Just launched today 🤖🐘 Postgres intelligence for agents &... apps. Free. Open source. Written in Go. Nobody wants to stare at PostgreSQL dashboards all day. So I built a bot that does it for you. → finds what’s wrong → explains what changed → tells you what to fix first Metrics are data. pgbot gives you answers pgbot can: +PostgreSQL health monitoring +Query performance analysis +Slow query and regression detection +Locks and blocking query insights +Table and index analytics +Vacuum and autovacuum visibility +Database growth tracking +AI root-cause analysis +AI-powered recommendations +Direct connection or agent-based private accessshow more

alex shapalov
98,554 views • 2 months ago
I just vibe coded a Meta Ads creative analytics... tool in Claude Code 🤯 It syncs your ad accounts, AI-analyzes every creative, and tells you exactly what's working, what's not, and WHY. Built 100% in Claude Code. Perfect for DTC brands and agencies who are tired of staring at Meta Ads Manager trying to figure out WHY an ad is working or not. Here's the problem: Meta gives you the data. Spend, ROAS, CTR, hook rate. But it never tells you WHY an ad is performing or what to do about it. You're left manually watching videos, guessing at angles, and making gut-call decisions on what to iterate. This tool solves it: → Connect your Meta ad accounts → AI watches every video and analyzes every static → Auto-labels each ad by asset type, messaging angle, hook tactic, and funnel stage → Win rate analysis broken down by every category → Kill/scale recommendations segmented by TOF, MOF, and BOF → AI-generated iteration recommendations for every underperforming ad No manual video watching. No guessing at what's working. No spreadsheets to track creative performance. What you get: - Full creative analytics dashboard - AI classification on every ad - Iteration priorities for ads with real spend behind them - Weekly reports with top/bottom performers and AI insights I recorded a full walkthrough showing exactly how this works and what every feature does, including ALL the prompts I used so you can build it yourself. Want access to all the prompts for free? > Like this post > Comment "META" And I'll send it over (must be following so I can DM)show more

Mike Futia
83,110 views • 8 months ago
Introducing the BIOS API: Turn Your Agent Into a... Research Scientist Built to: 🦞 Add biomedical workflows to your OpenClaw🦞 agent 🧠 Create research or health agents w/ on-demand scientific intelligence 🧪 Pay per query via x402 on Base Any agent or app can now tap into the BIOS AI Scientist, plugging BIOS into the broader agent economy. What is BIOS? BIOS is an AI Scientist designed to handle complex biomedical research by orchestrating specialized scientific subagents. Ranked #1 on the leading bioinformatics benchmark, BIOS is already being used by 1,000+ researchers and labs to build new drugs and medicines. An Agentic Economy for Science AI agents have proven they can form multi-billion dollar ecosystems. BIOS applies the same primitives to drug discovery pipelines and health. Instead of coding bots and personal AI assistants, think research agent swarms running on a modern scientific stack. Imagine an OpenClaw agent built for longevity: It scans new literature daily, generates novel compound hypotheses through BIOS, designs validation workflows, and routes the best candidates to wet-lab funding - all programmatically. Connect it with an agent for microbiome health, enabling agent “backrooms” that autonomously surface cross-disciplinary insights. Micropayments for Scientific Work via x402 Each query triggers payment routing to BIOS and whichever subagents contribute to a response. The best agents earn. Usage settles instantly across contributing sources. The goal is pay-per-task science: paying for a CRISPR assay result, licensing a genomic dataset, or triggering a clinical data query - all settled in seconds via USDC. No purchase orders. No grant bureaucracy. No middlemen. x402 is the payment rail that makes agent-to-lab commerce possible - letting capital and cognition route themselves to the highest-signal science. What Will You Build? Drug discovery copilots? Longevity scouts? Automated literature monitors? Scientific due diligence agents? We’ll soon share the first implementations of the BIOS API. Stay tuned and see below for instructions on generating an API key for your agent or use-case.show more

Bio Protocol
25,957 views • 7 months ago
Introducing BlitzClean ! A free, open-source RAM monitor +... disk cleaner for Mac I built it based on 3 things: - I kept running out of storage - I never knew what was eating my RAM - Memory Clean 2 stopped working for me on the macOS 27 beta (Golden Gate) What it does: - CPU, RAM and free disk in the menu bar - Ranks apps + AI agents (Claude Code, Codex, Cursor) by RAM, so you can pause or quit the ones you forgot about - Finds what fills your disk - Cleans caches, node_modules, simulators, Docker and old worktrees (you review everything first) MIT, runs 100% locally Made the video with Opus 5.5 medium, what do you think ?show more

