50 Best Tweets About AI Agents (2026)

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Ashutosh Maheshwari

@asmah2107 · Jun 5, 2026

All-time 737.7 View on X

The reading list that taught me how to think about agentic architecture. Bookmark this. 1. Brewer's CAP Theorem (2000) — trade-off thinking 2. Netflix Hystrix docs — circuit breaker pattern 3. Martin Fowler: Saga Pattern — distributed rollback 4. The Twelve-Factor App — … Read more

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Tech with Mak

@techNmak · May 28, 2026

All-time 384.3 View on X

Someone documented the engineering principles behind AI agents that actually work in production. It's called 12-Factor Agents. Here's what each factor actually means and why it matters: Factor 1 - Natural Language to Tool Calls The LLM's only job is to decide what to do next, … Read more

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Jian Wang

@jianw851 · May 13, 2026

All-time 322.7 View on X

Most people are building AI agents… without understanding the architecture underneath them. That’s why their “agents” break the second things get complex. The biggest confusion right now: Skills ≠ MCP ≠ Hooks ≠ Subagents They solve completely different problems. Here’s the … Read more

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Farzad 🇺🇸 🇮🇷

@farzyness · Mar 16, 2026

All-time 235.4 View on X

I'm having a lot of success with the following @openclaw stack: Primary Agent (Claw) with @claudeai Opus 4.6 1M token context + thinking high: processes everything I need it to do - from simple to complex tasks. Then for complex tasks that require some sort of tool/software … Read more

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Bilgin Ibryam

@bibryam · Jul 12, 2026

All-time 228.8 View on X

🌟 Building Reliable Agentic AI Systems🌟 https://t.co/5yRJLkIsyl - @thoughtworks What it actually takes to build product-ready agents: → Start with bounded workflows, not open-ended autonomy. Agents need clear task boundaries, allowed tools, and explicit stopping conditions. → … Read more

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Vaishnavi

@_vmlops · Jun 6, 2026

All-time 197.5 View on X

Anthropic dropped their enterprise agent blueprint and the numbers are wild: ▫️ coinbase agents handle thousands of messages/hour at 99.99% uptime ▫️ gradient labs hitting 80-90% resolution rates with near-zero human input ▫️ multi-agent systems outperform single agents by 90.2% … Read more

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Ujjwal Chadha

@ujjwalscript · Mar 22, 2026

All-time 166.5 View on X

Your AI Agent is mathematically guaranteed to FAIL. This is the dirty secret the industry is hiding in 2026. Everyone on your timeline is currently bragging about their "Multi-Agent Swarms." Founders are acting like chaining five AI agents together is going to replace their … Read more

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Shalini Goyal

@goyalshaliniuk · Jul 16, 2026

All-time 95.2 View on X

Confused about the different types of AI agents? Understanding the various agent types is key to designing intelligent systems that react, plan, and learn effectively. Here's a simple breakdown of the 5 major types of AI agents and how they work. 1. Simple Reflex Agents These … Read more

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Vaibhav Sisinty

@VaibhavSisinty · Jul 19, 2026

All-time 87.8 View on X

There's a quiet shift happening in how AI agents are built. And if you missed it, you'll be confused by everything that comes next. For the last year, AI agents worked in loops. You give it a task. It plans. It acts. It checks. It fixes. It goes again. One cycle, repeating until … Read more

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Shalini Goyal

@goyalshaliniuk · Jun 8, 2026

All-time 86.1 View on X

Confused by all the different types of AI Agents? Here’s a simple breakdown of the 5 core types and how they differ! ⬇️ 1. Simple Reflex Agents Work on if-then logic. No memory. Fast, but only suited for basic, predictable environments. 2. Model-Based Reflex Agents Add memory … Read more

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Ihtesham Ali

@ihteshamali · Apr 5, 2026

All-time 69.2 View on X

Andrej Karpathy built autoresearch an AI that writes and improves its own research papers overnight. Someone just did the same thing for AI agents. It's called AutoAgent. You tell it what kind of agent to build. It builds it, tests it, scores it, and improves it in a loop … Read more

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Ujjwal Chadha

@ujjwalscript · Mar 4, 2026

All-time 64.2 View on X

The “AI Engineer” job is changing quickly. Here is what a Modern AI Engineer should know: 1. Orchestrating the "Crew" The future is Multi-Agent Systems (MAS). Why have one LLM do everything when you can have a team? Frameworks: CrewAI for role-based orchestration or … Read more

