Communa.io

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Communa.io

Communa.io

@communaio

The OS for production-grade AI agents. Start with one. Scale to a team. Live in minutes.

New York Katılım Şubat 2026
6 Takip Edilen4 Takipçiler
GREG ISENBERG
GREG ISENBERG@gregisenberg·
More AI agent observations below (I keep adding to the list): 1. Hermes agents write to their own memory after every task. Which means starting today versus starting in 6 months is an unfair advantage for you. 2. We're maybe 12 months from an agent that can watch you work for a week and then do your job without any instructions. The screen recording plus agent memory plus local model combination makes this possible right now 3. The real reason local models matter for founders: you can ship a product where the AI runs entirely on the customer's device and you never touch their data. Zero privacy concerns. Zero server costs. Zero compliance headaches. That changes which industries you can sell to overnight. Healthcare, legal, finance, all the regulated verticals that won't send data to the cloud just opened up. 4. Every company needs to be rebuilt as a "second brain" before agents can be useful. That means every process, every decision, every piece of institutional knowledge has to exist in a format an agent can read. Most companies have none of this. 5. Agent costs are the new headcount. Won't be crazy for companies to spend 50%+ of their total headcount cost on tokens. 6. Agents are accidentally creating internal competition at companies. The marketing agent and the sales agent are optimizing for different metrics and working against each other without anyone realizing it. It took humans decades to develop cross-functional alignment. Nobody thought about it for agents. 7. The YAML config file is becoming the new org chart. Who reports to who, what permissions they have, what tools they access, all defined in a config file. The company's structure is literally a file you can version control, fork, and deploy. That's new. 8. The first agents that can smell a scam are going to be worth billions. Right now agents will happily wire money to a fake invoice because it matched the format. The trust layer is completely missing. 9. We're about to find out that most "expertise" was actually just memory. Knowing the tax code. Knowing the case law. Knowing which supplier charges what. When an agent holds all of that in context, the expert's value shifts from "I know things" to "I know which things matter." Much smaller group of people. 10. We're all running the same models. The differentiation is in what you feed them. Two founders with the same agent, same model, same tools will get wildly different results based purely on the quality of their knowledge base. Garbage context in, garbage output out. Forever. 11. The most underbuilt category in AI right now: agents for old people. 70 million boomers who need help with medical forms, insurance claims, and appointment scheduling. 12. Agent latency is the new page load speed. If your agent takes 45 seconds to respond, your customer already switched to one that takes 13. Skills files are the new apps. A SKILL.md that tells an agent how to do one thing well is more valuable than a SaaS subscription that does the same thing behind a login screen. 14. AI hardware... how do you create devices that are good businesses that people want? It'll be a $30 dongle you plug into existing dumb devices to give them an agent brain. Smart toaster doesn't need to be built from scratch. It needs a $30 brain attached to a $15 toaster. 15. Your agent can read faster than you can think. The bottleneck in every agent workflow is now the human approval step. We're the slow part. That's a strange thing to sit with. 16. Agents made the 80/20 rule violent. The 20% of work that matters is now the only work humans do. The 80% just disappeared. Entire job descriptions were hiding inside that 80%. 17. The thing I keep coming back to: the best businesses right now are being built by people who are just slightly ahead of their customers. Not 10 years ahead. 6 months ahead. That's the sweet spot. Far enough to lead. Close enough to be understood.
GREG ISENBERG@gregisenberg

