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VerdictInsufficient public evidence

Inconclusive.

Hugin did not capture enough deterministic public evidence to support a scam, suspicious, or clean label. Re-scan when Reddit comments and account metadata are available.

r/buildinpublicPosted by u/Downtown_Pudding9728Original
Sources6/12checked
Flags00 high, 0 med
Work33 limits
People140 histories
Scan shape50% source coverage
High flags0
Medium flags0
Work signals3
Sources checked6
Decision path

Hugin marked this inconclusive because the available signals were mixed or incomplete, and missing author metadata keeps the clean-read confidence low.

  1. The final verdict text came from the AI verdict engine using the stored structural signal block.
  2. The scan reviewed 19 comments and 14 unique commenter accounts.
  3. Signal count: 0 high, 0 medium, 0 low flags; 0 coordination-class signals.
Author metadata gap

15 scanned authors had unknown account age. Hosted profile metadata and archive fallbacks were exhausted, so Hugin stopped after 5 failed fetches and left 10 profile lookups unattempted. Absence of young-account signals is lower confidence.

JSON
Full evidence trailSources, public checklist, values lens, network map, account coverage, archive, and sharing tools.
Validation protocol

Review before sharing.

Hugin reports are evidence packets, not accusations. Use the rating as a prompt to inspect sources, limitations, and archived material before quoting a claim elsewhere.

The post
I quit my job to vibe code a LinkedIn Automation SaaS tool, with no Engineering background, and made ~$3.6k in the first 3 months
Post age
33.6h
Commenters scanned
14
<7d-old accounts
0 (0%)
Removed comments
0
Median age
unknown

Source checks

Checked
6
Limited
2
Needs key
0
Total sources
12
checked / thread
Reddit thread snapshotReddit JSON or RSS

33 public comments loaded for r/buildinpublic.

checked / thread
Comment evidence archiveHugin snapshot

Public comment bodies were retained with the report snapshot.

limited / accounts
Author account metadataReddit account about + old Reddit profile + Arctic Shift/PullPush archives

15 author age values were unavailable; 10 not attempted after hosted metadata fallbacks were exhausted.

limited / accounts
Recent author historyReddit user activity + old Reddit profile + Arctic Shift/PullPush archives

1 selected author history checked; 1 unavailable.

checked / coordination
Reply graphHugin graph pass

19 reply edges mapped.

checked / coordination
Writing-style comparisonAI stylometry pass

0 same-hand writing pairs surfaced.

checked / coordination
Shared identifiersHugin extractor

0 unique external identifiers extracted.

checked / archive
Prior report matchesHugin report archive

0 prior archive matches returned.

Show your work

Deterministic explanation of the stored scan inputs behind the verdict. This is not hidden model reasoning; it is the evidence checklist Hugin can show publicly.

Verdict path · AI summary

Hugin marked this inconclusive because the available signals were mixed or incomplete, and missing author metadata keeps the clean-read confidence low.

  1. The final verdict text came from the AI verdict engine using the stored structural signal block.
  2. The scan reviewed 19 comments and 14 unique commenter accounts.
  3. Signal count: 0 high, 0 medium, 0 low flags; 0 coordination-class signals.
  4. The scan did not have enough clean metadata coverage to call the thread legitimate.

What limited confidence

uncertainAuthor metadata gap

15 scanned authors had unknown account age. Hosted profile metadata and archive fallbacks were exhausted, so Hugin stopped after 5 failed fetches and left 10 profile lookups unattempted. Absence of young-account signals is lower confidence.

What kept the rating lower

cleanNo reply ring detected

Hugin mapped 19 reply edges and did not find a mutual-reply clique.

cleanStylometry pass was clean

The writing-style comparison ran and did not surface same-hand pairs.