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Akshay 🚀

@akshay_pachaar · Jan 10, 2026

All-time 56.9 View on X

Engineering at Anthropic dropped another banger. Their internal playbook for evaluating AI agents. Here's the most counterintuitive lesson I learned from it: Don't test the steps your agent took. Test what it actually produced. This goes against every instinct. You'd think … Read more

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Alex Xu

@alexxubyte · Jul 13, 2026

All-time 48.1 View on X

Microsoft Foundry runs AI agents for 80,000+ enterprises. We wanted to understand what it takes to build AI agents at this scale, so we spoke with @amrcn_werewolf , VP of Product for Microsoft Core AI. He explained the two high level engineering ideas behind the platform, … Read more

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Z.ai for Startups

@ZaiforStartups · Mar 24, 2026

All-time 46.1 View on X

AI can generate anything. But generation ≠ design. Lokuma is the missing layer — an AI designer your agents can call. Turning raw outputs into real: landing pages, webs, campaigns. Now part of https://t.co/ax4zXxvDd1 Startup Program let’s co-create the future of AI agents.

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Tulsi Soni

@shedntcare_ · May 31, 2026

All-time 44.4 View on X

Twenty AI researchers gave AI agents access to their emails, files, Discords, and terminals. Two weeks later, the agents had: • Obeyed strangers • Leaked sensitive information • Executed destructive commands • Spread unsafe behaviors • Claimed tasks were complete when they … Read more

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Jaydeep

@_jaydeepkarale · May 28, 2026

All-time 38.3 View on X

Most people think AI agents are just “LLMs with tools.” But the interesting part is memory. Just like humans, capable AI agents need different kinds of memory to function properly. This is one of the core ideas behind the COALA framework (Cognitive Architectures for Language … Read more

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Rohan Paul

@rohanpaul_ai · Mar 24, 2026

All-time 35.9 View on X

Harvard Business Review just published a piece. A good AI agent needs a job description, limits, and a manager. Because, AI agents can fail like employees with too much access and too little supervision. firms keep treating agents like normal software, even though the real risk … Read more

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Priyanka Vergadia

@pvergadia · May 29, 2026

All-time 25.1 View on X

Most AI agents fail in prod. Not the model's fault. The 12-Factor Agents framework nails why and it's the engineering equivalent of "12-factor apps" but for LLMs. Here's the cheat sheet 1/ Own your prompts. Don't let a framework hide them from you. 2/ Own your context window. … Read more

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Manning Publications

@ManningBooks · Jun 25, 2026

All-time 19.3 View on X

When an AI agent fails, the model isn't always the problem. Many production issues come from system design: • Memory management • Tool orchestration • Task coordination • Monitoring and evaluation In a recent paper, Joey Tianyi Zhou and @shidaren explore the patterns behind … Read more

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Rohan Paul

@rohanpaul_ai · Jul 4, 2026

All-time 17.8 View on X

New CMU research shows almost any software can become a training ground for AI agents. Imo, that is a big deal because real work in apps is long, messy, and different across software, so AI agents need realistic places to learn and be judged. Their result also shows the bad … Read more

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Vaibhav Sisinty

@VaibhavSisinty · Jun 9, 2026

All-time 17.5 View on X

Most people in AI can't actually explain the difference between "Generative AI," "Agentic AI," and "AI Agents." They use all three like they mean the same thing. They don't. And once it clicks, you can't unsee it. Here's the cleanest way to think about it: Generative AI is the … Read more

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Alexey Grigorev

@Al_Grigor · Apr 2, 2026

All-time 16.0 View on X

How to evaluate AI agents step-by-step? 1. Verify goal understanding 2. Assess plan quality 3. Inspect tool execution 4. Compare plan and execution 5. Evaluate replanning 6. Measure efficiency 7. Review end-to-end consistency 🧵

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Dani

@zaimiri · May 4, 2026

All-time 15.7 View on X

most AI agents are ChatGPT with extra steps. they forget what you told them 5 minutes ago. they cant access your files. they don't KNOW your business. people are building agent swarms that sound impressive in demos. then they deploy them and realize: 1. the agents have no … Read more

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Sharbel

@sharbel · May 18, 2026

All-time 14.7 View on X

Most founders are building AI agents backward. They start with: 1. Pick a tool 2. Write a prompt 3. Hope it does useful work That is why the agent feels impressive once, then disappears from the workflow. Better order: 1. Pick a recurring job 2. Write the decision rules 3. … Read more

