This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
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Product upvotes and comments
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LinkedIn Auto Reaction Codex
simple autoamtion binding for native codex app
Human-in-the-loop Codex skill for safer LinkedIn engagement: finds relevant posts, drafts contextual comments, avoids duplicates, and waits for approval before any action. - dipbd1/linkedin-auto-reaction-codex (You can remove the human intervention part, but it will make the code go against the LinkedIn policy)
I was looking into the new capabilities of codex app, and thought, why not make a plugin that people can use to automate the way they give reactions to LinkedIn?
So, if you can route your AI tool/agent into the native browser where you use LinkedIn, then the AI can take over and do the rest.
The common problem with this is actually the policy from LinkedIn.
Also, the site changes so much internally/technically that you can make a static caller.
So, analyzing the image and based on the image, taking a decision and then executing the reaction/comment is better.
This is what I am doing.
Give it a try.
About LinkedIn Auto Reaction Codex on Product Hunt
“simple autoamtion binding for native codex app”
LinkedIn Auto Reaction Codex was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #159 on the daily leaderboard. Human-in-the-loop Codex skill for safer LinkedIn engagement: finds relevant posts, drafts contextual comments, avoids duplicates, and waits for approval before any action. - dipbd1/linkedin-auto-reaction-codex (You can remove the human intervention part, but it will make the code go against the LinkedIn policy)
On the analytics side, LinkedIn Auto Reaction Codex competes within Social Media, GitHub, LinkedIn and Marketing automation — topics that collectively have 164.3k followers on Product Hunt. The dashboard above tracks how LinkedIn Auto Reaction Codex performed against the three products that launched closest to it on the same day.
Who hunted LinkedIn Auto Reaction Codex?
LinkedIn Auto Reaction Codex was hunted by Dip Chowdhury. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of LinkedIn Auto Reaction Codex including community comment highlights and product details, visit the product overview.
Dip Chowdhury