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Hacker News learning resources on any topic, sent by email

by Mindketn8n workflowEducation
Newversion 1 · updated
Nodes10Apps3Like

Overview

  1. Google Gemini Chat Model
  2. GetTopicFromToLearn
  3. SearchAskHN
  4. SplitOutChildrenIDs
  5. FindHNComments
  6. CombineIntoSingleText
  7. Basic LLM Chain
  8. Convert2HTML
  9. SendEmailWithTopResources
  10. Finished
Hacker News learning resources on any topic, sent by email, picture 1
‹2 / 2›

An n8n workflow with a small form: you give it a topic and an email address. It reads the comments under Ask HN posts on that topic, has a Google Gemini model pick out the resources people recommend, and emails you the list.

Hacker News learning resources on any topic, sent by email is an n8n workflow in the Education category, listed by Mindket. It is free. This is version 1, last updated on . Download it on this page or copy its JSON, then import it into an n8n canvas. Nothing runs until you activate it in n8n.

At a glance

Runs in
  • n8n Cloud: import the file into a new workflow there
  • Your own n8n server: the same file and steps
  • Another mail route: replace SendEmailWithTopResources with a Gmail or other mail node and fill its fields from the same values
  • Another model: swap the Gemini node for a different chat model node

Platform

n8nWorkflow automation, in n8n’s cloud or on your own server
Connects 3 apps

How it works

Trigger

Form

It starts when someone submits a form with:

  • I want to learn: the topic, such as Python, DevOps or AI
  • What’s your email ?: where to send the list, required

Actions

  1. The Hacker News node searches for up to 150 Ask HN posts that match the topic
  2. The workflow splits out the ids of the top-level comments under those posts
  3. Each comment is fetched from the Hacker News API, one request per id
  4. The comment texts are joined into one list
  5. A Google Gemini model keeps the comments that name resources and groups them by type and level, in Markdown
  6. The Markdown becomes HTML and is emailed to the address from the form

Result

An email with the learning resources people recommend on Hacker News, grouped by type and level, with a link where a comment gave one

Integrations

What you need before you start.

Hacker News

Source of the advice

Finds Ask HN posts on the topic and returns each top-level comment under them.

NeedsNothing: no account or key

Google Gemini

Language model

Reads the comments, keeps the ones that name resources and writes the grouped list.

NeedsGoogle Gemini API key

Email (SMTP)

Delivery

Sends the list as an HTML email to the address from the form.

NeedsAn SMTP account and a sender address

Workflow check

Checked by Mindket on 13 Nov 2026

Steps
9 steps, starting on a form
AI
1 step calls an AI model: Basic LLM Chain
Sign-ins
Signs in to: Email and Google Gemini
API keys
No API key is left in the file
Step types
Mindket’s checker reads all 9 of its step types

Read from the workflow’s file, not from a run.

About

What it is

This n8n workflow turns Hacker News advice into a reading list. You fill in a small form with a topic and your email address. The workflow searches Hacker News for Ask HN posts on the topic and collects the top-level comments under them. A Google Gemini model keeps the comments that name courses, books, articles or videos and groups what they name by type and level. The list reaches you as an email. Ten nodes do the work.

Who it suits

Self-taught learners who want a starting list for a new subject, and people who write or teach and want to see what a technical crowd recommends. Skip it for a topic so narrow that no one has asked about it on Ask HN, because the list can only be as good as the comments it finds.

Who uses it, and how
IndustryWho uses itHow they use itExample
EducationSelf-taught learnersGet a starting list for a new subjectA learner asks about Rust and gets books and talks sorted by level.
EducationTeachers and course writersSee what practitioners recommendA teacher checks which free courses come up for data science.
SoftwareEngineers changing stacksFind what to read firstAn engineer moving into DevOps asks for the best starting guides.
ContentNewsletter writersDraft a roundup of resourcesA writer asks about machine learning and edits the email into an issue.

You need a little n8n: import a file, add a Google Gemini credential and an SMTP credential, and run the form.

Where to use it

Any n8n that can reach Hacker News, Google’s Gemini API and an SMTP mail server will run it. The form opens from the GetTopicFromToLearn node.

  • n8n Cloud: import the file into a new workflow there
  • Your own n8n server: the same file and steps
  • Another mail route: replace SendEmailWithTopResources with a Gmail or other mail node and fill its fields from the same values
  • Another model: swap the Gemini node for a different chat model node

Setup

Download saves a zip with workflow.json and Mindket’s setup notes in your downloads folder. Setup is two credentials and one sender address.