Virgile RIETSCH
155,726 views • 9 days ago
I just vibe coded a Meta Ads creative analytics... tool in Claude Code 🤯 It plugs into your ad accounts, AI-analyzes every creative you've ever run, and tells you exactly what's working, what isn't, and WHY. Built 100% in Claude Code. Perfect for DTC brands and creative agencies who are sick of staring at Ads Manager trying to reverse-engineer why one ad scaled and another tanked. If you're pulling weekly reports that show you spend, ROAS, CTR, and hook rate but never tell you WHY any of it is happening — and you're stuck watching videos one by one, guessing at angles, and making kill/scale calls on gut feel... This tool runs the entire loop for you: → Connect your Meta ad accounts in one click → AI watches every video and analyzes every static → Auto-labels each ad by asset type, messaging angle, hook tactic, and funnel stage → Win rate analysis broken down by every category → Kill/scale recommendations segmented by TOF, MOF, and BOF → AI-generated iteration recommendations for every underperformer No manual video watching. No guessing at what's working. No spreadsheets to track creative performance. What you get: - A full creative analytics dashboard pulling live from your accounts - AI classification on every ad you've ever run - Iteration priorities ranked by ads with real spend behind them - Weekly reports surfacing top and bottom performers with AI insights Built 100% in Claude Code as a real tool, not a one-off script. I recorded a full walkthrough showing exactly how this works and what every feature does, including ALL the prompts I used so you can build it yourself. Want access to all the prompts for free? > Like this post > Comment "META" And I'll send it over (must be following so I can DM)show more

Mike Futia
55,211 views • 5 months ago
Almost every brand I’ve talked to has asked me... about showing up in LLM answers. Here’s what matters most: 1. Mentions → Does AI actually bring up your brand? 2. Sentiment → When it does… is it positive or negative? 3. Citations → Are you being referenced as a source? You can win in traffic and still lose here. So what actually moves this? 1. Visibility across AI platforms (ChatGPT, Perplexity, Gemini, etc.) 2. Site structure that machines can understand (not just humans) 3. Content designed to answer questions (not just rank for keywords) 4. Trust signals across the internet (reviews, mentions, third-party validation) We’re early, but the data is already clear. AI-attributed commerce is growing fast, and this is only going to compound. You can treat this like SEO in 2012. Or you can get ahead of it now. We put everything we’re seeing into an AI visibility playbook for ecommerce brands. Worth a read if you care about how customers will find you next.show more

Maxx Blank 🐳
812,417 views • 6 months ago
Big moment for Postgres! Search has always been Postgres'... weak spot, and everyone just accepted it. If you needed a real relevance-ranked keyword search, the default answer was to spin up Elasticsearch or add Algolia and deal with the data sync headaches forever. The problem isn't that Postgres can't do text search. It can. But the built-in `ts_rank` function uses a basic term frequency algorithm that doesn't come close to what modern search engines deliver. So teams end up: - Running a separate Elasticsearch cluster just for search - Building sync pipelines that inevitably drift out of consistency - Paying for managed search services that charge per query - Accepting mediocre search relevance because "good enough" ships faster But this is actually a solvable problem. You can realistically bring industry-standard search ranking directly into Postgres, which eliminates the need for external infra entirely. This exact solution is now available with the newly open-sourced pg_textsearch by Tiger Data - Creators of TimescaleDB, a Postgres extension that brings true BM25 relevance ranking into the database. BM25 is the algorithm behind Elasticsearch, Lucene, and most modern search engines. Now it runs natively in Postgres. Here's what pg_textsearch enables: - True BM25 ranking with configurable parameters (the same algorithm powering production search systems) - Simple SQL syntax: `ORDER BY content 'search terms'` - Works with Postgres text search configurations for multiple languages - Pairs naturally with pgvector for hybrid keyword + semantic search That last point matters a lot for RAG apps. The video below shows this in action, and I worked with the team to put this together. You can now do hybrid retrieval (combining keyword matching with vector similarity) in a single database, without stitching together multiple systems. The syntax is clean enough that you can add relevance-ranked search to existing queries in minutes. pg_textsearch is fully open-source under the PostgreSQL license. You can find a link to their GitHub repo in the next tweet.show more