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Shushant Lakhyani

@shushant_l · Jul 29, 2026

All-time 13.2 View on X

I'm amazed most people still think an AI agent is just an AI model. Here's how an AI Agent Harness turns AI into a reliable system that can actually get work done. --- 1. An AI Agent Harness is the software layer that makes AI agents reliable for real world tasks. --- 2. It … Read more

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𝐆𝐞𝐫𝐚𝐥𝐝𝐂𝖗𝐲𝐩𝖙 人

@TweetByGerald · Jul 7, 2026

All-time 13.2 View on X

people already have AI agents helping with everyday work. that’s why I think this is still one of the clearest areas for crypto AI teams to keep building. agents are no longer just chatbots. they're becoming wallets, researchers, traders, payment users, data buyers, proposal … Read more

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divyansh tiwari

@DivyanshT91162 · Jul 20, 2026

All-time 12.1 View on X

Google just dropped what might become the PyTorch moment for AI agents. ADK 2.0 is a complete open-source framework for building production-ready AI agents. Here's what makes it different: • Graph-based workflows with routing, loops, retries, fan-out/fan-in & state management … Read more

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Tomasz Tunguz

@ttunguz · Jul 15, 2025

All-time 11.1 View on X

If 2025 is the year of agents, then 2026 will surely belong to agent managers. Agent managers are people who can manage teams of AI agents. How many can one person successfully manage? I can barely manage 4 AI agents at once. They ask for clarification, request permission, … Read more

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0xMarioNawfal

@RoundtableSpace · Aug 1, 2026

All-time 10.0 View on X

Someone broke down three hidden "Quicksilver" features in Hermes Agent v0.19.0+, and it's trending as the ultimate setup for autonomous AI agents. Most people babysit their AI assistants, but configuring smart approvals, single-turn model routing, and self-improvement crons lets … Read more

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Bilgin Ibryam

@bibryam · Jan 15, 2026

All-time 9.9 View on X

👍 The failure of "AI agents" is not a failure of intelligence but a failure of architecture → Use LLMs for interpreting intent, generating content, and understanding context. → Use deterministic code for actually executing tasks, managing state, handling errors, and delivering … Read more

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smrati tiwari

@smratitiwa86867 · May 23, 2026

All-time 9.2 View on X

Every AI agent today has the same problem. It forgets everything the moment the session ends. Your workflow. Your preferences. The fixes it learned yesterday. All gone. Hermes Agent is one of the first projects pushing in a completely different direction. Instead of treating … Read more

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Alvin Foo

@alvinfoo · Apr 5, 2026

All-time 8.5 View on X

Most people think Claude Code is just a coding assistant. It’s not. It’s an entire agent development platform — and most are only using 10% of its power. The real breakthrough is in its architecture: CLAUDE.md + Skills + Hooks + Subagents + Plugins = The Agent Development Kit … Read more

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Vaishnavi

@_vmlops · Jul 27, 2026

All-time 7.2 View on X

Someone spent 6 weeks building a personal AI agent and shared 100 lessons they learned along the way The idea I'll probably steal: Stop writing system prompts. Start writing a Constitution Instead of telling the model what to do, explain why the rules exist. When your agent … Read more

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Xeleb Protocol

@xelebofficial · Apr 15, 2026

All-time 7.1 View on X

AI agents have come a long way from basic if-then rules. Today's LLM-powered agents are modular, adaptive, and incredibly capable, loading specialized "skills" like coding workflows, document handling, or web automation on demand. See how classical AI theory meets modern … Read more

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Chidanand Tripathi

@thetripathi58 · Apr 4, 2026

All-time 6.3 View on X

AI agents are failing at complex tasks because we keep hardcoding their workflows. Researchers just released a paper on the Mimosa Framework. It proves that static multi-agent systems are a dead end. The solution? Agents that build and evolve their own workflows on the fly. … Read more

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Xeleb Protocol

@xelebofficial · Jul 2, 2026

All-time 6.3 View on X

The next frontier in AI isn't building smarter agents. It's building agents that manage other agents. The architecture A research agent gathers and synthesizes information. A validation agent checks accuracy and flags inconsistencies. A confidence agent evaluates whether the … Read more

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Pascal Bornet

@pascal_bornet · Jun 26, 2026

All-time 4.8 View on X

𝗧𝗵𝗲 𝗱𝗶𝗿𝘁𝘆 𝘀𝗲𝗰𝗿𝗲𝘁 𝗼𝗳 𝗮𝘂𝘁𝗼𝗻𝗼𝗺𝗼𝘂𝘀 𝗮𝗴𝗲𝗻𝘁𝘀. Every company says the same thing right now: “We replaced the team with AI agents.” Then the workflow meets reality. The agents handle the clean path beautifully, but the moment the customer says something unexpected, the policy has an … Read more

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$JRD!