What you need first
NeedDetail
n8nOn n8n Cloud or on a server of your own
Google GeminiAn API key
EmailAn SMTP account that can send mail
  1. In n8n, create a workflow, open its menu, choose Import from File and pick workflow.json.
  2. Add a Google Gemini (PaLM) API credential with your key and select it in Google Gemini Chat Model. The node is set to models/gemini-3.6-flash, the swap for the file’s gemini-1.5-flash, which Google no longer lists.
  3. Add an SMTP credential and select it in SendEmailWithTopResources. Replace <YOUR_SENDER_EMAIL> in its From field with an address your mail server lets you send from.
  4. Open GetTopicFromToLearn and press Execute workflow. The form opens in a new tab. Fill it in and submit.
  5. Wait for the run, which can take minutes for a common topic, then read the email.

How to use it

Type a topic and your address and submit. The workflow searches Ask HN posts that match the topic, fetches the top-level comments under them one by one, joins them into one text and sends it to Gemini. The prompt asks for the best resources, grouped by type and level. A Markdown step turns the reply into HTML, and the email step sends it.

What to change for a different result
To changeWhere
The topic and the addressThe two fields in GetTopicFromToLearn
How many posts are searchedlimit in SearchAskHN, 150 as shipped
What the model looks for and how it lays out the listThe prompt in Basic LLM Chain
The modelGoogle Gemini Chat Model
The subject and wording of the emailSendEmailWithTopResources

Example

A learner types Rust and an address and submits the form.

The email lists resources under headings such as books, courses and videos, each with a one-line note and a link when a comment gave one. Treat it as a starting point. The model summarises what commenters said, so a resource can be dated or wrong.

For newcomers and experts

If you are new. n8n draws a workflow as boxes joined by lines, and each box, a node, does one job. This one starts from a form that n8n hosts for you. Hacker News is a discussion site, and the answers under an Ask HN post are often a good list of what people in the field trust. The workflow reads those answers so that you do not have to.

For experts. The Hacker News node in SearchAskHN searches through Algolia. It returns up to 150 matching posts, and each post carries the ids of its top-level comments in a list called children. Next, SplitOutChildrenIDs makes one item per id. After that, FindHNComments fetches each comment from the Hacker News Firebase API. Then CombineIntoSingleText collects the comment texts into one list, and Basic LLM Chain places it in its prompt.

Where to look closer
NodeWhat it doesWhat to know
GetTopicFromToLearnShows the form and starts the runThe email field is required and the topic field is not
SearchAskHNFinds up to 150 Ask HN posts that matchA topic with few posts gives a thin list
SplitOutChildrenIDsMakes one item per comment idA common topic gives thousands
FindHNCommentsFetches each comment from the Hacker News APIOne request per comment, in turn
CombineIntoSingleTextJoins the comment textsThe comments are HTML
Basic LLM ChainAsks Gemini for the best resourcesThe prompt sets the categories and the layout
SendEmailWithTopResourcesSends the HTML emailNeeds an SMTP credential and a sender address

Good to know

The workflow can read thousands of comments in one run, and its form is open to anyone who has the address.

  • Model: Google’s deprecations page, read on 12 November 2026, lists gemini-2.0-flash for shutdown on 1 June 2026 with gemini-3.6-flash as the replacement, and gemini-3.8-flash as the newest Flash model. The file’s gemini-1.5-flash is no longer listed. Mindket’s copy sets models/gemini-3.6-flash
  • Size: on 12 November 2026 the topic python returned 150 posts and 3,276 top-level comments. The run fetches each comment in turn and sends all the text to the model in one call, so it can take minutes and can pass the model’s input limit. Lower limit in SearchAskHN to cut both
  • Prompt fix: the prompt used a form field called Learn once, and the form has no such field, so that line came out empty. Mindket’s copy points it at the topic field
  • Sender: the file named its author’s own mailbox as the sender. It is now <YOUR_SENDER_EMAIL>, so fill in an address your SMTP account may send from
  • Judgement: the model weighs what commenters wrote. It may miss a good resource that nobody named, and it can repeat a claim that is wrong
  • Open form: once the workflow is active, anyone who has the form’s address can start a run and use your Gemini and mail quota
  • Your data: the topic goes to Hacker News’s search, the comment text goes to Google, and the address is used to send the email
  • Billing: one model call per run, sized by the comments collected
  • Credentials: the JSON holds none

README and files

README

Hacker News learning resources on any topic, sent by email

An n8n workflow with a small form. You give it a topic and your email address. It collects the top-level comments under
Ask HN posts on that topic, has a Google Gemini model pick out the books, courses, articles and videos people recommend,
and emails you the list.