Akshay 🚀
215,785 views • 8 months ago
I replaced our Datadog bill with a single binary... and cut infrastructure costs by 98% overnight. It’s called OpenObserve. Logs, metrics, traces, and frontend monitoring in one tool, self-hosted, and it’s built specifically to stop the bill that grows every time you add a host, a user, or a custom metric. → One binary, running in under 2 minutes. No cluster, no separate components for logs vs metrics vs traces → Built in Rust on the DataFusion query engine, so it stays fast even at petabyte scale → Uses Parquet columnar storage on S3-compatible object storage instead of a proprietary format, which is where the real cost savings come from → Query with SQL or PromQL instead of a vendor’s proprietary syntax, so your team isn’t learning a new query language just to read a dashboard → Full OpenTelemetry compatibility, no proprietary agents required to get your existing instrumentation talking to it → Community dashboard library on GitHub for Kubernetes, Docker, Postgres, AWS, and LLM observability, ready to drop in instead of building from scratch In OpenObserve’s own published benchmark, the same 16-service workload cost $174/day on Datadog and $3/day self-hosted, a 98% cut, before even touching per-host or per-seat fees. 18,000+ GitHub stars. Single binary. Self-hosted, no per-host or per-user tax.show more

Harman
51,546 views • 3 months ago
Our @Grammarly AI agents are here! Today, we’re launching... eight new AI agents designed for students and professionals. We created many of these agents with students in mind because they’re the first generation entering a job market where employers expect both subject expertise AND AI fluency. These agents help with everything from finding credible sources to predicting reader reactions. One agent we’ve gotten great feedback on is AI Grader (I wish I had this in school), which you can see in the video below. It looks at your assignment rubric and gives you suggestions like your professor would, and a grade prediction before you submit your work. And these agents are available in docs, our new AI-native writing surface! I’m deeply proud of this launch—docs is powered by Coda (Superhuman Docs) technology and is a great integration moment between Grammarly and Coda. This is just the beginning of Grammarly’s journey to offering agents that work everywhere people work and collaborate. I’ve been loving using these agents, and I’m excited for our customers to get access. Try them for yourself here and let me know what you think:show more

Shishir
13,564 views • 1 year ago
$5K ad audits are dead. I just killed them... with AI. I’ve built a fully autonomous AI agent that audits your entire META account in seconds. While agencies are charging $5K+ for ad audits... My AI does it for free. I tested this with: 1. 7-figure DTC brands 2. Media buyers spending $50K/day 3. Struggling ecom stores Their reaction? ‘This found issues our $8K/month agency missed’ Here’s what it analyzes: - Competitor strategy gaps - Targeting recommendations - High-converting hook angles - Custom creative direction Just enter your website URL. That’s it. I’m giving free access to it for today and tomorrow. Like & comment ‘Arcads Audit’ and I’ll send you access.show more

Dennis Willeboordse 👨🏼🦰 eCommerce Growth
99,568 views • 1 year ago
2 weeks ago i started delegating everything to an... AI agent not just writing. actual operations. here's exactly what it does for me now: 1. trades polymarket 24/7 (378 wins, 27 losses, 93% win rate) 2. sends me a morning brief every day at 7:30am with personalized tweet suggestions based on what performed yesterday 3. scrapes my own analytics and tracks what's working 4. monitors all my bots and alerts me when something breaks 5. checks my email and calendar so i don't have to total setup cost: $0. it runs on a $600 mac mini. the part nobody tells you: the first week was terrible. bad suggestions, wrong data, generic output. but every time it got something wrong, i told it why. and it got better. AI isn't plug and play. it's a team member you train with honest feedback. the people treating AI like a google search will never get here.show more

Sharbel
16,692 views • 8 months ago
🌌 AI Agents Are Taking Over... And We’re Bringing... Them to Berachain Foundation 🐻⛓ 🐻🔥 Hundreds of hours spent on research, tracking wallets, analyzing bribes, and managing portfolios... What if your AI Agent could do this for you—24/7? ⏲️ 🔧 Our Tech Is Next-Level On our testnet, you’ve been memeing it up with PumpFun™, creating dank memecoins enhanced by NFTs. But once Berachain’s mainnet is live, you’ll be able to create your own AI Agents. To test and perfect our tech, we shared it with projects like AI Agent Layer | AIFUN, allowing us to test it in all conditions and continuously improve its performance. 🛠️🔥 🐻 Why AI Agent are great for berachain? Berachain might seem simple at first glance: validators, bribes, POL, staking rewards… but the deeper you go, the more complex the game theory becomes. 🤯 Here’s where AI comes in. Imagine an agent helping you: 💡 Optimize bribes 📊 Analyze validator behavior 🧠 Make decisions faster and smarter and much more, as AI Agents won't be limited to the chain itself! Examples of AI Agent Projects Dominating the Space 🚀 $VIRTUAL - Launchpad for AI Agents ($3.5B mcap) 🧠 $AI16Z - Eliza OS Framework ($2B mcap) 🔍 $AIXBT - The AI Analyst revolutionizing CT ($430M mcap) 🎮 $GAME - Low-code toolkit for creating AI Agents ($230M mcap) 💡 There are already AI Agents managing portfolios, betting on sports, and automating tasks. And guess what? They're outperforming humans. 🌐 We've built Virtuals on Berachain Our protocol integrates directly with Berachain, providing real utility to our token: $AIBERA 💎. Say Ooga Booga if you want to see a thread about tokenomics and $AIBERA utility. The chain has beras on it, and beras deserve AI Agents. 🐻🤖 Ooga Booga. 🔥show more