Limitations
  • 15 author account ages were unavailable; 10 profile lookups were skipped after hosted metadata and archive fallbacks were exhausted.
  • 1 selected author history was unavailable to the scan.
  • Username shape alone is never treated as a finding; it is only context when stronger public signals also appear.
Rating thresholds
  • Likely scam: multiple high-severity signals, prior identifier reuse, or several coordination signals stacking together.
  • Suspicious: one high-severity signal, multiple medium signals, or one concrete coordination signal that deserves review.
  • Inconclusive: weak, conflicting, or partial signals where the scan cannot justify either trust or a stronger warning.
  • Looks legitimate: no structural red flags, available metadata, and clean coordination passes.

Values lens

Use standardEvidence, not pile-ons

Use scans to slow down, inspect public signals, and keep uncertainty visible. Never use them to harass, shame, or flatten people into a verdict.

EvidenceDignityRepairCommon good
source humilityhuman dignityno pile-onsrepair when possible
Fair-use checks
  • What was observed, and what is interpretation?
  • What data is missing, blocked, or confidence-limiting?
  • Would the wording feel fair if it were about someone you care about?
Stable reference

What the post is doing

  • Some account metadata was unavailable

Coordination map

Who replied to whom in the scanned comments. Organic threads branch out from the post; accounts that reply back and forth to each other (red links) or hub around one shared identifier (dashed amber) are the structural fingerprints of a coordinated pod.

u/Downtown_… (OP)u/withKairou/Grumpygib…u/boatnotea…u/ChrisHarp…u/hosamalsw…u/ilackemot…u/JohnPillayu/KayKongou/Kitchen_C…u/Mobentrep…u/sigmafica…u/Smart-Gif…u/Startup_b…u/Sure_Fig5…
  • mutual-reply ring member
  • account under 30 days
  • other commenter
  • replied to each other
  • shared identifier

Commenter patterns

Recent public Reddit activity for the OP and selected accounts, plus same-hand writing checks when the stylometry pass runs. These are coverage-limited evidence summaries, not identity or availability claims.

Reddit blocked the recent-activity fetch from Hugin's scanner during this run. Treat this as missing coverage, not a finding about the account.

Stylometry

The writing-style pass ran and did not surface same-hand pairs.

Account age coverage

OP and scanned commenters are shown when Hugin recovered profile metadata or an oldest-public-activity age floor. Lower-bound ages are labeled as estimates; unknown age remains missing coverage, not a finding about the account.

Reddit blocked metadata
Reddit blocked metadata
Reddit blocked metadata
Reddit blocked metadata
Reddit blocked metadata
u/KayKongounknown
metadata not attempted after block
metadata not attempted after block
metadata not attempted after block
metadata not attempted after block
metadata not attempted after block
metadata not attempted after block
metadata not attempted after block
metadata not attempted after block
metadata not attempted after block
metadata not attempted after block

Archived evidence

Snapshot of the post and comments at scan time. Preserved here so the evidence survives even if it gets deleted on Reddit.

