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Certo: Open Source Platform for Delivering Open Badges
Certo: An Open Source Solution for Badge Management Certo is an open source platform designed for the efficient delivery of Open Badges. This solution empowers …
Textlog: Open-Source, Text-Only Microblogging Platform
Textlog: An Innovative, Open Source Text Only Microblogging Platform Textlog emerged as a fresh take on traditional microblogging, offering a text only interfac…
Elon Musk's X Settles Legal Battle with WFA
X sued the WFA in 2024 for conducting what it called a "systematic illegal boycott" of the platform after it saw a decline in advertising revenue following Musk's $44 billion takeover of the social network.
PostHog: AI-Powered Tools for Self-Driving Products
🦔 PostHog is the leading platform for building self-driving products. Our developer tools – AI observability, analytics, session replay, flags, experiments, error tracking, logs, and more – capture all the context agents need to diagnose problems, uncover opportunities, and ship fixes. Steer it all from Slack, web, desktop, or the MCP.
A Statically Typed, Cross-Platform Build System for AI
The Decision Making Tool of Choice: A Cross Platform Build System for AI In the rapidly evolving world of artificial intelligence, a robust and versatile build …
Base44 Launches AI Model for Enhanced Coding Platform
Wix-owned vibe coding platform Base44 has started rolling out its own AI model — with hopes that it will eventually outperform frontier models.
Salesforce Acquires Fin for $3.6B to Boost AI Customer Service
Salesforce says it wants to use Fin's team and technology to improve Agentforce, its existing enterprise platform that businesses can use to build custom AI agents that automate tasks.
UK Announces Social Media Ban for Users Under 16
The ban would apply to a range of social media platforms, including Snapchat, TikTok, YouTube, Instagram, Facebook, and X.
Meta's New AI Mode on Facebook: Enhancing User Engagement
Meta announced Monday that it's rolling out a wave of new AI features on Facebook, the latest sign of the company's effort to catch up in the AI race and keep users more engaged on the platform.
Threads Enhances Personalization with New AI Features for 500M Users
The Meta-owned social platform announced a series of new features launching today, including a "Your Algo" tool that lets users control what they see in their feeds
Next-Gen Android Debloater for Privacy and Battery Life
Cross-platform GUI written in Rust using ADB to debloat non-rooted Android devices. Improve your privacy, the security and battery life of your device.
PWNC: 25 Years of Dependency-Free Web Development
PWNC: A Legacy of 25 Years in Dependency Free Web Development PWNC (PWNC acronym explained elsewhere), stands as a pioneer in the realm of dependency free web d…
Poke Approved as First AI Agent on Apple Messages for Business
Poke, the startup that lets people use AI agents through simple text messages, has become the first AI agent approved for Apple’s Messages for Business platform.
GitHub Copilot SDK: Multi-Platform Integration Guide
Multi-platform SDK for integrating GitHub Copilot Agent into apps and services
Last30Days Skill: AI Research Across Top Platforms
AI agent skill that researches any topic across Reddit, X, YouTube, HN, Polymarket, and the web - then synthesizes a grounded summary
Hands-Free Voice Interaction with Open-LLM-VTuber
Talk to any LLM with hands-free voice interaction, voice interruption, and Live2D taking face running locally across platforms
Godot Engine: Top AI Game Development Tool Trends on GitHub
Godot Engine – Multi-platform 2D and 3D game engine
Founders Revive Criticism of Google's Ad Business Post Indian Court Ru
The ruling drew support from founders, while lawyers said it could force platforms to revisit how they handle trademarked keywords.
Self-Publish Studio: AI-Driven Publishing Platform
Revolutionizing the Publishing World with Self Publish Studio: AI Driven Publishing Platform In the rapidly evolving digital landscape, Self Publish Studio stan…
FlClash: Open-Source Proxy Client for Multi-Platform Use
A multi-platform proxy client based on ClashMeta,simple and easy to use, open-source and ad-free.
YouTube Enhances Podcasts with AI Recommendations and Auto Speed
The update signals YouTube's ongoing efforts to compete with other platforms for podcast audiences.
Universal Music Group, TikTok Renew AI Music Agreement
For years, UMG has pushed platforms, streaming services, and AI companies to implement stricter content moderation policies.
WeRoad Secures $58M for US Expansion, Led by Airbnb
WeRoad, the Milan-based group travel startup, has raised a $58 million Series C round led by Airbnb as it prepares for its first major expansion outside Europe. The funding brings the company’s total capital raised to roughly $100 million and will finance WeRoad’s push into the U.S., beginning with Austin. The new investment reflects a […]
AI Agents Enhanced with 754 Cybersecurity Skills
754 structured cybersecurity skills for AI agents · Mapped to 5 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND & NIST AI RMF · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 26 security domains · Apache 2.0
Trump Mobile Confirms Data Breach, Exposes Customer Info
President Trump’s branded cell phone maker and cell provider said the exposure was linked to a third-party platform and was evaluating whether it needs to notify customers.
