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feat: thử đẩy user_data lên
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ooker777 committed Dec 12, 2024
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19 changes: 19 additions & 0 deletions .env
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FIBERY_HOST = https://quacau.fibery.io
FIBERY_TOKEN = 26d174de.24b1cbf0079420149f218af264d06a5bf99
FIBERY_ARTICLE_DATABASE = Articles
FIBERY_ARTICLE_SPACE = Blog

# FACEBOOK_PROFILE_URL = "https://facebook.com/qua.cau.the.sphere"
# FACEBOOK_EMAIL = "[email protected]"
# FACEBOOK_PASSWORD = "Qu@cau00"

# FIBERY_HOST = https://torihi.fibery.io/
# FIBERY_TOKEN = 55a06407.9e13b61bec3b49dba58387602ac4c09df53
# FIBERY_ARTICLE_DATABASE = Articles
# FIBERY_ARTICLE_SPACE = Source

FACEBOOK_PROFILE_URL = "https://facebook.com/dohangminhtri511"
FACEBOOK_EMAIL = "[email protected]"
FACEBOOK_PASSWORD = "Kendykangta511@"

CHROME_PATH = "/home/runner/.cache/puppeteer/chrome/linux-131.0.6778.108/chrome-linux64/chrome",
4 changes: 0 additions & 4 deletions .github/cron.yaml

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34 changes: 34 additions & 0 deletions .github/workflows/Chạy định kỳ.yaml
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name: Chạy định kỳ
on:
push:
workflow_dispatch:
schedule:
# - cron: "0 0 * * 0" # Mỗi tuần
- cron: "0 0 * * *" # Mỗi nửa đêm

jobs:
cron:
name: Chạy chương trình
runs-on: ubuntu-latest
steps:
- name: Clone repo
uses: actions/checkout@v4

- name: Cài Deno
uses: denoland/setup-deno@v2
with:
deno-version: vx.x.x
- name: Cài Chrome
run: npx puppeteer browsers install chrome

# - name: Giải mã credentials
# env:
# GOOGLE_API_PASSWORD: ${{ secrets.GOOGLE_API_PASSWORD }}
# run: |
# cd Code\ hỗ\ trợ/Google\ Calendar/
# gpg --batch --yes --decrypt --passphrase="$GOOGLE_API_PASSWORD" --output credentials.json credentials.json.gpg
# gpg --batch --yes --decrypt --passphrase="$GOOGLE_API_PASSWORD" --output token.json token.json.gpg
# cd ../..

- name: Chạy chương trình
run: deno task start
11 changes: 3 additions & 8 deletions .gitignore
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user_data
# user_data
draft
.env
node_modules
credentials.json
token.json
calendarID.txt
*.html
test.py
# .env
node_modules
27 changes: 27 additions & 0 deletions Bài viết/Bloom' Taxonomy.md
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# Tóm tắt về Bloom'Taxonomy

📌

1. Remember :bbe1a9c2-31b4-486d-acf0-92e27dbddb41: **define**
2. Understand :bbe1a9c2-31b4-486d-acf0-92e27dbddb41: re-structure **outliner**, **explain** by own words
3. **Apply** :bbe1a9c2-31b4-486d-acf0-92e27dbddb41: ứng dụng cho own project hay own pain point, usecase
4. Analyze :bbe1a9c2-31b4-486d-acf0-92e27dbddb41: zoom in ⇄ **break** down
5. Evaluate :bbe1a9c2-31b4-486d-acf0-92e27dbddb41: zoom out ⇄ metadata ⇄ assign name of relationship (create relevant/ create connect) ⇄ Relationship ⇄ **Ontology** ♣️ similar, opposite … là 1 dạng grouped by
* :26d333e4-566c-4d76-aff9-2ec5ea4c1b48: Define các tên của Ontology theo 4 hướng
6. Create ⇄ evergreen ⇄ create ⇄ **new**

[Screenshot 2024-04-17 125013.png](/api/files/164802f1-1f5f-4e35-8f8c-01ca8af7d729)

[Screenshot 2024-04-17 125757.png](/api/files/49d24067-2b16-4d20-9103-9ff777730cf4)

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>
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<video src="/api/files/a7e4b38b-ff14-4c4f-bef9-e214ec6cddab" type="video/mp4" width="900" height="200"></video>

![Screenshot 2024-04-17 125757.png](/api/files/0c33316a-3a47-4d68-b701-5da7910549df#width=462&height=413)

![image.png](/api/files/9c19a640-6bf1-4547-8679-55e8756e4069#width=833&height=565)
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1 change: 1 addition & 0 deletions Bài viết/Bài viết số 4.md
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thử zxc zxczxc zxc zxc
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Great product management tools are opinionated. Or they aren’t: this is [clearly a myth](https://www.linkedin.com/pulse/myth-opinionated-software-rob-litterst/). But [they are on the rise](https://medium.com/@stueccles/the-rise-of-opinionated-software-ca1ba0140d5b), so that’s good, right?

