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Case study  ·  Cake or Fake  ·  Hiring intelligence

Your buyer is in the thread. So are a hundred people who aren't.

Cake or Fake is an AI extension that helps people hire the right freelancer — and screen out the fakes. We built and run their community agent: it shows up in hiring and freelancing communities, leads with genuine help, and mentions the product only when that's the honest answer. A human approves every word.

Category
Hiring intelligence · Chrome extension
Where it works
Reddit · X · LinkedIn · YouTube · Meta
Model
Research & Recommend · human-approved

The client

Cake or Fake helps the person doing the hiring make a confident call — screening out the fakes, and surfacing the candidates actually worth their time.

You post a job on Upwork and, by lunch, your inbox is full of noise: eighty near-identical proposals, polished by AI, from people who didn't read your brief. The old trick of deleting the badly written ones no longer works, because now they're all written well. Cake or Fake sits on top of Upwork and reads what a human can't at that volume — profiles, reviews, work history, proposal quality — and hands back a ranked, flagged shortlist in minutes. It's the first tool of its kind built for the person hiring, not the freelancer applying.

The challenge

Their buyer is outnumbered three to one — by people who look exactly like them.

In every hiring subreddit and freelancing forum, the freelancers looking for work outnumber the people hiring by roughly three to one. They use the same words, sit in the same threads, and ask about the same platform. A keyword match for "Upwork proposals" is far more likely to be a freelancer polishing theirs than a founder drowning in them.

And these are communities — Reddit above all — that spot a marketer on sight and ban a bot on reflex. Point a blunt tool at them and you get the worst of both: you reach the wrong audience, and you get removed for trying. The task wasn't to broadcast into hiring conversations. It was to find the few that were the right conversations, and earn a place in them.

The keyword was never the hard part. Telling the buyer from the seller was.

The problem the build was designed around

What we built

An agent that tells your buyer from everyone who looks like one.

It reads the communities where hiring actually happens, and before it drafts a single word, it works out whether the person is there to hire or to be hired. Freelancers looking for work are passed over, however on-topic the thread. When the poster is a real buyer, it writes a reply in the voice of a seasoned hiring manager — direct, useful, a little opinionated — that leads with help and mentions the product rarely, always with disclosure.

And it never posts. Every draft is scored, queued, and waits for a person on the Cake or Fake team to approve, edit, or kill. Nothing reaches a community without a human on it — and every edit and every kill becomes a rule the agent follows the next day.

  • Buyer-first, or it doesn't speak
    Every thread is classified hirer-versus-freelancer before drafting. If the poster is there to win work, not hire, the agent moves on — no matter how relevant it looks.
  • Real help before product, always
    Most replies mention nothing to sell. Cake or Fake comes up only when a recommendation is the genuinely honest answer — and never without disclosing the connection.
  • Written to be read, not detected
    Replies sound like a real practitioner — varied in length, specific to the thread, occasionally imperfect. The way people actually write, not the way a template does.
  • Never sells to someone venting
    A person burned by a bad hire gets empathy and a useful tip, never a pitch. Reach never outranks the room, and it never helps a freelancer win work — that's the client's counterparty, not their customer.
  • It never posts unsupervised
    Every draft waits for a human. This is the one law the whole studio runs on — a machine never speaks for a brand on its own.

What it sounds like

Real help first. The product only when it's the honest answer.

Reddit · r/Entrepreneur
"Posted my first dev job, woke up to 90 proposals that all say the same thing. Where do I even start?"
Ninety is normal now, and about eighty of them didn't read your brief. Fast first pass: delete anything that doesn't reference a specific detail from your post — that clears half in minutes. Then ignore the star rating and read the actual reviews. You want clients naming the person and describing what they did, not a wall of "great work." A portfolio of only tiny $50–100 jobs is a yellow flag — those reviews are the easiest to manufacture. Whatever survives that is your real shortlist.
Approved by the team · no product mentioned
Reddit · r/smallbusiness
"Is there actually a tool that tells you if an Upwork freelancer is legit before you hire?"
Honestly, nothing replaces a small paid trial task, so budget for one regardless of what you use. For the screening itself: check whether reviews name the person, look for a consistent track record over years, and be wary of a block of identical five-stars. Full disclosure — I work on a tool called Cake or Fake that scores all of that automatically and flags the AI-written proposals — but the manual version above genuinely works if you've got an hour.
Approved by the team · the rare, honest mention

Illustrative, drawn from real drafts. Most mention no product at all — which is exactly what makes the rare one land.

How it runs, every day

Six steps, and a person at the only one that reaches the public.

01
Listen
Scans the hiring and freelancing communities where Cake or Fake's customers gather, across six-plus platforms, several times a day.
02
Tell buyer from seller
Classifies who's actually there to hire before drafting a word. Freelancers looking for work are skipped, however relevant the thread.
03
Read intent
Distinguishes someone drowning in proposals from someone burned by a bad hire from someone just venting — and treats each differently.
04
Draft in voice
Writes a platform-native reply in the voice of a seasoned hiring manager: useful first, product rarely, disclosure always.
05
Score & queue
Ranks the day's strongest opportunities into a review sheet, so the team spends its time only on what's worth posting.
06
A human approves
The team approves, edits, or kills each draft. Every decision is distilled into a rule the agent follows tomorrow.

Why it matters

The hard part was never finding conversations. It was finding the right ones.

Any tool can surface every thread that mentions your category. The value is in the handful that count — your actual buyer, not the crowd that looks like them, reached with something genuinely worth reading. Cake or Fake is where we proved a community agent can do exactly that: pick the real customer out of a noisy, look-alike market — and sound like a person worth listening to while doing it. If it works in a room this crowded, it works for yours.

By design

6+
platforms monitored, every day
~9/10
surfaced threads are an actual hirer, not a freelancer
80–90%
of drafts mention no product at all
0
posts published without a human

The engagement is early, and we treat it that way. We report monthly, and stay honest about the part that compounds — the trust, the awareness, and the right conversations becoming the right customers over time. Authority in a community isn't a campaign; it's earned one genuinely useful reply at a time.

Considering communities as a channel?

Your customers are already discussing the problem you solve.

If your product is one people research, compare, and ask peers about before they buy, that decision is happening in communities — not on your site. We build the agent that shows up there helpfully, finds the people who can actually buy, and never says a word without your approval. Book a 30-minute fit call. If it isn't the right move for you, we'll say so.

Book a fit call

No hard sell. Just a straight conversation about whether this fits.

AI agents that build your brand's authority, and a real understanding of what you do, in the conversations that matter, with a human on every word.

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