Hi all Hunters, I have built an application by following Andrej Karpathy's LLM council approach, which simulates the proceedings of an entire courtroom. Each agent has a role to play; one is a prosecutor, another is a defender, another is the judge, etc. Each is an individual DeepAgent with their own set of skills and tools.
The backend is built using FastAPI, and the Frontend uses React.
I will attach a video here as well so that interested people can go and check it out. Please feel free to reach out to me for any queries you might have.
When writing or optimizing articles for search engines, striking the right balance with term frequency is essential. Overusing target keywords can lead to search engine penalties, while underusing them might make it harder for algorithms to grasp the main topic.
Our PRs were going through AI code review like everyone else's. Every PR came back with a long list of comments: naming, style, a missing null check, "consider extracting this function". We read all of it, fixed what made sense, and merged.
Then some of those reviewed, approved, "looks good" changes still broke in production.
The review wasn't wrong. It just answered a different question. It told us whether the code looked right. It never told us whether this change, in this part of the codebase, would hold up once it shipped.
Hi everyone, I'm Mia from Coolplay. Tomorrow we're launching Music MCP on Product Hunt.
It's a free Mac menu bar app that gives your AI agent Apple Music. Ask Claude, Codex or Cursor for a mood, something new that fits your taste, or the acts playing a venue near you, and it finds the songs and plays them.
It runs as a local MCP server on your Mac and is its own player. No account, no API keys, and it only reads your library if you switch that on.
Before we launch: what would you ask your AI to play? And what do you think it would get wrong?
Hi, my name is Stefan and I keep daydreaming about opening a caf and wondering if the numbers would actually work. So I built Caf Empire, a business simulation where you run a caf , set prices, hire staff, manage stock and suppliers, take loans, and all your decisions generate real financial statements (P&L, balance sheet, cash flow).
There's a Student Mode aimed at people learning accounting or entrepreneurship, where it adds quizzes built from your own numbers, "explain this" tips on every line, and CSV export for Excel/Power BI, but also Tycoon mode for more advanced functionalities like franchising, opening a roastery, rivals, market share, reviews & reputation, seasons, etc.
A few weeks ago I shared Reporting SaaS here, and the feedback was clear: nobody wants "automated reports", people want to stop losing money without noticing.
So that's what it does now. Every Monday, a Shopify store owner gets a PDF report that explains why sales moved. And when discounts, refunds or cancellations run well above normal, the report puts a dollar figure on the loss, names the cause (the discount code, the most refunded product, the main cancellation reason) and suggests one action. If there's no clear cause, it doesn't invent one.
