adjust within days instead of discovering the flaw months later in production.

There is also a sequencing problem no manual solves. Books present topics in the order an editor chose; a guide presents them in the order your situation demands. When Meera’s team suffered a cascade of duplicate incidents, her mentor shelved the machine-learning chapter she was halfway through and spent two sessions on deduplication logic instead — because that was the wound currently bleeding. Curriculum that bends around your reality is something print physically cannot offer.

Myth 3: Asking for one-on-one help is a junior move

In aviation and surgery, nobody calls supervised practice embarrassing; it’s simply how competence is built. IT somehow absorbed the idea that real engineers figure everything out alone. The senior people Meera admired turned out to have had guides of their own — a staff engineer here, a patient architect there — whose judgment they borrowed until their own matured. Guided growth is not a confession of weakness. It is how strong practitioners were made in the first place.

Myth 4: A mentor must sit in your office

This one quietly dies every year. Screen-shared dashboards, recorded incident reviews, and async code comments make distance irrelevant. Kumar, for instance, offers consulting, corporate training, and personal mentorship to engineers anywhere in the world from his practice hub for DevOps, SRE, and AIOps guidance, and the sessions work precisely because modern operations tooling is remote-native anyway. If your observability stack lives in a browser, so can your apprenticeship.

Myth 5: Mentorship slows you down compared to self-paced study

Self-paced sounds fast until you count the dead ends. Meera spent four months tuning an anomaly-detection approach her mentor later dismissed in one sentence, because he had watched three teams try it and drown in false positives. That sentence was four months handed back to her. Speed in learning taming alert floods with smarter event handling rarely comes from consuming material quicker; it comes from not walking into walls that someone ahead of you has already mapped.

Count the arithmetic honestly. A weekly hour with a guide costs perhaps fifty hours a year. One avoided dead end of Meera’s size repays that several times over, and most learners hit more than one dead end per year. The “slow” option, measured in outcomes rather than calendar pages turned, is almost always the solitary one.

Myth 6: Once you’re mentored, you’ll stay dependent

The quiet fear behind many objections is dependency — that guided learners never develop their own judgment. Real mentorship runs the other way. Every session, a little of the mentor’s decision-making gets transplanted: why he distrusts that metric, how she scopes an automation rollout. Meera’s weekly reviews grew shorter over a year, not longer, until they became occasional conversations between peers. The endpoint of sustained guidance is independence with better instincts, which no amount of solo reading reliably produces.

What Meera’s second year looked like

With a practitioner reviewing her work, she shipped a noise-reduction pipeline, cut her team’s paging volume, and led her first live troubleshooting of production issues as they unfold without panic. None of the material she had studied alone was wasted — it simply started connecting, because someone kept asking her the questions textbooks never ask: what would you do here, and why?

If you are circling AIOps the way she once did, the lesson is plain. The field rewards judgment more than vocabulary, and judgment moves fastest when a seasoned head passes it directly to the person still forming theirs. Find your own version of that relationship — a senior inside your company, or an established mentor outside it — and let the myths above stop costing you months.