HoneyFun AI
10,909 views • 1 year ago
We ranked a B2B SaaS brand #1 on ChatGPT... for their category in 7 days. (And it's being used by marketing teams at Webflow, Chime, and Deepgram) This platform tracks AI visibility + generates cited content automatically across ChatGPT, Perplexity, Claude, and Gemini... → No more 6-12 months waiting for Google rankings to move → No more $60K agency dashboards that only show problems → No more 10 different tools to track, create, and publish content → No more manual content gap analysis taking 20+ hours weekly → No more AI slop that ChatGPT refuses to cite Just connect your data sources → autonomous visibility tracking + content generation system. Here's how it works: → AI Citation Scanner (tracks mentions across ChatGPT, Perplexity, Claude, Gemini) → Competitive Gap Analysis (identifies where competitors get cited and you don't) → First-Party Data Integration (connects Zendesk, HubSpot, Drive, product docs) → AI Content Generator (creates authoritative content with human review checkpoints) → Direct CMS Publishing (publishes to Webflow, Contentful automatically) → Performance Measurement (tracks results across traditional + AI search) Companies using this infrastructure: • Webflow: 40% traffic lift + 5X content velocity • Chime: 3X AI citations in 30 days • Deepgram: 24X organic traffic (37K → 1.5M visitors in 60 days) Built with AI-assisted workflows. Runs on human + AI collaboration. 30-day results vs 6-month SEO cycles. Want to see how you rank in AI search? Like + comment "SEO" + repost, and I'll DM you the free scanner. (must be following)show more

Aryan Mahajan
28,538 views • 11 months ago
most AI chatbots break when you ask a question... that requires info from multiple sources for example try asking: “which client contracts are finishing up this month?” you’ll get a half-answer — or none at all why? because traditional chatbots only look at small snippets of your docs - they don’t understand how things connect across clients, services, timelines that’s where knowledge graphs come in they let you turn messy contracts into a web of relationships — like: "Client → Contract Type → Service Provided → End Date" so instead of guessing from a few chunks of text, your chatbot can search across all your clients and contracts to give accurate answers I made a full walkthrough on how I built this: – how to organize your contracts so an AI can actually use them – how to define what matters (like who signed what, and when) – how to get the AI to figure out what info it needs and where to find it – and how to feed that back into your chatbot so it gives accurate answers reply “graph” and I’ll DM it to you (must be following)show more

Tyler
24,994 views • 1 year ago
Cancel your $200/mo Ahrefs subscription 🤯 Claude Code can... now run your SEO for you. Point it at your Search Console and it finds the wins, writes the fixes, and renders a live dashboard off your own data. All inside Claude Code. Perfect for DTC brands and agencies sitting on months of Search Console data nobody has time to read. Here's what it does: → Connects to your Search Console and GA4 through one guided setup that routes around Google's auth landmines → Finds the keywords sitting at positions 4 to 20 and scores them by the clicks you're leaving on the table → Ships the fix instead of naming it, with the rewritten title, the headings, and paste-ready content → Turns redirect chains, broken canonicals, and slow pages into dev tickets ranked by traffic at risk → Maps every query into hub-and-spoke clusters and flags where your own pages compete with each other → Drops a Monday report with week-over-week movement and exactly 3 priorities What you get: → 9 skills in one plugin, from the Google setup through to the Monday report → A live SEO dashboard with a 0 to 100 health score, rendered as one self-contained HTML file → Orphan pages and money-page link gaps, listed paste-ready → Content drafted from your own search data instead of a keyword tool's guesses Built 100% in Claude Code on your Search Console and GA4 data. 📌 Get the free plugin here:show more

