Hermes like the Agent not the handbag. Building Voice-AI Agents, Director of DevRel @Agoraio | Polyglot Engineer / Evangelist | Thoughts & opinions are my own
New York, USA
Joined June 2009
- Tweets10.2K
- Following1K
- Followers1.8K
- Likes25.8K
This is so true. Even as an avid user of Codex and Claude, long term open models will be crucial for businesses running agents.
API costs aside, most businesses don’t want frontier labs training on their data, and the only way to guarantee privacy is to own the intelligence.
Own your intelligence.
Anyone that opposes this has something to sell you (perhaps your own intelligence back to you.)
Local models need to continue proliferating. The “absolute unit” massive models may be out of reach for now locally, so your best option is to, indeed, keep your options open. Own your harness, data, connections, runtime: your agents. Embrace open source.
this is wild. Voice first AI without the noise. super cool!
We’ve raised $1.3M from YC & Afore Capital so you never have to type or speak again.
Typing is slow. Talking into your computer is awkward. Subvocal fixes both
Our glasses give you the speed of speech without you making a sound or touching a keyboard.
It tracks your internal speech muscles with non-contact sensing and decodes silent, almost invisible mouthing into text at more than 200 words/min.
Pre-orders are now live at:
subvocal.co/preorder?utm_sou…
Hermes ᯅ retweeted
introducing prism, the world’s first speech-to-speech model you can’t tell from a human in conversation
prism has:
> 300ms response time, 4x faster than OpenAI GPT-Live
> outperforms every other s2s model on intelligence (with NO reasoning)
> the first s2s model customizable through reinforcement learning
we’re a team of 35 with $35M in funding, and we’re unlocking s2s model adoption faster than openai, google, and x.
the first 100 people to sign up here get 1 month free: rime.ai/prism?utm_campaign=p…
Not surprised to see the consolidation in the Voice AI space. Being strictly an STT provider was not viable long term as we see the Deepgram’s competitors like Assembly releasing TTS and Rime with their Voice to Voice models.
This also solidifies the need for the full stack (RTC, ASR, LLM, TTS) when building voice agents. This is something @AgoraIO we’ve understood for years and focused on building the best orchestration layer atop of our industry leading Realtime Network (SDRTN).
Deepgram said that it is committed to keep Pipecat open source.
spr.ly/6010BHm7ow
Hermes ᯅ retweeted
We tested Nemotron 3.5 Transcribe in a classroom demo, and word-level timestamps stood out: students can replay a lesson with a timed transcript alongside it. Agora powers the live interaction;
@NVIDIAAI adds post-session transcription that helps extend the lesson’s value.
Meet NVIDIA Nemotron 3.5 Transcribe 🎙️
An open-weight, promptable 30B MoE model with ~4B active parameters that brings transcription in 40 languages, speaker attribution, translation, contextual prompting and audio understanding into one checkpoint.
Watch it keep track of who said what when everyone’s talking at once.
1/ 🧵
Hermes ᯅ retweeted
Yesterday we ran Gemini 4 Argon (Google Antigravity) on the same 92 live APIs as Claude Code, Codex and Muse.
Nearly 8 in 10 APIs got roughly the same score from all four agents.
Same #1 on all four leaderboards in 12 of 24 categories:
Payment: @stripe
Voice STT: @AssemblyAI
Voice TTS: @ElevenLabs
Document Parsing: @reductoai
Durable Workflow: @PrefectIO
Email: @resend
Observability: @datadoghq
Cloud Hosting: @render
Meeting Bot: @meetstreamai
Unified API: @merge_api
Video Infra: @MuxHQ
Voice Infra: @AgoraIO
@ryanseams, @raunakdoesdev, @zenorocha, @ojusave, @shensi, @aidan_timmerman, @lightsagehq
@
Hermes ᯅ retweeted
Presented by our partners at @AgoraIO: Sid Sharma, VP of AI Innovation & GTM, joins Boardroom Exclusives to discuss Agora’s expansion from connecting people to bringing AI to life through real-time voice and video. He explains how Agora’s low-latency infrastructure connects models from OpenAI and Google with users at scale. Plus, $40.4M in Q2 revenue and seven consecutive quarters of GAAP profitability. $API
I’m not sure in what world this make any sense.
I’d love to hear the discussion for this. Im imagining the product meeting and someone chimes in..
“You know how we protect against the most malicious tool calls, what if we support an env var that allows it anyway?”
One of the more interesting demos I came across at RTE 2026.
@ORULINKAI is building WatcherRobot, bringing conversational AI into the physical world.
Moving beyond AI agents that just respond on a screen, toward agents that can interact with the world around us. 🤖
This isn’t as severe as the latest PHP and Node exploits, but if you’re still using a frontier LLM model for classification and not a small language model (like the ones from @scaledown_team) you might be vulnerable to overspending on basic tasks.
