... moments fade in sight, yet remain painfully fresh in feeling. 2. The First Realization This is the first message the player sees on screen a quiet nudge that makes them recognize what s been missing all along. 3. The Balloon This damned red object has always been a wretched signal that something is terribly wrong. In IT, Georgie follows the paper boat before seeing the red balloon

... back to me to fix it, so yippee! Now I'm building a SaaS product on the side and it's dawning on me that this is a completely different problem. You ship new features, the codebase starts to balloon, and hopefully, someday, there will be a team who needs a single source of truth to reference. Suddenly it's a very big deal if what's written in your docs stops matching reality. So for those of you further ...

... Product Hunt community! If you've worked with proxies at scale, you know the pain: frequent IP bans killing your scraping jobs, unstable connection speeds derailing automation workflows, opaque pricing that balloons unexpectedly, and integration docs that make even simple setups take hours. We've been there too. That's why we built Pxyedge a rotating residential proxy platform designed for developers and growth teams who need reliability without the headaches. Here's what we're bringing to the table ...

... tightened scope shows in the numbers this time Comment from Omri Ben-Shoham(@omri_ben_shoham1): @Adamma appreciate the LinkedIn add, will accept and be there Friday. good to hear the scope stayed narrow on purpose instead of ballooning into a general devops platform, that's usually where these repo tools go wrong post-launch Comment from Adamma(@faithada): @omri_ben_shoham1  Really appreciate that. The scope is deliberate: repo truth, readiness, and governed execution, and we want ...

... from groups You can give a group its own AI context, and it now flows into chat, chart-editing, and automation agents whenever a member of that group is interacting. If different teams think about your data differently engineering versus sales versus

... Product Hunt We're live today with Ailoitte: Outcome-Based Engineering. Since 2017, I watched founders pay $280/hr to agencies that delivered invoices, not outcomes. Timelines slipped. Budgets ballooned. The client always absorbed the risk. So we flipped the model. Every Ailoitte engagement is fixed-price, delivered by an AI Velocity Pod activated in 48 hrs, with milestone demos every 2 weeks; you pay when working software ships. If we overrun? We absorb it. 300+ products. 22 countries. 0 hourly ...

... every line, just the risky stuff. New API integrations. Database changes. Anything touching billing. That's where the expensive mistakes live. The rest, we let it run and watch the logs. What's your threshold? What do you review vs let slide? Comment from Dylan(@liraelw5836): I read the whole thing and the 38% cost spike hit hardest. The hardcoded discount logic was a close second. We built flat rate inference at Canopy Wave for exactly this reason so cost ... ... review the logic and have it review the implementation before anything gets merged. Two things that I do almost every time that has significantly improved the quality is to have the agent do a gap analysis of the plan vs

... ProductHunt Companies are hemorrhaging money on inefficient AI usage without even realizing it. After watching countless teams, and myself, struggle to manage ballooning AI costs across multiple platforms (juggling between billing portals, losing track of spending, getting surprised by bills), I decided to build. After ~1 week, I launched (first launch) an MVP for AIBillingDashboard.com . What I built: A unified dashboard that tracks spending across all major AI providers (OpenAI, Claude, Gemini, Tavily, Pinecone, Make.com , n8n, HuggingFace, etc). Cost comparison ...