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Reflection — An Honest Take 8 min

Honest Take — Before You Begin

Honest Take — Module 12: Ethics & Edge Cases of Public Teaching #

The ethical questions in teaching are not abstract until they are. The first thirty thousand readers of your work are statistical strangers — names you don't know, behaviors you don't see. The thirty-thousand-and-first is the one who emails you after acting on advice you gave, and now the question of whether you were appropriately careful is no longer abstract. Engineers consistently underestimate how quickly the abstract becomes concrete, and the position statements this module asks for exist to be written before that email arrives. The cleanest one-sentence summary of public-teaching ethics I can give you: the person on the other end is real, and the work of treating them as real is what most of these questions reduce to.

Attribution and accuracy are the two that scale with audience. The temptation to stop linking sources rises with reach — a 200-reader blog cites freely because citation costs nothing; a 200,000-reader blog has the temptation, sometimes unconscious, to present synthesized ideas as its own. The discipline is to keep citing as you grow, not despite it; teachers who become extractive are noticed, and the trust erodes first among exactly the people in the field who matter most.

On accuracy: you will be wrong in public — not "if," only "when" — and the fork in the road is silent edit versus explicit correction. Silently fixing it and hoping nobody noticed is the common move and the corrosive one; readers who catch silent edits start discounting everything else. The explicit correction, linked from the original, explaining what you got wrong, feels disproportionate to the error every single time and builds the exact trust that lets your future work be taken at face value. The math favors corrections, and so does the related, chronically underused sentence: "I don't know." Engineers internalize that confidence is competence and uncertainty is weakness; audiences perceive the opposite more clearly than writers do. "I don't know, but here's what I'd check" is the highest-trust sentence in technical teaching. Use it while teaching what you don't fully understand — which every working teacher does — by naming the uncertainty in the work itself: "here's my current model; corrections welcome" is a legitimate frame, as long as you reserve "I have figured this out" for things you actually have.

The parasocial trap deserves its own caution because it arrives quietly. Audiences develop one-sided relationships with teachers — the reader knows your voice, your jokes, your typical tone; you know nothing about them. The asymmetry is not pathological; it is the structural shape of audience itself. But it carries a duty of care that increases with reach: don't exploit the imbalance as a marketing channel, don't let emotional dependence drive product sales, and don't mistake parasocial signal for peer relationship — the reader who feels they know you is not your friend, and treating them as one is a category error that produces bad decisions on both sides. Adjacent to this sits pricing, where M11's work meets its ethics: no position survives everyone's scrutiny — "all teaching should be free" ignores that teachers have rent; "charge what the market bears" ignores structurally underpaid markets — and the defensible position is simply the one you have actually thought through and written down. The indefensible one is the default you never examined.

Two harder edges to close on. First, the regional question: if your audience concentrates in a region whose exclusion patterns you haven't lived — patterns of caste, class, gender, language, geography — your teaching enters that context whether you've thought about it or not. The duty is not to refuse to teach there; it is to do the homework, cite people who do understand, notice when your default examples assume a context not all your readers share, and notice who is missing from your audience that should be present. Most of this work is not heroic; it is just paying attention.

Second, the AI inflection: as of now, an LLM answers a large fraction of the questions a learner once asked a tutorial author — and I say this as the LLM in the room. The honest question this puts to your teaching is what specifically it offers that I don't: judgment formed by consequences, taste, scars, sequencing, accountability, the curse-of-knowledge repair that requires actually not-knowing things on schedule, presence. If you can't name what your teaching adds, the work may genuinely not be needed. If you can, it has a clearer purpose than teaching had before I existed.

Conclusion #

The questions get real when the audience does. Cite as you grow. Correct in public and never silently. Use "I don't know" liberally. Write the pricing position down before the pushback email writes it for you. Respect the parasocial asymmetry without exploiting it. Do the homework on the regions your teaching enters. And know what your teaching offers that an LLM doesn't — the module's job was never to enumerate every edge case, but to build the muscle of taking them seriously before they arrive.

Predictions #

  • You will publicly correct one piece of work within twelve months. The act will feel disproportionate to the error; the audience response will be more positive than you expect.
  • You will be tempted at least once to silently edit instead. The temptation will come with a perfectly reasonable-sounding justification ("it's just a small fix"). Don't.
  • One reader will email you after taking your advice and having it fail. The first such email is hard. Acknowledge, update the post if warranted, and do not get defensive — the reply matters more than the original error.
  • Your written pricing position will change at least twice in three years. Fine. Date the revisions.
  • The first clearly visible "I don't know" you publish will feel like exposure and will measurably increase the trust of that piece. You will feel the asymmetry exactly backwards from the reader.
  • An ethical question you did not anticipate — one that matches nothing in this module — will arrive in your inbox within two years. Whether you handle it well will depend on the positions you wrote here, not on the specifics it brings.