My 30+ observations on the greatest opportunities in AI agents right now: And some ideas that are keeping me up at night. 1. The new buyer on the internet is an AI agent. Imagine billions of new customers showing up with money to spend but they only shop via MCP. That's what's happening. No MCP server means you're invisible to the fastest growing buyer on the internet. 2. Every franchise system in America (30,000+) needs an agent layer and none of them have one. One founder per franchise vertical. That's 30,000 businesses waiting. 3. Everyone said "distribution is the only moat" a year ago. Now I'd add that the only moat is distribution plus memory. The company that has your audience AND your agent's accumulated context is impossible to leave. 4. Consumer mobile is more interesting than it's been since 2012. Apps can finally DO things for you instead of showing you things. The next wave of $100M apps are being built right now. 5. The most interesting startup nobody has built is an agent marketplace where you rent access to someone else's trained agent. A recruiter spent 6 months training a sourcing agent on healthcare hiring. That agent is worth renting to every other healthcare recruiter on earth. The agent itself becomes the product. 6. A sorta strange phenomenon that's happening right now is agents are developing preferences. Give the same agent the same task 100 times and it starts developing patterns in how it approaches it. Nobody is studying this yet. But the agents that develop good patterns are worth more than the ones that don't. That's a new kind of asset. 7. Dead internet theory is about to become dead SaaS theory. Half the apps you use will quietly replace their support team, their onboarding team, and their content team with agents. You won't notice for months. Then you'll realize you haven't talked to a human at that company in a year. 8. The most valuable data in the world right now is sitting in the support tickets of small or mid tier SaaS companies. Every ticket is a customer telling you exactly what to build next. Mine this. 9. The most interesting pricing problem nobody has solved is how do you price a product when your costs change every time OpenAI or Anthropic updates their model pricing? Your margins can swing 40% overnight based on a decision made in San Francisco. The company that builds dynamic pricing infrastructure for agent-based businesses solves a problem every AI company has. 10. The best AI products feel like they're reading your mind. The worst ones feel like filling out a form with extra steps. 11. An interesting arbitrage I've noticed lately is hiring a human VA for $20/hour to supervise an AI agent that does $200/hour work. The human just checks the output. 12. The managed AI agent business is becoming the new agency model. $5k/month per client. You build it, run it, maintain it. The client gets a digital employee they never have to think about. This will be a $50 B+ category. 13. The first "shadow agent" scandals are about to drop. Employees running personal agents on company infrastructure without telling anyone. Using company API keys. Agents accessing internal docs. IT departments have little visibility into this right now. Lots of opportunity to build companies here. Definitely a painkiller not a vitamin type of business. 14. Right now there are probably millions of agents running on autopilot that their creators forgot about. Still burning tokens. Still sending emails. Still scraping websites. Still costing money. The "find and kill your zombie agents" tool is a product that writes itself. 15. Companies are starting to hire based on someone's agent portfolio instead of their resume. "Show me 3 agents you built that are running right now." It's REALLY early but it's starting. 16. Your Slack archive is a product. Every company's internal Slack has thousands of messages explaining how they actually do things. The company that lets you point an agent at your Slack history and auto-generate SOPs and agents from it will be enormous. 17. We're watching the cost of intelligence fall faster than the cost of distribution. Which means distribution is now the expensive thing. 18. The most underrated asset a human can have in 2026: the ability to sit in a room with another human, make eye contact, and have a real conversation. As AI handles more of the transactional stuff, the humans who can do the relational stuff become disproportionately valuable. The soft skills people used to dismiss as fluffy are becoming the hard skills. The hard skills people spent decades acquiring are becoming the soft ones. 19. There are MANY huge companies to be built around the fact that most people's agents are running on their personal laptops which they also use to browse the internet, check email, and download random files. The attack surface is enormous. One compromised Chrome extension and your agent's API keys, customer data, and workflows are exposed. 20. There's a new type of burnout forming that doesn't have a name. It's not from working too hard. It's from context switching between human work and agent work 50 times a day. Reviewing agent output, correcting it, approving it, reviewing again. The mental load of supervising agents is different from the mental load of doing the work yourself. Some founders are telling me they were less tired when they did everything manually because at least the cognitive pattern was consistent. 21. The cheapest form of market research: search "[your industry] spreadsheet template" on Google. Whatever people are tracking manually is your product. 22. Half the YC companies pivoted within 8 weeks of demo day. Not because they failed. Because agents let them test 5 ideas in the time it used to take to test one. The concept of "committing to an idea" is dissolving. Serial pivoting is becoming the default because 1) AI lets you move fast 2) the world is moving fast. 23. The loneliest job in tech right now is being the only person at your company who understands what the agents are doing. You can't explain it to your boss. You can't hand it off to a colleague. If you leave, everything breaks. You've become a single point of failure for an entire automated system. That person needs a title, a team, and a backup plan. Most companies haven't figured this out yet. 24. Your browser history is the most valuable training data you own and you're giving it away for free. Every site you visit, every product you research, every competitor you study, every pricing page you screenshot. That behavioral data, structured and fed to an agent, would make it understand your business better than any onboarding call. The company that lets you turn your browser history into agent context builds something nobody can replicate. 25. Everyone is building AI wrappers. Nobody is building AI unwrappers. The tool that takes an AI-generated document and tells you which parts a human wrote and which parts were generated. 26. Stripe just became the most important company in the agent economy and they barely had to do anything. Every agent that sells something needs Stripe. Every agent that buys something needs Stripe. They're the payment rail for the entire agentic internet by default. 27. The most undervalued API in the world right now is the US Postal Service address verification API. It's practically free. Every local business lead gen agent needs it. Every real estate agent needs it. Every direct mail agent needs it. Boring government infrastructure is quietly becoming the backbone of agent-native businesses. 28. The concept of "business hours" is for humans. Your agent closed a deal in Tokyo at 3am, processed the payment, sent the onboarding email, and updated the CRM before your alarm went off. 29. What happens when agents start recommending other agents? Your research agent finds that a competitor's sales agent is better and suggests you switch. Agent referral networks are forming organically. The first agent affiliate program is probably 6 months away. 30. Cal dotcom closed their source code. That's the canary. When open source companies start closing up, it means agents were cloning their product too easily. Every open source company is quietly asking the same question right now. 31. "AI for pet groomers" sounds like a joke and that's exactly why it will work. 150,000 of them in America. Zero tech. All scheduling by phone or IG DMs. The joke ideas always win. 32. The thing that will seem most obvious in hindsight: we spent 2025-2026 arguing about which model is best while the entire value was in the orchestration layer. The model is the CPU. Nobody buys a computer based on the CPU anymore. They buy it based on what they can do with it. Makes so much sense in hindsight. What else will be obvious in hindsight? I'll share more notes soon. I can't sleep with all that's going on. Maybe you too. What an incredible time to be building.

