DevTool & AI 商机

AI agents are getting smarter every day, but there’s a growing risk we don’t talk about enough: we’re running third-party agent skills on our machines without really knowing what they can do. That’s where SkillGuard stands out. It scans AI agent skills for potential security threats—like file access or shell execution—before you run them, helping developers catch issues early instead of reacting after damage is done. Open-source, developer-friendly, and very timely as agent ecosystems continue to grow. Definitely worth checking out : https://t.co/kCgJ65HUZR #AIAgents #CyberSecurity #DevTools #OpenSource #ProductHunt

This is how we hire at @uselayercode now We had to completely rethink the process in the last few months Live coding (with ai) is the only way to really understand how someone can wrangle coding agents productively

I just shipped Distill - payment recovery for SaaS. Failed payments cost you 9% of revenue. Most founders don't even track it. Distill: → Detects failed Stripe/Paddle/LemonSqueezy payments → Auto-retries at optimal times → Sends recovery emails → Shows exactly how much we saved $9/mo.

"Did you know many distributors are trapped in manual order entry chaos? 😱 Struggling with outdated customers costs time & money! 💸 Is there a tool to integrate WhatsApp orders seamlessly? Or is hiring data entry help the only option? 🤔 #B2B #Efficiency #BusinessSolutions #O…

I went deep into thousands of “I wish there was an app for this” posts. Not for ideas. For truth about demand. Here’s what people are actually telling us 👇 1/ Requests ≠ revenue Productivity gets the loudest noise. Education, self-improvement, and finance get the wallets. Attention is cheap. Willingness to pay isn’t. 2/ The quiet anti-cloud shift A real chunk of users want: • Offline-first • Privacy-first • No logins Subscription fatigue is pushing people back to simple, local software. 3/ The best specs are already written • ADHD communities describe pain in extreme detail • Developers rant in near-perfect requirement docs • Parents explain problems emotionally and practically These aren’t complaints. They’re free product briefs. 4/ Where money beats volume Finance users say “I will pay” more than anyone else. E-commerce operators pay to save minutes. Travel users pay only when tools actually remove stress. 5/ Overlooked opportunities Desktop apps are small in volume, high in intent. Minimal tools win where pain is high. One long angry post > 100 vague feature requests. 6/ Timing is a signal Pain spikes early in the week. January amplifies health + habit problems. Smart home users don’t want more devices — they want better data. TL;DR Build for pain, not hype. Follow willingness to pay, not loudness. Angry, detailed posts are the market telling you what to build. Most founders just aren’t listening.

Before Ossenna: spreadsheets multiplying overnight,dashboards gaslighting everyone,data buried in endless tabs,Slack on fire,meetings about meetings,and someone definitely broke production again / After Ossenna: organized pipelines,peaceful teams,real time insights @DataHaven_xyz

Invoice processing drinking game: 🥃 Every time you manually type vendor info 🥃 Every time you can't find an invoice 🥃 Every time you process a duplicate 🥃 Every time someone asks, "Did we pay this?" You'd be unconscious by Tuesday. Time to automate. #AutomatedInv

Spent today building a small automation instead of updating spreadsheets manually. Now it: > Monitors public pricing signals > Syncs data to a live dashboard > Slacks me on major market shifts Can't believe I did this manually for months. What are you still doing manually?

A couple of restaurants and shops I talk to in the area. No one is willing to pay more than $1,000. Many of them on platforms, where what they need is a simple configuration. I offer to help them in the end for free, because their network and good-will more valuable at this time. The more advanced companies have people in-house. Even Tier C companies that developers have learned to use AI tools. Where the opportunity is to build new tiers of digital applications geared towards AI. I've been outs selling, it's the reality

You want to see real results with AI in oil and gas? United Production Partners is doing it across their 6,000 wells in Texas. The Problem: UPP's regulatory team faced a monthly grind: pulling data from multiple disconnected systems, manually entering information, and triple-checking every submission before filing with the Texas Railroad Commission. This manual administrative work takes their team's time and attention away from the important work that actually moves the needle for the company. The Solution: Collide has automated this entire process for UPP. A process that used to take hours now takes minutes. 1. It reads the PDF notification from the Texas Railroad Commission and extracts the wells and information from the pdf. 2. With seamless database integration, Collide locates the well files and production data for the wells. 3. It then takes that data and generates the regulatory filing document in seconds. 4. Our quality control flags any exceptions and augments a regulatory expert's ability to identify errors. The Results for United Production Partners: • 1,200+ hours automated annually • 100% regulatory approval rate—zero rejections from Texas RRC • 6,000+ annual filings automated across three districts • 99.4% time reduction—50 days of work saved per year Looking Ahead: UPP has identified the next wave of automation opportunities: H-15 forms (500-600 annual submissions), H-10 injection wells (252 annual data points across 21 wells), production operations workflows, and historical validation projects. I have personally really enjoyed working with UPP and seeing how forward-thinking they are bringing AI to their operations and increasing the throughput from their team. We are quickly moving into a world where E&Ps will be AI native and these guys are the tip of the spear. You can read the press release below 👇