Last week I built an automation tool that manages my daily.dev account — maintaining streaks, browsing feeds, interacting with posts, even creating content. It works. It’s efficient. And building it taught me more about the ethics of automation than any article I’ve read.
<h2>Why I built it</h2>
As developers, we automate everything. Deployments, testing, monitoring, alerts. But we rarely turn that automation inward. I wanted to explore: what happens when you apply engineering principles to your own online developer presence?
The tool handles:
<ul>
<li>Session management with automatic re-authentication</li>
<li>Feed browsing and post discovery</li>
<li>Streak maintenance through strategic reading</li>
<li>Interaction tracking and logging</li>
<li>Reading summaries — automatically generates detailed markdown reports of everything I read</li>
</ul>
<h2>The reading summary feature</h2>
One of the most useful features I added was automatic summary generation. After browsing my feed, the tool:
<ol>
<li>Fetches my full reading history with post content</li>
<li>Extracts key sections and headings from each post</li>
<li>Pulls notable comments from discussions</li>
<li>Aggregates stats — top tags, favorite sources, most-read authors</li>
<li>Writes a timestamped markdown file with everything organized</li>
</ol>
Each summary includes a per-post breakdown with content digests, key takeaways, and community highlights. Over time, these files become a personal knowledge base of everything I’ve consumed on the platform. No more “I read something about that last week but can’t find it.”
<h2>The technical challenge was surprisingly deep</h2>
What started as “just hit a few API endpoints” became a real engineering project:
Authentication was the hardest part. The SSO flow involved Ory Kratos session management, JWT tokens from different sources (cookie vs JSON body), and subtle differences in token formats that took days to debug. A 626-character token from a Set-Cookie header worked, but the 580-character token from the JSON response didn’t. Same endpoint, different extraction method, completely different results.
Rate limiting required respect. I had to build in jitter delays, cooldown periods, and error handling that backs off gracefully. Hammering APIs isn’t automation — it’s abuse.
Session persistence was essential. Logging in for every operation would be wasteful and suspicious. Storing sessions securely and refreshing them intelligently required careful thought.
<h2>The ethical questions nobody asks</h2>
Building this forced me to confront questions that most automation discussions skip:
1. Where’s the line between efficiency and inauthenticity?
If I read a post through a script vs. clicking it manually, the knowledge transfer is the same — zero in both cases if I’m mindlessly scrolling. At least the automation is honest about not reading deeply.
2. Does automation devalue genuine engagement?
When I auto-upvote posts, am I diluting the signal for posts that genuinely impressed someone? This question led me to disable auto-upvoting — I only interact with posts I’ve actually read now.
3. Platform health vs. personal convenience
Every automation that interacts with a social platform affects the ecosystem. If everyone automated their engagement, feeds would become meaningless. There’s a tragedy of the commons here.
<h2>What I actually use it for now</h2>
After building the full automation, I scaled back to using it as a productivity tool rather than a hands-off bot:
<ul>
<li>Streak maintenance — genuine value, just removes the manual check</li>
<li>Feed aggregation — pulls interesting posts for me to actually read</li>
<li>Reading summaries — generates rich markdown reports with content digests, key sections, top tags, and discussion highlights from every session</li>
<li>Interaction logging — tracks what I’ve engaged with for personal reference</li>
<li>Post creation — drafts posts that I review and edit before publishing</li>
</ul>
The automation amplifies my intent rather than replacing my judgment. And the summaries mean I actually retain what I read instead of letting it vanish into the infinite scroll.
<h2>The bigger lesson</h2>
The tools we build reflect our values. Building a bot that fakes engagement is easy. Building a tool that genuinely helps you be a better community member is harder — and more rewarding.
Every developer will face this choice as AI makes automation trivially easy. The question isn’t “can you automate it?” — it’s “should you, and how do you do it responsibly?”
What’s your take on automation in developer communities? Where do you draw the line?

sirajju

A developer built an automation tool to manage their daily.dev account, handling session management, feed browsing, streak maintenance, and reading summary generation. The technical challenges included reverse-engineering SSO flows with Ory Kratos, JWT token handling, rate limiting with jitter delays, and session persistence. The more interesting takeaway is the ethical reflection: auto-upvoting was disabled after recognizing it dilutes genuine signal, and the tool was scaled back to amplify human intent rather than replace it. The post frames automation ethics as a tragedy of the commons problem that every developer will face as AI makes bots trivially easy to build.

I Built an AI Agent That Manages My Developer Account — Here's What I Learned About Automation Ethics

The auth debugging section is so real — I’ve spent more time fighting OAuth and JWT edge cases than I’ve spent on actual feature logic in some projects. Also appreciate the honest take on scaling back the automation. Tools should augment humans, not replace genuine interaction.