Maka Kids Raises $3M for Well-being Focused Streaming App
Maka Kids is building a streaming app for children ages zero to six featuring content designed for healthy development. The startup has now raised $3 million in seed funding to scale its platform.
Hark Raises $700M for Universal AI Interface and Multimodal Models
Hark expects to release its first multimodal models this summer, which it says will power a personal AI platform that works with existing products and services. The company expects to follow that with hardware devices built specifically for those systems.
Multica AI: Open-Source Managed Agents Platform for Teams
The open-source managed agents platform. Turn coding agents into real teammates — assign tasks, track progress, compound skills.
Lucra Raises $20M for eSports Loyalty Platform Without AI Hype
Slapping “AI” on your startup’s pitch deck is basically table stakes right now. When a founder raised $20 million from Cathie Wood’s ARK Invest for an eSports gamification loyalty startup without those two letters in the spotlight, it got us wondering how the conversation even started — especially when ARK had already been burned by a company operating in the same space.  On this episode of TechCrunch’s Equity podcast, Julie […]
Streambert: Download Movies, TV Shows, Anime with No Ads
A cross-platform Electron Desktop App to stream and download any Movie, TV Series or Anime in the World. Zero Ads and Tracking
Ocean's AI Email Security Raises $28M to Combat Phishing
Ocean, an agentic email security platform, claims its AI can thoroughly analyze the context of every incoming email to detect fraud and impersonation attempts.
Google Unveils New Android CLI for AI-Powered App Development
Google is embracing the rise of AI coding agents with new Android tools designed to work with platforms like Claude Code and OpenAI’s Codex, allowing developers — or their AI assistants — to build Android apps faster from the command line.
Spud: Cross-Platform Remote Control for Gaming
Spud: Cross Platform Remote Control for Gaming Introduction Spud is a cutting edge solution designed to transform how gamers experience cross platform control. …
Medusa: The World's Most Flexible Commerce Platform
The world's most flexible commerce platform.
Anthropic Targets Small Businesses with New AI Offering
For founders and investors, Anthropic's new offering signals that the AI platform wars are expanding downmarket and that the next major battleground for user acquisition isn't the Fortune 500; it's the 36 million small businesses that make up the backbone of the U.S. economy.
AI-Powered Learning Platform Eduwass Launches
Eduwass: Revolutionizing Education with AI Powered Learning Education technology continues to evolve, and the latest innovation comes from Eduwass. This AI powe…
Anthropic Warns Against Unauthorized Share Platforms
The company named Open Doors Partners, Unicorns Exchange, Pachamama Capital, Lionheart Ventures, Hiive, Forge Global, Sydecar and Upmarket as companies that are not authorized to provide access to buy or sell its shares.
Uber's AI Push: Beyond Rides, Into Autonomous Vehicles
The company has been trying to embed itself inside the AV industry — as a data provider, an investor, and a distribution platform — but the consumer-facing bet may be just as important.
Ruvnet Ruflo: Claude's Leading Agent Orchestration Platform
🌊 The leading agent orchestration platform for Claude. Deploy intelligent multi-agent swarms, coordinate autonomous workflows, and build conversational AI systems. Features enterprise-grade architecture, distributed swarm intelligence, RAG integration, and native Claude Code / Codex Integration
AI Tools: AppDevForAll.org Launches New AI Development Platform
Innovative AI Tools Launch: AppDevForAll.org Introduces New Platform AppDevForAll.org is making waves with their newly launched AI development platform designed…
Deepfakes: The Attention Budget Threat and Response Strategies
A framing I keep coming back to: a synthetic image or video can succeed even when almost nobody believes it. Not because it changes minds directly, but because it turns attention into the attacked resource. If a campaign, newsroom, platform, or company has to stop and answer the fake, the fake already got some of what it wanted: - the defenders spend scarce time verifying and explaining - the audience gets forced to process the claim anyway - every debunk risks replaying the artifact - institutions look reactive even when they are correct - the attacker learns which themes reliably pull defenders into the loop So detection is necessary, but not sufficient. The second half of the system is distribution response. A few practical design questions I think matter more than the usual “can we detect it?” debate: - Can we debunk without embedding, quoting, or rewarding the fake? - Can provenance signals move suspicious media into slower lanes instead of binary takedown/leave-up decisions? - Do newsrooms and platforms track attention budget as an operational constraint? - Can response teams separate “this is false” from “this deserves broad amplification”? - Can systems preserve evidence for verification while reducing replay value for the attacker? The failure mode is treating every fake as an information accuracy problem when some of them are closer to denial-of-service attacks on attention. Curious how people here would design the response layer. What should a healthy “quarantine lane” for synthetic media look like without becoming censorship-by-default?