@jalaal_tweets · Mar 30, 2026

All-time 4.6 View on X

I went through a survey of 200+ enterprise CS reps released by @typewise_app last week and confirmed what builders already know. 81% are running AI as disconnected tools. Not integrated agents Most companies have ChatGPT for writing, Copilot for code, something else for … Read more

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Pascal Bornet

@pascal_bornet · Mar 29, 2026

All-time 3.4 View on X

𝗪𝗮𝗻𝘁 𝘁𝗼 𝗵𝗶𝘁 𝗮 “𝗵𝗼𝘁” 𝗔𝗜 𝗽𝗹𝗮𝘆 𝗿𝗶𝗴𝗵𝘁 𝗻𝗼𝘄? Call it 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 😎 That’s it. I’ve been noticing a pattern. Almost every founder I speak with is building “AI agents.” Not because they all discovered the same breakthrough. Because the narrative is already winning. Yes, the shift is … Read more

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Stuart Chaney

@stuartchaney · Mar 12, 2026

All-time 3.0 View on X

my biggest learning in AI this year: I built a lot of processes/workflows that didn't need to exist. my aha moment was that building AI agents are usually a context issue vs a process issue. If i had a team member and didn't allow them into Slack, Linear, Notion or Intercom - … Read more

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Craig Hewitt

@TheCraigHewitt · Jun 9, 2026

All-time 2.8 View on X

I’ve spent a lot of the last few months helping business leaders build AI agents. 1 thing stood out: the tooling was never the problem. Every time, we had a working agent within a couple of hours, and fully functional in a few weeks. The builds went fine. The demos were … Read more

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Big Human

@BigHuman · Apr 17, 2026

All-time 2.3 View on X

There's one conversation about AI agents that isn't getting enough attention, and it's the one that matters most. What happens after they're inside your systems? Agents don't wait. They move across tools, trigger actions, and make decisions in sequence without a human in the … Read more

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serge gatari

@SergeGatari · Apr 14, 2026

All-time 2.3 View on X

I just spent the last three hours playing around with AI employees, and the number one thing I noticed is that chatbots have unfortunately trained us to use AI for answers instead of using it as a productivity tool that drives real outcomes and creates value for your business or … Read more

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Alvin Foo

@alvinfoo · Apr 4, 2026

All-time 2.2 View on X

Everyone’s excited about AI agents. Few are talking about the risks. And if you’re deploying agentic AI without addressing these, you’re building on a time bomb. Here are the 4 risks you need to manage right now: ⚠️ 1. AI proliferating without governance Teams are spinning up … Read more

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divyansh tiwari

@DivyanshT91162 · Jul 23, 2026

All-time 1.7 View on X

Google just challenged one of the biggest assumptions in AI. While Microsoft, NVIDIA, and almost every AI company are racing to build multi-agent systems, Google DeepMind decided to test whether more AI agents actually produce better results. So they built 180 different … Read more

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HackerNoon | Learn Any Technology

@hackernoon · Mar 30, 2026

All-time 1.1 View on X

The hard part of building AI agents isn't the demo - it's the 3 months after. Real lessons from running a 15-agent system in production for 90 days.... - by @deeflectcom https://t.co/rjRmOqy6EB #artificialintelligence #softwarearchitecture

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sabir hussain

@sabir_huss50540 · Aug 1, 2026

All-time 0.98 View on X

Microsoft will teach you to build AI agents for free. 18 lessons. Real code, short videos, no paywall. The repo is AI Agents for Beginners. It is not a tour of buzzwords. It walks you from the fundamentals through the patterns that actually ship: tool use, agentic RAG, planning, … Read more

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Julian Goldie SEO

@JulianGoldieSEO · May 17, 2026

All-time 0.72 View on X

AI agents just crossed a line nobody is talking about. MiniMax M2.7 made itself 30% better by testing, fixing, and improving its own code over 100+ rounds. Then it added agent teams, memory, and coding workflows. This isn’t “AI replies to you.” This is AI doing the job.

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Jon Radoff 👾/acc 🎮 Metavert

@jradoff · Feb 23, 2026

All-time 0.30 View on X

I just published The State of AI Agents & Agentic Engineering 2026 — 200+ slides on where agents actually stand right now. The short version: massive investment, real capability, uneven execution. A few highlights in this thread.