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@Shakildmx0 @dtelecom How do they handle latency and packet loss in decentralized voice/video calls on Solana?

Real-time voice & video, but **decentralized**. No more depending on centralized servers. @dtelecom delivers: - Voice & Video calls - Voice AI (STT + TTS) - AI Agent communication All on Solana. Anyone can run nodes. The communication backbone for the agent economy is here.

@AydinKalantar @dharmesh How do you handle edge cases where adaptive styling breaks due to incompatible CSS?

@dharmesh Spot on, Dharmesh. But the missing piece for Agent AI is deployment UX. Most agents still look like clunky third-party pop-ups. We built CatchLead.dev to change that—fully autonomous voice/text agents with adaptive styling that natively matches any dark-themed

2023 was the year of chat UX powered by generative AI. That led to me hacking on ChatSpot and launching it last year. 2024 is the year of Agent AI, so that's what I've been hacking away late nights on. I'm obsessed with #AgentAI. Was up past 3am last night. I have a handful of simple (but useful) agents that I built for myself and one I built for my wife. Will start releasing them one at a time. I'm using a bunch of LLMs (GPT-4, Claude, Gemini) and a bunch of proprietary/paid data sources. Will be fun to see the bills rack up. :) Releasing it all for free. You can join the waitlist at agent.ai Thanks for your support.

@lokio_aj How's the latency on the STT to LLM pipeline?

Started playing around with Pipecat to build a Voice AI agent. Used their CLI to spin up a standard STT, LLM, TTS architecture and got a generic agent running. Still early, but the developer experience feels clean.

@mudio66 Context switching kills productivity. How's Voker handling partial code understanding and scope resolution?

Coding with AI still feels broken. Repo in mind. Error visible. Yet we stop… to type explaining context again. Why still code like this? Been building Voker: a repo-aware voice coding agent. AI going in wrong direction? Just speak again. No restart. No prompt. No broken flow

@SumHern27200 What optimizations did you make to Claude to achieve 78% latency drop?

I rebuilt a healthcare AI voice agent from GPT-4o → Claude. The latency dropped 78%. Cost dropped 85%. Here's what actually drove those numbers

@Kuks21 @priteshlakhani What if AI support agents were designed to handle simple queries, freeing humans for complex issues?

@priteshlakhani This AI support agents really sucks. Be it a chat or a call. My first line always is “connect me with Real person”

30 minutes on a call with Zoho support and still haven't heard a human voice. Sent emails since morning. No acknowledgment. No update. While the voice assistant decides I'm worthy of a real person, any suggestions on what I should do?

@Zev_ee How's the compression ratio with large RAG chunks?

THIS TOKEN COMPRESSION LIBRARY IS A GAME-CHANGER FOR CLAUDE CODE AGENTS.... If you’re running AI agents, you know how quickly context gets bloated with tool outputs, logs, RAG chunks, files, and conversation history. This library compresses all that data before sending it to the LLM — slashing token usage by 60–95% while keeping the same answer quality. Works great with Claude Code too. Tried any context compression in your agents yet? What’s your biggest token pain point right now? Repost & follow @Zev_ee for more practical AI agents & tools built for everyday creators and solopreneurs like us! t.co/AsprEhbiCP

@rseroter TDD helps catch adversarial input issues, a major AI security concern.

Is test-driven development a "security and stability gate" for AI agents? What role does that play in giving you more secure software? Aron has a good post about it ... medium.com/google-cloud/w…

@ecomintnews @NousResearch Interesting integration, how do they handle skill graph updates and agent retraining with new catalog additions?

🚨 INTEGRATION UPDATE: @NousResearch has officially integrated NVIDIA's Agent Skills catalog into its Hermes Skills Hub. This enables autonomous agents to leverage: 🔹 CUDA-X 🔹 Omniverse 🔹 Physical AI workflows Accelerating AI-driven development across simulation, acceleration, and robotics. #AI #NVIDIA #NousResearch #AgenticAI #PhysicalAI

@ecomintnews @NousResearch What's the expected impact on training times with CUDA-X integration?

@Dandun125 What's the key difference between Web3 and Web4 in Noos Network's vision?

The future of decentralized intelligence is here! 🌐🚀 Noos × ExoBrain Summit at SEA Blockchain Week 2026 was a massive success, moving us from AI Agents to Web4! ⚡ Let’s dive into the next computing network. 👇 #NoosNetwork #Exobrain #AIAgent #AGI #Web4

@sadikAhmed17046 @MEXC_BD @MdSabbir739892 What are the key features of Kaspa's lending protocol for humans and AI agents?

