Fresh drop on r/PromptEngineering: an LLM API called Clocked, and a free hackathon with $2,000 in prizes. The organizer posted it and disclosed that up front, so treat this as a heads-up about a tool and a contest, not a review. I’m passing along what the post says. The idea is a real change from the usual “prompt it and parse it” routine.
What’s new
Clocked is an LLM API that returns structured results instead of generated text. The endpoints cover:
- decisions with probabilities (think “is this ticket urgent, routine, or spam,” with a score for each option)
- exact extractions with source positions (the quote itself, plus where it starts and ends in the document)
- PII masking (names, emails, and phone numbers swapped out before the text goes anywhere else)
- prompt-injection detection (a check on incoming text before it reaches your main model)
- grounding checks (does this answer actually follow from the source you gave it)
- doc comparison and reranking (what changed between two versions, or which search results deserve the top slot)
The hackathon asks you to build a new app that uses at least one of those endpoints. You don’t need all of them. They also chain well: mask PII first, then classify, then extract. That pipeline makes a nice demo, even though one endpoint is enough to qualify.
The twist
You don’t prompt for JSON and hope. You define the schema or the list of options, and the API returns a decision with a probability attached. For extraction, it returns the exact span plus where it sits in the source. No free-text generation in the middle.
A probability is something your code can act on. Say you route support emails. Above 0.9 on “billing issue,” send it straight to the billing queue. Between 0.5 and 0.9, flag it for a human to glance at. Below that, treat it as unknown. With generated text you end up guessing confidence from the wording. Here the number is part of the response.
If you’ve ever written a retry loop because the model wrapped your JSON in a friendly paragraph, you know why that matters. One commenter on the thread said skipping text generation and going straight to structured results makes sense for production work. Fewer moving parts means fewer surprises, and there’s no parsing layer to babysit.
I haven’t tested Clocked myself. I’m only describing what the post claims, so run your own test before you build anything serious on it.
Mini-workflow: how to enter 🛠️
- Make a new account. It comes with 4k credits.
- Add the code CLOCKEDHACKATHON for 16k more credits.
- Pick one endpoint and one annoying problem. PII masking on support tickets, or quote extraction with positions, are the obvious candidates. Other ideas: a contract checker that points at the clauses that changed, or a screen that checks user input for prompt injection before it reaches a chatbot.
- Start the app after the challenge begins. It has to be started during the challenge, and AI coding tools are allowed. So don’t dig up an old project and bolt Clocked onto it. Begin with a fresh repo, even a tiny one.
- Record a demo and push to a public repo. Both are required. Keep the demo short, and write a README that says which endpoint you used and why. 📦
The details
- Prizes: Best Overall $600, three category awards at $400 each, People’s Choice $200.
- Solo or teams, any language or framework.
- 18+, with some location restrictions. Check the rules page before you spend time on a build, especially if you’re outside the US.
- Deadline: Nov 10, 11:59 PM ET. Winners announced Nov 18.
- Today is Nov 6, so you have four days. That’s tight, but enough for a small, focused build. A rough split: one day to pick the problem and test the endpoint, two days to build, and the last day for the demo and README.
- The People’s Choice prize presumably rewards whatever people find fun or easy to grasp, so a clear idea can matter as much as a clever one.
Pro tips
- Build something narrow. A one-endpoint app with a clean demo beats a sprawling one that half works.
- Put the source-position output on screen in your demo. Highlighting the exact span in the original text is the part people will remember.
- Check how the credits get used. 20k total should go a long way, but test on small inputs first, and log every call while you build so you can see where the credits go.
- Keep a few messy, real-looking sample inputs ready. Structured outputs look great on clean text, and a judge will trust your app more if it handles an ugly support ticket or a rambling email.
- Use your AI coding tool for the boring parts, like the UI shell and the README, and spend your own time on the one idea that makes the app worth watching.
Your move
If you’ve been looking for a reason to try structured outputs without paying for it, this is a cheap way to do it. Read the rules and grab the entry form at https://clocked.rezolve.ai/challenge. Then tell me what you build! 🏴☠️
Frequently Asked Questions
Q: How is this different from asking a model to return JSON?
Prompting asks the model to write text that looks like JSON, so a missing bracket or an invented quote can still get through. With Clocked, you define the schema or the list of options up front, and the response comes back as decisions with probabilities or extracted spans with source positions. If you’ve lost days to malformed output, that gap is the whole point.
Q: Do I still need my own grounding and prompt injection checks?
The post lists grounding checks and prompt-injection detection as Clocked endpoints, so you can call them directly instead of chaining a second model call. One commenter said these built-in checks save them from the extra calls they’d otherwise have to write. Read the endpoint docs for exactly what each check returns before you depend on it in production.
Q: Can I try it without paying, and how much time do I have?
Signing up is free, and new accounts get 4k credits. Entering the code CLOCKEDHACKATHON adds 16k more, which should be enough for a small prototype. Entries close Nov 10 at 11:59 PM ET, and your app has to be started during the challenge, so don’t wait.
Structured outputs instead of prompting for JSON: free hackathon to try it ($2k prizes, closes Nov 10)
by u/SolemnSpanking in PromptEngineering