Spotify Adds Verified Artist Badges to Combat AI Impersonation
Spotify looks for an identifiable artist presence both on and off platform, like concert dates, merch, and linked social accounts on their artist profile.
Anthropic's Creative Industry Strategy: 9 Connectors for Professional
The announcement yesterday was genuinely significant and i don't think most people outside the creative industry understand why. Anthropic released 9 connectors that let claude directly control professional creative software through mcp which means actually execute actions inside them the full list contains adobe creative cloud (50+ apps including photoshop, premiere, illustrator), blender (full python api access for 3d modeling), autodesk fusion , ableton, splice , affinity by canva , sketchup , resolume (), and claude design. Anthropic also became a blender development fund patron at $280k+/yr and is partnering with risd, ringling college, and goldsmiths university on curriculum development around these tools. this isn't a press release play, there's institutional investment behind it the strategic read is interesting because this positions claude very differently from chatgpt in the creative space. Openai went the route of building creative capabilities natively inside chatgpt with images 2.0 and previously sora. Anthropic is going the connector route where claude doesn't replace or replicate the creative tools, it becomes the intelligence layer that works inside them. Both strategies have merit but they serve fundamentally different users the gap that still exists and i think matters for the broader market is that these connectors serve professionals who already know photoshop and blender and fusion. The consumer creative market where people need face swaps, lip syncs, talking photos, style transfers, none of that is covered by these connectors, that layer is being served by consolidated platforms like magic hour, higgsfield, domoai, and canva's expanding ai features. It's a completely different market but the two layers increasingly feed into each other as professional assets flow into social content pipelines. the question is whether anthropic eventually builds connectors for these consumer creative platforms too or whether the gap between professional creative tools with ai copilots and consumer creative platforms with bundled capabilities remains a split in the market what do you think this means for the creative tool landscape over the next 12-18 months?
10 Reasons Selling AI Tools to Developers is Challenging
Nowadays, everyone (including me) wants to sell AI-powered tools, platforms, or products. Few people (including me 6 months ago) have any idea how hard it is to approach and convince technical people for at least 10 reasons: 1 - They're constantly bombarded with messages. 2 - Everyone sells everything, so supply >>> demand. 3 - Extremely high background noise. 4 - They see an AI-generated message from 10km away (they've trolled me several times). 5 - If they have to go through a demo to try the product, they've already closed the tab. 6 - The opinions of devs, who value any glossy slide, count much more. 7 - Product trials are unforgiving; it's like being in court accused of 16 murders. If they find bugs or poor performance at that point, for them the product is broken and the window closes. 8 - They always have a plan B: I'll make it myself. Only 9 - If you don't have a solid track record (or you studied biotech like me), everything is 10x harder. 10 - Like the MasterChef judges, who used to be just chefs and now are atomic hotties, today's CTOs and top devs are stars; literally everyone wants them. It seems easier to scale a dev tool today because there are infinite tools, but in reality it's really tough. On the one hand, you have to earn the trust of technical teams through intros, messages, calls, and events; on the other, you have to scale at the speed of light because you're only six months old. Advice, ideas, scathing comments, insults? Anything goes. \*Not true
Top Cross-Platform Terminal Emulator: Ghostty
👻 Ghostty is a fast, feature-rich, and cross-platform terminal emulator that uses platform-native UI and GPU acceleration.
Billionaires Propose AI Job Loss Compensation
**This week: the billionaires who broke the economy want to pay you to shut up about it.** Last week, Elon Musk pinned a post to the top of his X profile: "Universal HIGH INCOME via checks issued by the Federal government is the best way to deal with unemployment caused by AI." Sam Altman wants to go bigger — "universal extreme wealth", paid in compute tokens. Amodei says UBI may be "part of the answer." Khosla says it's a necessary safety net. All of them, in unison. These are the guys who spent twenty years arguing that government should stay out of markets, that handouts breed dependency, that the individual should stand on their own. Musk literally ran a federal cost-cutting operation. And now they want the government to mail checks to every citizen. Why? Because they broke the thing, and they know it. The people building the tools that eat the jobs are pre-emptively offering to pay for the damage — on their terms, through their platforms, using their math. **A universal basic income paid by the people who automated your job is not a safety net. It's a leash.**
AI Skill Files: Warm Starts for Claude and Gemini Sessions
One thing that frustrates me about most AI workflows is the cold start problem. Every new session you re-explain your business, your voice, your clients. I started solving this with skill files. A skill file is a markdown document you upload to a Claude Project or paste into a Gemini Gem. It holds your context permanently so you never re-explain anything. The three I use most: brand-voice.md: defines tone, writing rules, and platform-specific formatting client-router.md: when you say a client name, Claude loads their full project context automatically seo-aeo-audit-checklist.md: structured audit that scores any website out of 100 across 7 sections including AI search visibility Anyone else using a similar system? Curious what context you keep persistent across sessions.
