Often and early

My friend and mentor Danny Lieberman writes an excellent newsletter about antipatterns: the moves people make instinctively that quietly cost them (https://substack.com/@dannylieberman). This week’s issue is in that spirit. The antipattern: keeping important work to yourself until it is ready. The fix turns out to be the thing the old saying tells you not to do.

The instinct is universal. When people work on something they consider important and big, they retreat into a shell and wait for the work to be done before they show it to anyone. A report for leadership. A presentation. A new product. A Python module. A pitch deck. The instinct is the same: I will share when it is ready.

There is a saying in many languages: do not show half-done work to a donkey. It sounds like discipline. I think it is one of the more harmful rules people carry around. It tells you to optimize for not looking foolish today, while saying nothing about whether your final product will be any good.

This is the trap the donkey saying sets. It tells you the audience is the problem. Show your work only to people who can already see what you see. Otherwise they will misread, miss the point, ask a question whose answer is on page two. They will. That is the feature, not the bug. The “donkey” from the saying, the reader you were told to hide rough work from, is the most useful reader you have. They cannot see the picture you carry in your head, which means they will show you where it fails outside it.

If the legal or IP situation allows, share your work long before you think it is ready. The half-done draft. The rough plot. The function that almost compiles. The demo with three broken screens.

Most of the feedback will be off-target. You will think, this person did not get it. Sometimes they did not. More often, they got something you stopped noticing: that the framing was not clear, that the order of the argument was confusing, that the assumption you treated as obvious is not obvious to anyone else. You think you know what you know, but you might not know what you know.

The embarrassment cost of sharing rough work is small and one-time. The cost of polishing the wrong thing is large and compounds.

So pick the piece of work you have been keeping in your shell because it is “not ready to share yet.” Find one person who will give you an honest reaction. Send it to them today, in the state it is in, with one sentence:

“I am still working on this and I do not know what it will be. Tell me what you see.”

You will get back something useful, often only one sentence. That sentence is worth more than another week alone with the draft.

If you are in academia and work on a paper, publish a draft on arxiv or preprints.org - not only will you timestamp your findings so that nobody scoops you, you will also attract feedback that will make the further review process smoother. Loud Camel, the tool that I work on, will help you attracting the feedback faster.

Inside Loud Camel, a tool that helps researchers get cited and recognized, the work I have been sharing in drafts is the visibility handbook. Five short chapters on why good work goes unnoticed, nine tactics for an afternoon, and a stack of prompts that turn each tactic into a first draft. The chapters with the most placeholders are the ones the next reader’s question will rewrite first. If you are writing an internal playbook, a hiring rubric, or a strategy memo, share it while it is unfinished and let the questions you get back set next week’s writing.

Q: What does “sharing early” look like for academic work that is still in private revision?

The academic version of this antipattern has a name in the Loud Camel handbook: Tactic 2, Post the Preprint. The peer-reviewed argument is the same one this issue makes. The first readers of a paper, including the ones who half-misread the draft, set the citation trajectory of the work, sometimes for years. Loud Camel also runs a prompt that turns an in-progress abstract into a one-minute lay summary, which is the smallest version of sharing early that still gets the feedback loop running.

· Is it ethical to use AI to promote your research?: Using AI to promote honest work is not the ethical risk. Staying silent while sloppier voices use it is.

· Why your acquaintances, not your closest friends, bring you the next opportunity: Most useful job leads in Granovetter’s study came from contacts seen only occasionally, not friends seen often.

Pick the piece of work you have been keeping to yourself until it is ready. Send it to one honest reader today, in the state it is in, with one sentence. The donkey is the reader you need.