Your doubts
are reasonable.
Your next move
should be too.

Short stories for lawyers and professionals navigating AI, its promises, its risks, and what competence really means.

Fiction. Realistic.
Professionally relevant.

AI literacy lessons
woven in.

Read in 20–40
minutes.

Build confidence,
not hype.

The Library

Five fables. All free to read.

Each one puts capable people under real constraints and makes them decide. No villains, no miracle tools, and no vendor is ever the hero.

Competence36 min

Understanding Without Reliance

Miriam Adler will not put client information into an AI system and will not rely on what one produces. She refuses the more comfortable escape too: ignorance.

For principled non-users Read →
Read the jacket →

If AI is changing her clients, her opponents, the evidence, and the profession around her, she believes she has to understand it. So begins an unusual experiment in competence. She learns by observing, questioning, testing, challenging experts, and working with people who know things she does not. Can you become genuinely AI-literate without becoming an AI user, and can you prove it when it matters?

Governance42 min

Fit to Serve

Corinne Alvarez has sixty days to tell her board what AI should mean for a legal-aid organization already stretched beyond capacity.

For legal-aid leadership Read →
Read the jacket →

The promise is obvious: more people served, faster work, scarce resources extended further. So are the stakes. A careless shortcut can expose a client's secrets, a confident error can cost someone a home, and the people most excited about innovation are not always the ones who will live with its consequences. As she uncovers hidden talent, hidden AI use, eager funders and persuasive vendors, Corinne has to build something harder than a strategy: a vision worthy of the people her organization exists to serve.

Ownership44 min

No Obvious Owner

For twenty-six years Glenda Pruitt has handled the problems nobody else quite owns. Then AI lands on her desk with one difference: nobody can tell her what question she is supposed to answer.

For firm operations Read →
Read the jacket →

Research the issue, make a recommendation, let the partners decide. That has always been the method. But around the firm people are already using AI, avoiding it, selling it, worrying about it, and pretending to understand it, and clients and insurers are starting to ask questions too. Following the problem from practice group to practice group, Glenda discovers that the firm’s real gap is not technology. It is ownership.

Rulemaking39 min

The Drafting Table

Eight people sit down to write a rule for AI in legal work. The trouble starts when every simple principle meets a real person.

For rule-makers & bars Read →
Read the jacket →

A paralegal asks who actually performs the work. A self-represented litigant asks who can afford to verify it. Lawyers, clients, adjudicators and a technologist keep discovering that words like competence, supervision, disclosure and reasonable use are far easier to endorse than to define. Clause by clause, certainty gives way to harder questions and better language.

Bar Leadership12 min

What the Board Owed

Jerry has spent twelve years making other lawyers stay current. He has never once pointed that machinery at himself, and now a file nobody wanted is on his desk.

For bar & association leaders Read →
Read the jacket →

Seven hundred members, mostly solo, a hundred dollars a year, and a board that cannot agree whether saying something about AI is leadership or exposure. One member came within a click of sending a client's file to a tool nobody had vetted. Another built his own practice on tools he taught himself and needs no saving at all. Six weeks to the annual meeting, a vote he cannot control, and a resolution that has to hold both kinds of member at once.

Verification12 min

Good Law

Mira Desai is the fastest researcher on her moot court team. The brief goes in at three in the morning with one authority nobody opened.

For law students & new lawyers Read →
Read the jacket →

A research tool returns six cases, ranked, with a green check beside each one. It answers exactly what it was asked, twice, and neither question was what am I missing. By the time anyone reads the actual opinion, the brief has been filed for three weeks and cannot be changed. What can still be changed is the person who has to stand next to it and answer for it.

Education38 min

What Must Be Taught

The people responsible for deciding what lawyers must know about AI have a problem: they are not sure they know it themselves.

For educators & regulators Read →
Read the jacket →

A supreme court justice, a bar examiner, an accreditor, law professors, judges and disciplinary counsel convene to define professional competence for a new generation. Their first act is to take the same diagnostic they plan to impose on everyone else. The results are uncomfortable. Before they can decide what must be taught, they have to confront what they themselves never learned.

What every book carries

The objections, at full strength

Every book in the series rests on the same foundation: a detailed, principled list of objections to AI use in legal work, argued properly and never set up to fall over.

And the reasons to understand anyway

Alongside them, the equally detailed account of why a principled non-user still needs to understand the technology. Refusal is a position, not an exemption.

99 topics, open in one click

Course content from LawQi's 99 AI Skill Building topics informs the narrative. Most of those resources are linked inline, right where the story uses them. Free, no signup, no account.

Every story is free to read, in full.

About

A small library for a loud moment.

Reasonable Doubts publishes short fiction about professionals meeting artificial intelligence at work: the promises, the pressure, and the quiet question of what competence is going to mean next.

The stories are invented; the pressures are not. Each book is built on the same two foundations: a detailed list of principled objections to AI use in legal work, and an equally detailed account of why a principled non-user still has to understand it. Start anywhere in the Library.

House rules

No miracle endings

Nobody is saved by a feature. The resolution is always a decision a person made.

Not legal advice

These are fables, not guidance. Your jurisdiction, your regulator, your call.

Written with AI, openly

AI was used extensively in organizing the underlying material and in drafting these stories. Saying so is part of the point.

Why Fables?

Nobody ever changed their judgment because of a slide deck.

Narrative is already how lawyers reason

The whole profession learns judgment from the facts of someone else's bad week. A case is a story with a holding attached. Fables work because the format was never foreign.

Rules go stale; the situations don't

A policy written for last spring's tool is already obsolete. The pressures underneath it have not moved in forty years: speed, cost, candor, the urge to look capable.

Fiction lets you be wrong safely

You can watch a careful person make the wrong call and feel exactly what it costs, without it being your matter, your client, or your bar number.

LawQi

Who's behind this.

Reasonable Doubts is published by LawQi, which spends its working days on the unglamorous end of this question: how legal teams actually adopt AI without trading away judgment, confidentiality, or their own standards.

LawQi CEO Colin Lachance “produced” the stories. Let him know what other scenarios you’d like to see represented.