Post body — by u/Downtown_Pudding9728
Last Christmas I was at my parent’s place, pretty bored just watching TV on the couch, and realised I wasn’t really satisfied with my life. My job wasn’t going anywhere, and I felt like I really had no direction in life. I had spoken with a friend around that time, who had vibe coded his website for his business, and it looked really cool. So I spoke with ChatGPT to see what i could possibly build that could be interesting, but done in an innovative way. As I worked in sales already, it suggested that I lean into my own experience, and build something for my own use case. I’d been using LinkedIn automation tools to help generate leads, but I kept getting warnings from LinkedIn from the tools I was using, so I wasn’t using them regularly. So, after a lot of back and forth conversation with AI, I realised that there was a big opportunity to create a tool that was safer than anything else out there; Every tool I’d been using operated either on the cloud or used plugins - there were almost none that simply operated on your desktop, and this would most likely remove my issue of getting warnings and appear natural to LinkedIn. So, I decided to build something for myself primarily, in the sales job that I was in - could I build something that would help me generate more leads without risking my account as much? Turns out, I could. It definitely wasn’t easy, there was a very steep learning curve in terms of learning how to build something with AI, as well as making complex design and architectural decisions. I also made a lot of mistakes at first with building new features without testing first. As a result, there were tonnes of errors and bugs at first, but I spent a huge amount of time on hardening the tool to ensure that it’s now highly unlikely to break, and even if it does, it’s quick/easy to diagnose and implement fixes. It was a complex build as it’s essentially two code bases - a web dashboard where people can control their campaign settings and messaging sequences, with an inbuilt CRM, unified inbox, analytics etc., along with building the software itself separately, which automates LinkedIn in a dedicated browser on people PC’s. And not only did I have to build it, but I had to make sure it actually worked effectively. So I used it myself on my own account throughout the testing phase. I made sure that the tool had strict daily limits on actions, randomised delays between connection requests and follow up messages, along with effective messaging, written by Claude Sonnet via API. And it worked - in my first campaign in my old job, I got a 40% acceptance rate and a 25% response rate. What I realised along the way though, was that working on the tool itself was much more enjoyable than my sales job, so, I decided to quit my job and go all in on building and working on the tool. I made it into a business and took a leap of faith. Now, the tool has had 260 signups to free trials, many of whom converted into paying customers, and so far hovering around $3.6k in total revenue since launching in April, completely bootstrapped. Not a life changing sum yet but the first few months have been very promising, and there’s clearly a demand for a tool that’s safe for LinkedIn accounts and effective at booking meetings. Anyway, I hope this story inspires people to follow your passions and keep going!
Comments captured (33)
  • Very inspiring. Thanks for sharing. But do you think linkedin will slowly find a way to block it to make their environment safe? Also how did you market it? If you would like to share. Thanks
  • There are many other automation tools that are much larger than mine, and have existed for up to 10 years doing the same thing. LinkedIn does occasionally ban some, but typically it just means the company profile/founders profile is taken down from LinkedIn (like with HeyReach). HeyReach was unaffected by this and still works for its users, so while I’d rather not lose my own LinkedIn account, I’m not concerned currently. Also, I’m building an email, SMS, and cross-app voice note functionality, so ZenMode will be multi-channel within the next few months, I’m just starting with LinkedIn first. With marketing, I actually use ZenMode itself to do LinkedIn outreach in my own account, to promote the tool (ie dogfooding). I also post a lot on LinkedIn, X, Reddit, and reply to industry relevant comments where possible too. Just recently I’ve started doing Google ads, with limited results so far. I also did a lot of work on SEO, and rankings have been improving slowly. Hope that helps!
  • So what do you think the reason your user choose your automation rather than others that already in the business for 10 years?
  • Great progress, congrats! I wonder how much time it took to create the SaaS from scratch and what AI did you use along the way for coding?
  • Took a huge amount of time - I’ve been working on it for 6 months, mostly 8-10 hours a day (even on weekends) and I feel like I still have a huge amount more to do. I’ve pretty much exclusively used Claude, Claude code and vercel for this.
  • be very careful with linkedin automation; recently gojo berry got its entire platform nuked for this; linkedin is super strict
  • What happened to Gojiberry specifically? Or did their users simply get banned? (Which happens often with cloud/plugin tools)
  • Impressive, congrats! I’m a solo founder too, building a LinkedIn outreach agent and took me 3 months to build the first version (pre-AI) and many more months just keeping the account from getting banned by LinkedIn. That anti-ban piece is brutally underrated. Took me way too long to crack the MRR side, so seeing you pull this off is genuinely motivating. Kudos man!

Original on Reddit: https://www.reddit.com/r/buildinpublic/comments/1ugub8m/i_quit_my_job_to_vibe_code_a_linkedin_automation/ — “I quit my job to vibe code a LinkedIn Automation SaaS tool, with no Engineering background, and made ~$3.6k in the first 3 months”

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