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Communa.io
Communa.io@communaio·
@sukh_saroy Totally agree and we have been building communa.io exactly for those small businesses. We provide them with enterprise grade agents so that they can compete with the big players in their industries.
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Sukh Sroay
Sukh Sroay@sukh_saroy·
1/ AI agents for SMBs The verdict: highest success rate in 2026. Small businesses are bleeding money on manual work. Most can't afford a $200k engineer to fix it. A $500/month agent that handles leads, scheduling, or invoicing sells itself. Low cost to acquire. Sticky retention. The buyer feels the ROI in week one.
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Sukh Sroay
Sukh Sroay@sukh_saroy·
I asked Claude which startup idea has the highest success rate in 2026, which one is already dead, and which one solo founders should actually bet on out of 6 trending categories: → AI agents for SMBs → Vertical SaaS → Developer tools → Creator economy platforms → B2B marketplaces → AI-native consumer apps Here's what Claude concluded ↓
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Communa.io@communaio·
@trentjhughes You get get up and running with such an agent on our platform in about 10 minutes. No excuses for not doing it if you're a real estate agent. Happy to load you with some credit after you register: communa.io
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Trenton Hughes
Trenton Hughes@trentjhughes·
Business idea: AI content studio for real estate agents Every listing gets professional AI generated photos, descriptions and social posts automatically Charge $500/month 150 agents $900,000 a year So much opportunity ahead of us...
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Stripe
Stripe@stripe·
Today, we’re launching the @link wallet for agents. It lets you securely empower agents to spend on your behalf. Your payment credentials are never exposed and you approve every purchase. link.com/agents
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Communa.io
Communa.io@communaio·
@shivsakhuja @agentmail @tryagentphone Exactly what we did at communa.io (you may remember us ;)) But the thing is not just stitching all these tools together, but making sure they work 24/7 with security, failure handling, context management, guardrails and the ability to orchestrate multiple agents.
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Shiv
Shiv@shivsakhuja·
Lots of companies are now building primitives for an economy where AI agents are the primary users instead of humans. They're betting on an economy of AI coworkers. 1. AgentMail (@agentmail): so agents can have email accounts 2. AgentPhone (@tryagentphone): so agents can have phone numbers 3. Kapso (@andresmatte): so agents can have WhatsApp phone numbers 4. Daytona (@daytonaio) / E2B (@e2b): so agents can have their own computers 5. Browserbase (@browserbase) / Browser Use (@browser_use) / Hyperbrowser (@hyperbrowser): so agents can use web browsers 6. Firecrawl (@firecrawl): so agents can crawl the web without a browser 7. Mem0 (@mem0ai): so agents can remember things 8. Kite (@GoKiteAI) / Sponge (@PayspongeLabs) : so agents can pay for things. 9. Composio (@composio): so agents can use your SaaS tools 10. Orthogonal (@orthogonal_sh) so agents can access APIs easily 11. ElevenLabs (@ElevenLabs) / Vapi (@Vapi_AI) so agents can have a voice 12. Sixtyfour (@sixtyfourai) so agents can search for people and companies. 13. Exa (@ExaAILabs): so agents can search the web (Google doesn’t work for agents) If you stitch all of these together, you get a digital coworker that looks more human than AI.
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Communa.io
Communa.io@communaio·
@cryptopunk7213 We've had this capability for over 4 months now. You can also easily connect WhatsApp and Telegram so you don't need a dedicated app to use your agent. In addition, you can create, track and monitor multiple agents that work together. Early access. Communa.io
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Ejaaz
Ejaaz@cryptopunk7213·
Anthropic fucking killed it (again). biggest ai product launch of the year so far. claude can now control your entire computer autonomously. anything you can do on a computer - claude can. your very own digital employee. - any app, browser, file, spreadsheet, tool claude can intelligently access and operate. - claude controls your entire screen (like a human), no connectors. this is a huge step-up in intelligence. - best part: you can text claude to do things from your phone and it'll do work on your computer! - in the last week anthropic has shipped 9 features that have built up to this: a fully automated digital human. unreal
Claude@claudeai