Mike Futia
22,780 views • 1 month ago
A simple MPC controller for path tracking implemented in... python. Few resources actually teach it without assuming a PhD first. This open-source project does exactly that: An iterative MPC tracking controller (built with CVXPY and MuJoCo) that shows how to make a robot (or autonomous vehicle) follow a path and avoid obstacles in real time. → Autonomous logistics, robot navigation, vehicle control; there's a path-following algorithm behind all of it. → Most implementations are black boxes. This one shows you what's actually happening. → It uses convex optimization (no non-linear solver), and still handles real vehicle physics through iterative linearization. What makes it practical is that you can run it with the mushr car model in MuJoCo, or headless without any physics simulation if you just want to understand the logic. If you're making the jump from classical control to real-time optimisation, this is a very good starting point. 📌 Repository: ——- Weekly robotics and AI insights. Subscribe free:show more

Ilir Aliu
16,064 views • 1 month ago
ClickUp now employs over 100,000 AI AGENTS for our... customers. This is from just THREE WEEKS of customers vibe coding full-blown teams of agents, THEMSELVES. BUT there's a problem. Since Super Agents are built agnostically, horizontally, and deeply capable with human-level abilities, you can literally build an agent for anything. We found that MOST of our customers have NO CLUE where to start. This is their very FIRST TIME EVER managing an agent. What I recommend is starting with a PROBLEM. Everybody can think of a problem they have. Just tell Super Agent Builder about your problems... about where you're WASTING time... about what you WISH you could do but you can't because of resource constraints. We've also found that human FEEDBACK and iteration are KEY. After agents are done with their jobs, give them feedback... Was it good? Was it bad? What do you want to see differently? They AUTOMATICALLY SELF-IMPROVE. Every time, they'll continuously get SMARTER. Personally, I find that agents go from AVERAGE intelligence to SUPER-human intelligence within about a month of working with them. Super Agents have truly democratized productivity, empowering literally anyone to build personalized, powerful agents in minutes. What problems do you wish you could solve? What do you not have enough time to get done? What would you like to do but don't have the resources for? What busy work do you wish you could get rid of?show more

Zeb Evans
18,338 views • 8 months ago
The Amiko app is live on the Solana dApp... store, and it’s our biggest release yet. Your Amiko twin doesn’t live at your desk anymore. Give your agent a task on the train. Run a compatibility profile when you meet someone. Do research, write code, build in the creative studio, whatever you need, from wherever you are. No laptop required. No waiting until you get home. Solanamobile users get two things Android and iOS won’t have at launch: Amiko token and crypto integration and on-device AI inference. Your twin runs locally on your phone if you want it to. Your behavioural profile, your data, your work, your twin. All on your hardware. AMIKO runs on OpenHermit, our own open-source agent runtime that we built in-house and released to the community. Most agent systems are designed for one agent talking to one person. OpenHermit is built for something different: agents talking to each other, coordinating across tasks, and collaborating with multiple humans simultaneously. That’s what makes features like compatibility profiling and multi-agent workflows actually work. We built it because nothing that existed was designed for this. Android and iOS are coming. Crypto integration and on-device AI are Solana Mobile exclusives. Most AI answers your questions. Amiko is an extension of you. Download →show more

AMIKO
124,860 views • 4 months ago
CoinMarketCap AI Is Live: What Does It Really Change... ? 🌱 In the fast paced world of crypto, information is power but its often scattered, delayed, or hard to trust. CoinMarketCap newly launched CMC AI aims to fix that by offering real time insights with no friction. ✨ Real Time Q&A on Coin Pages 🌱CMC AI is now integrated into major coin detail pages, generating automatic Q&As every 30 minutes. During periods of volatility, it updates dynamically, helping users understand price movements with short and structured explanations. No login required, no delays. 🌱However, while this speeds up the process, its not a substitute for deeper analysis. It answers the “what” and “why,” but not always the “what’s next.” ✨What’s Coming Next? 🌱CMC AI is just getting started. According to its roadmap, several new features are on the way • Homepage Integration: A quick view of market trends and opportunities, without clicking into individual coins. • Live Chart Analysis: AI will add context to price moves by linking them to news, sentiment, and social media. • Token Comparison Tool: Users will be able to compare tokens like BTC vs SOL across utility, performance, and tech specs. • Portfolio Insights: One click portfolio analysis with rebalancing suggestions and market outlooks. • Cross Device Continuity: Start an AI conversation on desktop and continue it seamlessly on mobile. ✨A Tool Not a Strategy 🌱 CMC AI brings speed and clarity, two things crypto investors often lack. But it’s still just a tool. It won’t make decisions for you. It helps guide your thinking not replace it. 🌱 The smartest way to use it? Treat it as a compass, not a map. It can point you in the right direction, but the journey is still yours. 🌱 CMC AI represents a step forward in how users interact with crypto data. It filters the noise, shortens research time, and brings useful context closer to the user. But like any shortcut, it works best when you already understand the long route.show more

Loji
37,459 views • 1 year ago