What is inside

  • workflow.json: the workflow as n8n exports it, 10 nodes, no sticky notes. It holds no credential.
  • README.md: these notes.

What we changed from the original copy

  • The model node and the email node were linked to credentials in their author's n8n. The links are gone, so select your own.
  • The model was models/gemini-1.5-flash, which Google no longer lists. It is now models/gemini-3.6-flash.
  • The sender address was the author's own mailbox. It is now <YOUR_SENDER_EMAIL>.
  • The prompt used a form field called Learn once, and the form has no such field, so that line came out empty. It now reads
    the topic field, I want to learn.
  • The form's webhook id is gone, so n8n makes a new one.
  • Nothing else. The file has no Code node.

Before you start

  • An n8n instance, on n8n Cloud or your own server.
  • A Google Gemini API key.
  • An SMTP account that can send mail: host, port, user and password.

Set it up

  1. In n8n, create a workflow, open its menu and choose Import from File. Pick workflow.json.
  2. Add a Google Gemini (PaLM) API credential with your key. Select it in Google Gemini Chat Model.
  3. Add an SMTP credential. Select it in SendEmailWithTopResources and replace <YOUR_SENDER_EMAIL> in its From field with an
    address your mail server lets you send from.
  4. Open GetTopicFromToLearn and press Execute workflow. The form opens in a new tab. Fill it in and submit.
  5. Wait for the run. A common topic can take minutes. Then read the email.

How a run goes

  1. GetTopicFromToLearn shows a form with two fields, the topic and your email address, and starts a run when it is submitted.
    The page that follows tells the person an email is on its way.
  2. SearchAskHN uses the Hacker News node to search for up to 150 posts tagged Ask HN that match the topic.
  3. SplitOutChildrenIDs turns the list of comment ids on each post into one item per id.
  4. FindHNComments fetches each comment from the Hacker News API, one request per id.
  5. CombineIntoSingleText joins the text of all the comments into one list.
  6. Basic LLM Chain puts that list in a prompt and sends it to Google Gemini Chat Model. The prompt asks for the best
    resources, grouped by type and by level, with a link when a comment gave one, and for the answer in Markdown.
  7. Convert2HTML turns the Markdown into HTML.
  8. SendEmailWithTopResources emails it to the address from the form, after a first line that says how many comments were read.
  9. Finished marks the end.

Change the look

  • The topic and the address: the two fields in GetTopicFromToLearn.
  • How many posts are searched: limit in SearchAskHN, 150 as shipped.
  • What the model looks for and how it lays the list out: the prompt in Basic LLM Chain.
  • The model: Google Gemini Chat Model.
  • The subject and the wording of the email: SendEmailWithTopResources.

Good to know

  • Model: Google's deprecations page, read on 12 November 2026, lists gemini-2.0-flash for shutdown on 1 June 2026 with
    gemini-3.6-flash as the replacement, and gemini-3.8-flash as the newest Flash model. The file's gemini-1.5-flash is no
    longer listed. Mindket's copy sets models/gemini-3.6-flash.
  • Size: on 12 November 2026 the topic python returned 150 posts and 3,276 top-level comments. The run fetches each comment in
    turn and sends all the text to the model in one call, so it can take minutes and can pass the model's input limit. Lower
    limit in SearchAskHN to cut both.
  • The model judges what commenters wrote. It may miss a good resource that nobody named, and it can repeat a claim that is wrong.
  • The form is public once the workflow is active: anyone who has its address can start a run and use your Gemini and mail quota.
  • Your data: the topic goes to Hacker News's search, the comment text goes to Google, and the address is used to send the email.
  • Billing: one model call per run, sized by the comments collected.
Files
NOTICE.md  706 B
README.md  4 KB
workflow.json  8 KB

3 files, 13 KB, downloaded as a zip.

What’s new

  • Version 1 · 2026-11-12

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