Does classifying a customer request need the same model as holding a conversation?
In this episode of the Convo AI World Podcast, @hermes_f speaks with @neal_k_patel, co-founder of @scaledown_team, about choosing models for the specific jobs inside an AI application.
Hermes ᯅ retweeted
Does classifying a customer request need the same model as holding a conversation?
In this episode of the Convo AI World Podcast, @hermes_f speaks with @neal_k_patel, co-founder of @scaledown_team, about choosing models for the specific jobs inside an AI application.
Hermes ᯅ retweeted
@AgoraIO is being used for the AI friend/enemey.I'll share what that looks like later but it's actually really cool. Just think: an AI companion that actually plays a game with you so you can say, "Hey go protect that side" or "Send some reinforcements here," and it actually responds.
Hermes ᯅ retweeted
I built a fighting game where you create your own ultimate moves by voice.
@AgoraIO powers voice chat. @reactorworld FastH3 Omni turns your words into a cinematic attack
Early demo. Going open source soon
Hermes ᯅ retweeted
We talk a lot about Voice AI, but not nearly enough about the infrastructure making it possible.
Real-time voice AI keeps evolving, but one thing remains constant: the network.
Back at @ISTatPENNSTATE talking about networking tech.
We talk a lot about Voice AI, but not nearly enough about the infrastructure making it possible.
Real-time voice AI keeps evolving, but one thing remains constant: the network.
Back at @ISTatPENNSTATE talking about networking tech.
Hermes ᯅ retweeted
🗣️ User: "STOP!"
🤖 AI Agent: "Sure! But first, let me explain..."
Why is interrupting a Voice AI agent so hard? 👀
Because stopping audio playback ≠ cancelling the entire pipeline.
VAD → ASR → LLM → TTS → Playback
Barge-in is a real-time coordination problem, not just a mute button.
That's where Agora Conversational AI comes in. ⚡
#VoiceAI #Agora #AIEngineering
Hermes ᯅ retweeted
You already gave the LLM the answer. So why is it writing it out from scratch?
Introducing a new AI model architecture: Constrained Decoding Models (CDMs)
LLMs were built to write. Most production workloads just need an answer: fast, consistent, and affordable.
CDMs are purpose-built for 1 task each. They read your input once and skip the token-by-token generative loop that makes LLMs slow and expensive.
Not just a decision model, but a family of 3 CDMs live today:
• Classify: define your labels and get back a calibrated probability + reason for each. Used for routing, tagging, and intent detection.
• Extract: describe the entities in natural language and get back well-formed JSON with confidence scores + citations. Used for web scraping, document processing, and PII redaction.
• Summarize: pass in long text, images, or PDFs and get back a consistent summary under 1,000 tokens. Used for context compaction, metadata generation, and transcript digests.
Built for production:
• 1M tokens of multimodal (text + image) input, 31x larger than Jev
• 77.2% on DecisionBench vs Jev's 72%
• 200x faster, 467x cheaper than frontier LLM APIs
• $0.05/M input tokens. Output is free (yes, even for summarize)
Live on your favorite platforms today:
@OpenRouter @vercel_dev @LiteLLM @LangChain @TrustedRouter @itsArthurAI @useRouterPlus
Get 50M input tokens for free (for the first 50 hours) at link below 👀
🤖 Made with AI
Kicking off Day 3 of SF @Techweek_ by ordering a coffee with my voice at the @cartesia event.
Hermes ᯅ retweeted
Your voice agent responds instantly.
Cool. But did it actually understand the person?
I attended Agora’s From Prototype to Production: Scaling Voice AI at #SFTechWeek. The panel got into what happens AFTER the demo.
Speed isn’t everything. Customer service and coding agents have different expectations. Acknowledge quickly, but take the time to do the work properly.
More context isn’t always better. Give the model what it needs, when it needs it. Keep conversations responsive while heavier work happens in the backend.
Stop asking one model to do every job. Route simple tasks to faster models. Bring in deeper reasoning when it matters.
Test beyond the happy path. Right tool? Right information? Correct permissions? Trace failures and evaluate audio, not just transcripts. Your tests need to reflect your business.
The panel discussed smart glasses combining voice, gaze and spatial context. “Remember that door design” hits differently when the agent knows which door you’re looking at.
My takeaway, working at @Speechmatics getting to the wrong answer faster is still getting it wrong.
Huge thanks to @AgoraIO for an awesome event!
Next, will be at Speechmatics × Aqua Voice × LiveKit for Solving Voice as an Interface.
partiful.com/e/Qfb44oJOo4cYv…
#VoiceAI #AIAgents