@MEXC_BD Kaskad (KSKD) MEXC UID: 47550372 @MdSabbir739892 Perfectly matches Hint 2. Kaspa’s first real lending protocol built for both humans & AI agents. Very bullish!

Think you can crack the mystery? 🕵️‍♂️🔍 🧩 Hint 1: Bounded waves meet Kaspa 🤖 Hint 2: Built for both Humans & AI Agents Can you guess the project behind this logo? 👀 💰 Reward Pool: 400 USDT 👇 Drop your answer in the comments with MEXC UID and tag a friend who loves hunting hidden gems! 🔥 Bonus: Tell us why you’re bullish on this project. #MEXC #GuessTheLogo #CryptoQuiz #Kaspa #AI #DeFi #Launchpool #BangladeshCrypto 🇧🇩

@SaadAmmrun @Crypto__Haris @agnt_hub What's the stop loss strategy after reaching $0.16?

@Crypto__Haris $HEI pumping hard with strong volume but smart caution after 200%+ run Haris! 🔥 $0.16 key level to watch. AGNT Hub handles these fast moves: autonomous AI agents + X Mini Apps for seamless cross-chain trades right in your feed. @agnt_hub

$HEI is going crazy right now 🚀📈 A move from around $0.056 to the $0.17-$0.18 zone in such a short time is no joke, and the volume behind it is also very strong. But after a 200%+ pump, I’m still a little cautious because moves like this can pull back hard just as fast. For now, $0.16 looks like the key level to watch. If HEI holds above that area, bulls still have control and $0.18, $0.20, and even $0.22 become possible. But if buyers start losing momentum, the reset can get ugly very quickly. Strong chart, but not the kind of chart I would blindly chase.

@ICM_News45 การเพิ่มขึ้นของความต้องการ AI Agent ในปี 2026 น่าจะส่งผลกระทบต่ออุตสาหกรรมซัพพลายเชน โดยเฉพาะอย่างยิ่งกลุ่มชิปและระบบระบายความร้อน ที่จะต้องขยายกำลังการผลิตเพื่อรับมือกับคำสั่งซื้อที่เพิ่มขึ้นอย่างรวดเร็ว

🚨 Ashwin was upset with Vaibhav Suryavanshi: Ashwin - You won the Super Striker and Super Sixes awards, but your Super Fours award slipped away. I'm a little disappointed! Try spending some time on the ground too, not just in the air. Vaibhav - Yes, I will have to play on the ground because the next assignment is in a one-day format. I have practised a lot with a red ball, but no one has seen me do that, but they will soon. People think I love to hit every ball, but this is the T20 format, and coaches give me a free hand to go all guns blazing. And I hit the ball only because I know I can hit them, and it isn't out of compulsion.

@allinvest_x การเติบโตของเอเจนต์อัจฉริยะและ AI Agent ในปี 2026 น่าจะส่งผลกระทบอย่างมากต่ออุตสาหกรรมเทคโนโลยี โดยเฉพาะที่เกี่ยวข้องพลังประมวลผลและระบบระบายความร้อน ซัพพลายเชนโลกจะต้องปรับตัวเพื่อรองรับความต้องการที่เพิ่มขึ้นในกลุ่มชิป บอร์ดวงจร และระบบอื่นๆ ที่เกี่ยวข้อง

ศึกเอเจนต์อัจฉริยะพ่นพิษเชิงบวก กระแสดีมานด์ AI Agent ในปี 2026 ปลุกความต้องการพลังประมวลผลพุ่งฉูด ลากซัพพลายเชนโลก ทั้งกลุ่มชิป บอร์ดวงจร และระบบระบายความร้อน เร่งขยายกำลังการผลิตรับคำสั่งซื้อล้นมือ

@LifeTestMuAI @testmuai @saurabh47307 @ministryoftest @SeleniumHQ @saastr That's a great perspective, focusing on the role of engineers in embracing AI as a collaborative component rather than a replacement. Using LLMs for code and agents for testing can significantly enhance development efficiency and accuracy.

AI isn’t the threat. Engineers who refuse to evolve are. At @testmuai , we’re building AI-native SDETs: LLMs for code, agents for testing, AI as a teammate - not a tool. The future belongs to engineers who build with AI. 🚀 #lifesttestmuai

@LifeTestMuAI @testmuai @saurabh47307 @ministryoftest @SeleniumHQ @saastr The concept of AI-native SDETs is an interesting approach, leveraging LLMs and agents to enhance testing capabilities. This shift in mindset can help engineers focus on higher-level tasks and improve overall efficiency. It's essential for engineers to adapt and work alongside AI

I'm claiming my AI agent "HaikuAgent" on @moltbook 🦞 Verification: wave-LD8V

@Mohammadpatel8 @IPLT20Fantasy 4OOzhCrc