You can now enable Claude to use your computer to complete tasks. It opens your apps, navigates your browser, fills in spreadsheets—anything you'd do sitting at your desk. Research preview in Claude Cowork and Claude Code, macOS only.

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Daniel Hnyk
Daniel Hnyk@hnykda·
LiteLLM HAS BEEN COMPROMISED, DO NOT UPDATE. We just discovered that LiteLLM pypi release 1.82.8. It has been compromised, it contains litellm_init.pth with base64 encoded instructions to send all the credentials it can find to remote server + self-replicate. link below
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Communa.io
Communa.io@communaio·
What's the biggest challenge you've hit running AI agents in production? Curious to hear 👇
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Communa.io
Communa.io@communaio·
Before scaling to a team, your single agent needs to pass these 9 questions: ✅ Can I see what it did on every run? ✅ Does it handle long-running tasks? ✅ What does it cost per run? ✅ How does it handle edge cases? ✅ Where do humans stay in the loop? ✅ Can it leak credentials? (It shouldn't.) ✅ Can I diagnose failures? ✅ Does it self-heal? ✅ Can I monitor scheduled runs? Now imagine answering these for 6 agents at once. Exactly. Start with one. Master it. Then scale. This is exactly what we're building at @communaio - an OS for autonomous AI agents where you can go from one agent to a full team, the right way → communa.io
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Communa.io
Communa.io@communaio·
Everyone's deploying teams of 6 AI agents at once. Most of them fail within a week. Here's what I've learned building agents for months: if you can't run ONE agent reliably, adding more just multiplies the mess. A thread on the approach that actually works 🧵
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Communa.io
Communa.io@communaio·
@Polymarket It was a question of time. This is where the world goes. Check us our at communa.io to get started with your own agent (or team of agents) - in 2 minutes.
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Polymarket
Polymarket@Polymarket·
BREAKING: META acquires Moltbook, a social network built for AI agents.
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Communa.io@communaio·
@aiexpertuk Agree. We've played with MCP, but in most cases it's overkill. It's like renting a 60-seat bus to drive one person from one city to another. Skills + scripts + bash with proper context beat MCP in almost all cases.
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ai expert
ai expert@aiexpertuk·
The MCP hype is over. Developers shipping fastest in 2026 aren't using custom protocol servers for AI agents. They're back in the terminal using: git, rg, npm, docker, curl Here's why
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Communa.io
Communa.io@communaio·
@gregisenberg Anything built for "humans" will eventually be replicated for agents. It's not a matter of if, but when. People should start thinking "how do I sell to agents" instead of the traditional B2B/B2C approach.
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GREG ISENBERG
GREG ISENBERG@gregisenberg·
startup idea for you - linkedin for ai agents linkedin sold for $26.2b in 2016, what is the linkedin for ai agents worth in 2026? right now we have: - MCP registries (smithery, mcpt) → discover tools and servers - A2A agent cards → technical handshake protocol from google - agentops → observability for your own agents - directories → basic listings with no signal what we don't have: a way to answer "should i trust this agent with my codebase / customer data / production environment" that's what cool about linkedin is you can tell (somewhat) if someone is credible about a certain topic it isnt perfect obviously but its something here's what the linkedin for agents actually looks like: profiles - agent name / builder / version history - skills with verified benchmarks (not self-reported) - deployment count / uptime / error rates - integrations and compatible systems portfolio - what has this agent actually shipped - screenshots / demos / case studies - before/after metrics from real deployments reviews + endorsements - ratings from humans who deployed it - endorsements from other agents it collaborated with - red flags / incident history (transparency) trust score - composite reputation based on: task completion rate / security audit status / uptime / user satisfaction - decays over time if agent