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eonist / feature spec.md
Created March 29, 2026 10:26
feature spec.md

[Feature] spec

Covers src/path/to/module.ts — one sentence describing what this module does and why it exists.


Why we write specs

Code tells you how something works. A spec tells you what it is supposed to do — and those two things are not always the same.

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eonist / FEATURE-MIGRATION-TEMPLATE.md
Created March 29, 2026 10:25
FEATURE-MIGRATION-TEMPLATE.md

Feature & Migration Roadmap — Best Practice Template

A general-purpose reference for structuring any feature, migration, or refactor using the tranche model. Drop this file into any project. Hand it to an agent or a new team member at the start of planning.


Philosophy

Every change ships in tranches. Every tranche produces a working, deployable system — never a broken in-between state.

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eonist / Apophenic branding.md
Last active March 29, 2026 07:55
Apophenic branding — strategically incomplete communication. The brand name, the visual mark, the product name — all designed to be just legible enough to trigger pattern completion without supplying the answer. The audience does the last 20% of interpretation and owns the result.

IV. Apophenia — The Brain's Compulsion to Find Signal in Noise

Apophenia is the cognitive tendency to perceive meaningful patterns in random data. It is not a disorder — everyone does it constantly. The brain is a pattern-completion machine; it looks for structure even where none exists because in evolutionary terms, a false positive costs less than a false negative. Better to see a predator in a shadow than to miss one. Better to find meaning in randomness than to risk missing the real signal.123

The result: the more minimal and undefined a thing is, the more strongly apophenia fills in the blanks. People report finding profound meaning in PPBS (pseudo-profound bullshit statements) — randomly assembled words that sound significant. Faces appear in static. Voices emerge from white noise. The brain will construct a signal from whatever material is available.34

For a brand: deliberate incompleteness is the most powerful communication tool available. The brand that says almost nothing, names itself with an un

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eonist / postlabourmarketeconomy.md
Created December 29, 2025 02:49
postlabourmarketeconomy.md

tell me 10 scams that has become established truths

Some scams and hoaxes don’t just trick a few people—they shape “common knowledge” for years (or even generations) before being exposed. Here are 10 well-documented examples where a deception was widely treated as true or used as “proof.”[^1_1][^1_2]

Ten “truth-like” scams

  • Piltdown Man: A forged “missing link” fossil announced in 1912 was widely accepted for decades before being conclusively shown to be a composite forgery in 1953.[^1_2][^1_3]
  • Cardiff Giant: A carved gypsum “petrified man” (1869) became a paid attraction and was treated by many as a real archaeological find until it was exposed as a hoax.[^1_4][^1_5]
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eonist / git summary with apple intelligence hack.md
Created December 16, 2025 12:30
git summary with apple intelligence hack

Yes, you can. You can use Apple Intelligence’s local on-device models to generate commit messages without downloading anything new.

The "secret" backdoor to accessing these models from the terminal is the Shortcuts app, which has a command-line interface (shortcuts) and exposes Apple Intelligence actions.

How to set it up (No new downloads)

You can build a simple "bridge" that takes your git diff, sends it to Apple Intelligence, and pipes the result back to your commit.

1. Create the Shortcut

  1. Open the Shortcuts app on macOS.
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eonist / divergent-ideas.md
Created December 14, 2025 18:30
what are some things one can do to find divergent ideas. that lives in the fringes. but might solve emergent or near emergent problems.

Finding divergent “fringe” ideas that might solve emerging problems works best as a repeatable practice: systematically scan for weak signals, spend time with lead users at the edge of need, and then rigorously stress-test the ideas before investing heavily.[1][2]

Scan for weak signals

Horizon scanning is a structured way to look for early signs (weak signals) of potentially important developments that sit outside mainstream attention today.[3][1]

  • Build a weekly “signal feed” from places where novelty appears early (new research, niche forums, small startups, policy pilots), and tag each item as “new capability,” “new constraint,” or “new behavior,” because weak signals are often subtle indicators of emerging issues.[2][4]
  • Keep a “fringe log” and deliberately include signals from subcultures and non-obvious domains, since some public-sector scanning programs explicitly target fringe areas to broaden what gets noticed.[5]

Find lead users

The lead user approach focuses on people who experience needs

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eonist / low-risk-work.md
Created December 7, 2025 14:14
low-risk-work.md

Task:

Primary objective:

Low-hanging fruit, low-risk refactoring items that don't follow the Architecture & Structure Guide and Code Style Guide

description

could you look at these documents: /Users/eon/conduit.design/_docs/code_style_guide.md

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eonist / climbing_the_wrong_hill.md
Created December 5, 2025 11:54
climbing_the_wrong_hill.md

Perfect! I found the blog post you were looking for. It's "Climbing the Wrong Hill" by Chris Dixon (not from mathewanders.com), published in September 2009. This is the exact post that uses the mountain peak and local maxima metaphor you described.

The Blog Post: "Climbing the Wrong Hill" by Chris Dixon

The Core Metaphor:

Chris Dixon uses a computer science concept called "hill climbing" to explain why smart, ambitious people often get stuck pursuing the wrong career path. Here's how he explains it:[1]

The Hill Climbing Problem

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eonist / scan_for_issues.md
Created December 2, 2025 15:43
scan_for_issues.md

/Users/eon/conduit.design/_docs/architecture_and_structure_guide.md /Users/eon/conduit.design/_docs/code_style_guide.md please read these documents. then scan the code base for lowkey low hangingfruit low risk items that doesnt follow these guids. then make a list of at least 20-40 items and save it to a markdown file for later refactoring. do not refactor yet. just search analyse and make the list

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eonist / hard_problems.md
Last active January 18, 2026 14:23
hard_problems.md

hard problems

This is how I solve bigger code challanges. Like really complex features.

  1. I asked for feedback on legacy code. pros and cons.
  2. i made my idea for v2 how it should work etc. then i asked the AI to plan it out in detail in a plan.md doc.
  3. i asked the ai to make readme doc for the feature before coding it.
  4. then i gave the ai all of these docs, and asked it to code it. it took 2h for it to finish.
  • four ais did this simultaniously. 2 in pplx. 1 cursor 1 cline. about 20$ each.