Harry Tandy

What’s actually changing with @ssv_network Here’s the simple version👇

Good Stake -> Productive Agent many believe that an AI agent is just a well-written prompt beyond that, it is very important to select the proper agent pieces: > LLM > Tools > Memory > Triggers > Feedback loop not a single point - the agent is just an empty talker 1. LLM: the reasoning engine this part defines objectives, course of action, and design of execution. but LLM itself doesn't auto-access your systems, retain stable context, or act in the real world that is why “just using GPT” is not the same as building an agent 2. Tools: the execution layer it's hands for agent, this layer converts thought into action your agent can check data, send messages, etc using tools but without tools, ai agent is just text generation system 3. Memory: the context layer it's what makes your agent consistent over time this could be user preferences, schemes and styles of text outputs, etc but remember: do not use your memory as a piece of paper with notes this strategy is only going to get you a performance hit and make your outputs confusing 4. Triggers: the decision to wake up a good agent does not need to be always running it should cause itself to awaken by happening this strategy works much better than polling system 5. Feedback loop: the process of improvement a productive agent is not just reacting – it improves over time i.e. its outputs are checked, errors are highlighted and corrected into prompts, tools, memory, or evals

@Blum_OG good prompt is just the entry point the agent starts to work when the loop is there

🚨 Cursor just dropped Composer 2, it changes vibe coding Now it plans, builds, and ships across hundreds of steps, on its own What's actually possible now: - Describe a feature in plain English: get working code across multiple files - Hand it a broken codebase: it reads the whole project and proposes fixes - Run a full API integration or migration: Composer plans the steps and executes them autonomously - Refactor legacy code: it holds context across the entire repo - Prototype an idea from scratch: architecture, logic, boilerplate - done - Hit a bug at 2am: it doesn't just find it, it traces the root cause and fixes it end-to-end The benchmark jump is real: +39% over Composer 1.5 The price is even better: $0.50/M input. $2.50/M output That's frontier-level intelligence at a fraction of what GPT-4 or Claude cost It's building its own model and it's coming for the whole stack👇

@alphabatcher the shift is not one-shot code anymore it can stay with the task long enough to matter

@alphabatcher businesses don't need lots of humans now

5 ways you can use AI to solve key business needs (automation guide) ​ I talked to dozens of small business owners over the past year ​ Most of them were losing 15-20 hours a week to tasks that could run on autopilot ​ Not because of bad strategy. because of repetitive tasks no one ever automated ​ Here are 5 real business problems AI solves right now 👇 ​ 1. Losing leads because you respond too slow ​ the average business responds to a new inquiry in 2-3 hours ​ but studies show that if you don't respond within 5 minutes, your chances of closing drop by 80% ​ the fix: ​ - AI responds to every new inquiry instantly, 24/7 - qualifies the lead with 2-3 questions - books a call or sends an offer automatically - logs everything into your CRM without anyone touching it ​ tools: Manychat, Tidio, n8n + your CRM of choice ​ 2. Team wastes hours answering the same questions ​ the average support agent spends 4-5 hours a day answering questions that never change ​ that's more than half the workday gone on copy-paste replies ​ "what's the price", "how does it work", "what's the timeline", "do you have X" ​ the fix: ​ - AI handles all repetitive questions instantly - complex or sensitive cases get escalated to a human with full context already attached - customer gets an answer in seconds, not hours - team focuses only on conversations that actually need them ​ tools: Intercom, Tidio, custom GPT connected to your docs ​ 3. Data lives in five different places and nobody looks at it ​ most small businesses collect data, but almost nobody actually uses it ​ decisions get made on gut feeling because the numbers are never ready in time ​ because pulling it together takes so long that by the time the report is ready, it's already outdated the fix: ​ - connect all your tools once (CRM, ads, sales, ops) - AI pulls the data automatically on a schedule - you get a clean summary delivered to your Slack or email every Monday morning - no spreadsheets, no manual work, no outdated numbers ​ tools: n8n or Make + Airtable + your data sources ​ 4. Onboarding is inconsistent and nobody notices until it's too late ​ the first 7 days after someone buys or joins your team are the most important ​ but in most companies, no one actually checks whether the person received everything they needed ​ the fix: ​ - new client or employee triggers an automatic sequence - day 1: welcome + what to expect - day 3: useful resource or check-in - day 7: quick feedback question - all of it runs without anyone managing it ​ tools: n8n or Make + ActiveCampaign or MailerLite + Notion or Google Docs (for resource delivery) ​ 5. Content either doesn't happen or happens in chaos ​ businesses that post consistently get 3x more inbound leads than those that don't ​ but most small businesses either don't post at all or post randomly when someone finds 20 minutes between meetings the fix: ​ - you prepare content once a week - AI generates post variations for each platform - you pick one, make small edits, approve - everything goes out on schedule automatically tools: Make or n8n + Claude or ChatGPT + Buffer or Publer ​ CONCLUSION: ​ Most small businesses already have the problems listed above ​ They just don't know they can be solved without hiring more people ​ Pick one problem from this list. Build one solution. Deliver one result ​ That's how you start. That's also how you scale ​ The demand is real. The tools are accessible. The businesses that move first will have a serious edge over everyone still doing it manually

@Blum_OG food to think solid point and I', completely agree with you

WHY REVENUE > HYPE? market is oversaturated with tokens lacking full semantic backing what are they based on? nobody knows, everyone just believes and yet there are a couple of worthy representatives namely revenue-driven tokens - isn't this stability in modern market? so, why do I think hype < revenue: hype is +1000% in a day, but -99.9% in a month and let's be honest, entering at the right moment is almost impossible. while revenue-backed tokens are +60% per month take $HYPE as an example сonfident growth $26 → $41 (+58%) over the last couple of weeks and this doesn't happen by chance, there's proper mechanics behind it: platform fees → buyback tokens → burn/distribute to holders and I found an even more stable model - @1winToken key sustainability criteria: > supply cap: 10B (hard-coded) ​ > revenue linkage: daily burn & regular buyback > utility: play-based usage, cashback, network compatibility + potentially powerful narrative (analyzed in the post below) NFA, DYOR!