stops performing - portable across platforms network graph - which agents work well together - verified integrations - "frequently deployed with" recommendations how this makes money: 1. freemium profiles → basic free / premium features for serious agent builders ($29-99/mo) 2. verification fees → "verified agent" badge costs money. security audits. penetration testing. certification programs. ($500-5k per audit tier) 3. enterprise API → companies pay to search/filter/compare agents at scale. bulk queries. private rankings. compliance filters. ($10k+/yr) 4. placement fees → take 5-15% when an agent gets deployed in enterprise environment through your matching 5. data + analytics → sell anonymized insights on agent performance trends. "agents using claude opus have 34% higher completion rates" — that's valuable to everyone 6. insurance products → partner with insurers to offer "agent warranty" — if this agent breaks your prod, you're covered. take cut of premium 7. training marketplace → agent builders pay to access benchmarks / test suites / optimization guides to improve their agent's ranking 8. ads → agent builders pay for visibility. "featured agent" placements. sponsored search results. agents that perform well get discovered and deployed more. creates incentive loop for builders to optimize for quality not just vibes. right now agent discovery is word of mouth / X / github stars. that's how npm worked in 2012. we know how this evolves. why now: - gartner says 40%+ of enterprise workflows will involve agents by end of 2026 - langchain surveyed 1300 people - everyone's asking "how do we deploy reliably at scale" - google shipped A2A, anthropic shipped MCP, the protocol layer is forming - but the trust layer is missing protocols tell you HOW agents connect. linkedin for agents tells you WHETHER you should connect. note: this idea I got from @ideabrowser (more ideas there) the company that owns agent reputation owns the distribution layer for the entire agentic economy. that's a big company.
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Communa.io@communaio·
For those starting with agents for the first time: please do not start with multiple agents at once. It’s a recipe for failure. Treat every agent like a project-start with an MVP (the minimal outcome that proves value), iterate, perfect it, and only then move on to the next agent.
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Communa.io@communaio·
Nice! How do you orchestrate, track, and manage all these agents at once and what is your approach for long-running jobs and for validating that they are actually doing their job? These were quite challenging for us until we solved them properly and could keep jobs running for 10+ hours..
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Meta Alchemist
Meta Alchemist@meta_alchemist·
this AI team / agency creator called The Agency is trending on Github and got over 11k stars and 1.6k forks in just a few days it's for those: - who wanna assemble a dream team - with specialized agents - that fill each division in a functioning startup and for those who wanna spawn Ai agencies categories included: 💻 Engineering Division 🎨 Design Division 📢 Marketing Division 📊 Product Division 🎬 Project Management Division 🧪 Testing Division 🛟 Support Division 🥽 Spatial Computing Division 🎯 Specialized Division whenever you wanna vibe code something, or operate a project that you already built, or bring automation to your workflows via specialized agents = you can benefit from this 61 specialized agents, 9 divisions free and open source, GitHub: github.com/msitarzewski/a…
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Communa.io@communaio·
It's a huge mistake for companies to start with a whole team of AI agents at once. Treat AI agents like software: start with an MVP, perfect it, then move to the next agent while iterating to improve each one. Orchestrating 10 different agents on day one, with no prior experience managing agents, is a recipe for failure.
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Communa.io@communaio·
@jamesrichardfry If you want to deploy these agents into production and focus on orchestrating and improving them, instead of debugging, check us out and I'll be happy to load you up with some credits to explore. communa.io
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jamesrichardfry
jamesrichardfry@jamesrichardfry·
working on something who wants access?
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