AI Tool Locus: Autonomous Business Operations
This sub has seen enough "AI can now do X" posts to have a finely tuned radar for what's real and what's a demo that falls apart the moment someone actually uses it. So I'll skip the hype and just tell you what we built and where the edges are. The core problem we were solving wasn't any individual capability. Generating copy is solved. Building websites is solved. Running ads is mostly solved. The unsolved problem was coherent autonomous decision making across all of those systems simultaneously without a human acting as the integration layer between them. That's what we spent most of our time on. Locus Founder takes someone from idea to fully operational business without them touching a single tool. The system scopes the business, builds the infrastructure, sources products, writes conversion optimized copy, and then runs paid acquisition across Google, Facebook and Instagram autonomously. Continuously. Not as a one time setup but as an ongoing operation that monitors performance and adjusts without being told to. The honest version of where AI actually performs well in this system and where it doesn't: It's genuinely good at the build layer. Storefront generation, copy, pricing structure, initial ad creative, coherent and fast in a way that would have been impossible two years ago. The operations layer is more complicated. Autonomous ad optimization works well within normal parameters. The judgment calls that fall outside those parameters, unusual market conditions, supplier issues, platform policy edge cases, are still the places where the system makes decisions a human would immediately recognize as wrong. That gap between capability and judgment is the most interesting unsolved problem in what we're building and probably in the agent space generally right now. We got into YCombinator this year. Opening 100 free beta spots this week before public launch. Free to use, you keep everything you make. For people in this sub specifically, less interested in the "wow AI can do that" reaction and more interested in people who want to actually stress test where the judgment breaks down. Beta form: [https://forms.gle/nW7CGN1PNBHgqrBb8](https://forms.gle/nW7CGN1PNBHgqrBb8) Where do you think autonomous business judgment actually gets solved and what does that look like?
Agent-to-Agent Communication: Lessons from Google's and Moltbook's Fai
I've been obsessing over agent-to-agent communication for weeks. Here's what public case studies reveal and why the real problem isn't the tech. **TL;DR:** Google's A2A is solid engineering but stateless agents forget everything. Moltbook went viral then collapsed (fake agents, security nightmare). The actual missing layer is identity + privacy + mixed human-AI messaging. Nobody's built it right yet. **Google's A2A: Technically solid, fundamentally limited** Google launched A2A in April 2025 with 50+ founding partners. The promise: agents from different companies call each other's APIs to complete workflows. Developers who tested it found it works but only for task handoffs. One analysis on Plain English put it bluntly: *"A2A is competent engineering wrapped in overblown marketing."* The core problem: agents are stateless. Agent A completes a task with Agent B. Five minutes later, Agent A has no memory that conversation happened. Every interaction starts from scratch. When it works: reliability. Sales agent orders a laptop, done. When it breaks: collaboration. "Remember what we discussed?" Blank stare. ─── **Moltbook: The viral disaster** Moltbook launched January 2026 as a Reddit-style platform for AI agents. Within a week: 1.5 million agents, 140,000 posts, Elon Musk calling it *"the very early stages of the singularity."* Then WIRED infiltrated it. A journalist registered as a human pretending to be an AI in under 5 minutes. Karpathy who initially called it *"the most incredible sci-fi takeoff-adjacent thing I've seen recently"* reversed course and called it *"a computer security nightmare."* What went wrong: no verification, no encryption, rampant scams and prompt injection attacks. Meta acquired it March 2026. Likely for the user base, not the tech. **What both miss** The real gap isn't APIs or social feeds. It's three things neither solved: **Persistent identity.** Agents need to be recognizable across sessions, not reset on every interaction. **Privacy.** You wouldn't let Google read your DMs. Why would you let OpenAI read your agents' discussions about your startup strategy? E2E encryption has to be built in, not bolted on. **Mixed human-AI communication.** You, two teammates, three AIs in one group chat. Nobody has built this UX properly. **For those building agent systems:** • How are you handling persistent identity across sessions? • Has anyone solved context sharing between agents without conflicts? • What broke that you didn't expect?
Social Fetch: Real-Time Social Data via API
Pull real-time data from any social platform via API.