@AngryTomtweets @invideoOfficial the one click magic we all needed.

92% of social videos are watched on mute. That’s why @invideoOfficial dropped Dynamic Captions. AI-powered, word-by-word animated captions with multiple styles. Custom fonts, custom colors and one click to apply. Here's how it works:

@VadimStrizheus OpenClaw is the multiplier we’ve been waiting for

AI is the greatest invention on Earth. The use cases for OpenClaw are unlimited!! 👇

@hasantoxr managing multiple agents at once is a lot of work

🚨 This might be the most complete Claude Code setup on GitHub right now. Built by an Anthropic hackathon winner. Now it's free for everyone. The repo comes with: → AI helpers that do the work for you → Skills you can use again and again → Tools that run on their own → Simple commands for hard tasks → Ready-made rules and connections And they just added: → A way to manage multiple programs at once → Many AI helpers working together → 6 new commands Most people build this stuff one piece at a time. With this repo, you get it all on day one. One download. Everything included. (Link in the comments)

@dylan522p @cHHillee good luck to everyone applying!

Our hackathon on Sunday is gonna be HUGE We have many participants from every major AI lab, and sonmany sick speakers like @cHHillee Power to Prefill, Dirt to Decode, A Full-Stack AI Infrastructure Hackathon Limited spots, apply now luma.com/SAxFSHack

@hasantoxr privacy is no longer a feature, it's a requirement

Typeless is now officially HIPAA and GDPR compliant, and that is a bigger deal than it sounds. Most AI tools can't say that. HIPAA protects your health data in the US. GDPR protects everything in the EU. Passing both means your data is locked down under the toughest rules on the planet. → No cloud storage. Your inputs never leave your device → Your data never trains the AI. What you type stays yours → Your history lives on your machine. Not theirs Not just for doctors and hospitals either. Lawyers. Executives. HR teams. Anyone who types things they can't afford to leak. And they're already going further SOC 2 Type II and ISO 27001 are in the works. Most AI tools bolt on privacy at the end. Typeless built it in from day one. Check their Trust Center: trust.typeless.com Or download and try it yourself: typeless.com

@Markmanson vibe-coding on Sunday, debugging on Tuesday, crying on Wednesday the cycle is real

FOMA (noun) — Fear of Missing AI /ˈfōmə/ FOMA is a persistent fear that you are "falling behind" on AI and every minute you're not prompting, building agents, or vibe-coding brings you closer to inevitable replacement in the post-AGI economy. FOMA is exacerbated by listening to VC podcasts, reading clickbait articles about Open Claw, and refreshing your X feed like it's your ex-girlfriend's Instagram. Remedies to FOMA include: touching grass, talking to humans who don't know what an MCP is, actually trying to use Open Claw and realizing it's a total piece of shit, and watching as your vibe-coded masterpiece breaks eighteen different ways by Tuesday.

@jerrod_lew setup once, scale forever Alex’s tutorial is a must-watch

Been trying Claude Cowork recently, and Alex's video was a huge help to get started. Taking time to setup my ongoing projects, giving some history of myself and what I need has been really helpful in the recent days. Highly recommend if you're new to Claude like me:

@rezkhere crazy how fast "impossible" became "seconds"

We are finally at a stage where you don't need to learn any editing software. You just type in what you want. And Pexo on OpenClaw - understands it and asks clarifying questions - selects the best video models for the job - gives you a well-edited video in seconds. This was unheard of even a few months ago. 2026 is gonna be wild for AI videos...

@_heyrico @huge_icons simple, effective, no fluff love it

Design cheatsheet (bookmark this): - Typography: Only 2 font weights. Regular for body text, medium for headings and emphasis - Colors: TailwindCSS neutral palette. Visit tailwindcss(.)com/docs/colors to explore - Radius: Stick to 8-12px. No more, no less - Icons: @huge_icons solid icons I want to write it down in an article. Let me know if this is something that interests you, zero gatekeeping.

@rezkhere discord as an OS for video creation is the real meta

We are so cooked 💀 You tell your OpenClaw to make a video in a normal Discord message. It asks you a couple of questions and sends back a finished video with transitions and music within a few minutes. This is Pexo, the new OpenClaw video skill 👇

@VadimStrizheus game changer opus reasoning and sonnet speed - perfection

HOW AM I JUST FINDING OUT ABOUT THIS?! You can use /model opusplan Claude Code uses Opus for planning and Sonnet for execution. This is effiencymaxxing👇

@VadimStrizheus vibe-coding just reached its final form subagents are a massive win for productivity

Codex now has subagents!! > accelerate your workflow > Maintain a clean content window > Run multiple parallel tasks vibe-coding just got better.

@allen_lattimer @omneky dynamics always wins the race

Static campaigns lead to inefficient spend. Markets evolve, audiences shift, and creative effectiveness declines over time. @Omneky addresses this by continuously optimizing every element of your campaign using real-time performance data. Why it works: – Decisions are driven by data, not assumptions – Iteration is ongoing and systematic – Scaling remains controlled and efficient Adapt faster. Perform better. Try now : omneky.com