Opinions are like belly buttons. Everyone has one. Especially when it comes to the grand debate of opinionated vs. unopinionated systems. You see it every day: it’s McDonald’s vs. Subway, microwave ovens vs. conventional ovens, macOS vs. Linux, iOS vs. Android, or, dare we say, Productboard vs. Fibery.

In this article, we dissect the basic terms and explore the underlying philosophy to help you choose the perfect product management tool. Let’s dive in. 

## Binding freedom or restrictive simplicity?

In the heyday of software development, most of the tools we used for work had a tendency to be more unopinionated (by the standards of the time, at least). Microsoft OSs, for instance, allowed for a great degree of flexibility: if you had a clear idea of how you wanted to work, you could build your own suite of products and setups with a high degree of customization. It came with a steeper learning curve and it took time to get things to work.

Slowly but surely, though, opinionated software started rearing its head. Widespread adoption, increased competition, and probably just the nature of things in software development all pushed innovation toward simplified end products. Why have infinite freedom when you can get better (business) results with higher efficiency thanks to a more restrictive ecosystem? You don’t really have to look further [than Apple](https://www.bloomberg.com/news/features/2023-07-11/switching-from-iphone-to-android-is-a-data-transfer-hell).

Yes, the most popular tools are opinionated and collaborative, [heralds of a new era are already with us](https://fibery.io/blog/no-code-revolution-why-now/). No-code tools currently mean a fresh new alternative in many areas even though they form a hip minority opposing giants like Salesforce, Google’s productivity tools, or MS Office.

## Opinionated vs. unopinionated software

Okay, let’s stop for a breather. We are close. Let’s see first how you can identify an opinionated tool:

* **It tells you how to do stuff.** You only need to think about *what* you want to do. It imposes restrictions on your workflow and guides your hand heavily to do things the way it was designed to do. 
* **It’s easy to learn.** You can get started in a few hours to days. Tools designed to get you to value fast cater to your intent: they look, feel, and sound familiar. 
* **It comes with a low degree of customization.** You can’t really tailor it to your needs. Sure, you’ll have filters and custom views, but the system is already set up to work in a certain way. The inner workings of the tool will never reveal itself to you by design.

Unopinionated software is pretty much the opposite. In other words:

* **It gives you a sandbox.** Zero restrictions, near-infinite freedom. You need to know how you want to do things before you actually do them. Or you’ll be lost and clueless, often failing to find value in the tool. 
* **It’s tough to learn.** You won’t hit the ground running in hours. First, you have to set up the tool the way you want to use it. This takes effort. 
* **It can be customized.** Dream it and implement it. Why have (and pay) for features and functions you’ll never need? Build from scratch and mold the tool the way you want to use it. 

Does this mean product management tools should be either this or that? The answer is, as you might expect, not that simple.

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# thử zxczxc zxc zxc zxc

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![Screenshot 2024-02-03 110909.png](/api/files/9a44b0a1-73e0-43c4-a9bd-ddd39ee59b6b#width=834&height=609)
16 changes: 16 additions & 0 deletions Bài viết/Using AI for product feedback management.md
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In a world chronically suffering from too much information and too little understanding, user feedback is paramount for any product's success. But with the sheer volume of feedback that companies receive, sifting through it manually is neither efficient nor effective. AI has the potential to revolutionize how we handle, analyze, and act upon user feedback.

We're diving into some cool AI applications and ideas that'll change how you see feedback. For every AI application, I will try to evaluate usefulness vs. hype.

## Summarizing feedback

Hype: 6/10\
Value: 4/10

The trivial use of AI is to summarize long feedback into shorter, digestible points, allowing product managers to quickly grasp the essence without reading through lengthy paragraphs. Many articles and vendors praise summarization as a very useful tool, but I find it relatively useless. It works only for the very specific use cases when you really need to grasp the essence of the conversation to decide whether to dig into details or not.

### Tools

Summarization is quite easy to implement, so it is likely that it might work already in your favorite tool. [Fibery](https://fibery.io/ai) was among the first to introduce it. For example, here is how summaries of customer support chats work. You can quickly review recent chats, spot some interesting topics, and dig into details if you want.

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17 changes: 17 additions & 0 deletions Bài viết/bài viết số 5 testing .md
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## heading 2

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# heading 1

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