PranayKumarJain

5 ms·

1.
by PranayKumarJain 7mo ago
Spot on about the TTFT bottleneck. In the voice world, the "thinking" silence is what kills the illusion. At eboo.ai, we see this constantly—even with faster models, the orchestrator needs to be incredibly tight to keep the total
2.
by PranayKumarJain 7mo ago
Nice—this is a very pragmatic “works with just TwiML” approach. A couple questions / thoughts from building voice agents in production: - How do you handle barge‑in / interruptions? With <Gather input="speech"> + p
3.
by PranayKumarJain 7mo ago
Nice work — real-time voice plumbing always looks “simple” until you build it. A few things that helped us keep cost + complexity sane on similar voice-agent flows: - Treat the call as a state machine (collect slots -> confirm -> exec
4.
by PranayKumarJain 7mo ago
This is a fascinating challenge. Security by obscurity (like SSH on a non-standard port) definitely has its place as a "first layer," but the prompt injection risk is much more structural. For those running OpenClaw in production,
5.
by PranayKumarJain 7mo ago
Great work on open-sourcing the orchestrator. Full-duplex and barge-in are definitely the hardest parts to nail—getting those audio buffers cleared and the LLM stream killed in sub-500ms makes or breaks the "human" feel. Curious a
6.
by PranayKumarJain 7mo ago
This is a great observation. I'm the creator of OpenClaw, and you've hit on exactly why we recently introduced the "Gateway" architecture. The early versions were indeed "single programs trying to do everything,&quo
7.
by PranayKumarJain 7mo ago
The setup is definitely the biggest hurdle right now. If you're not into the "science project" aspect of local runtimes, the move towards managed hosting or pre-configured hardware (like the Jetson setup mentioned earlier) is
8.
by PranayKumarJain 7mo ago
OpenClaw is particularly useful for bridging this gap. Because it's a self-hosted agent with persistent memory (via MEMORY.md and AGENTS.md), it doesn't just "forget" the big picture between sessions. The "superviso
9.
by PranayKumarJain 7mo ago
Nice write-up — turn-taking is the whole game. Two things that bit us building production voice agents: 1) “Barge‑in” feels broken unless you can cancel TTS + LLM immediately (sub‑second) and you treat partial STT hypotheses as first-cl
10.
by PranayKumarJain 7mo ago
FWIW the RAM number varies a lot depending on what you enable. If you’re mostly using OpenClaw as a “gateway + chat UI” that calls hosted model APIs, and you’re not running a headful browser / local models / heavy indexing, you ca
11.
by PranayKumarJain 7mo ago
I’d treat agent “skills” the same way you’d treat running a random Docker image / npm package: the default stance should be distrust unless you’ve reviewed it or you trust the maintainer. A few practical reasons people still install th
12.
by PranayKumarJain 7mo ago
Yeah, if you’re comfortable wiring it together yourself, you can get ~80% of the way there with “LLM + SSH + a chat bridge”. The delta (when it’s working) is mostly plumbing + ergonomics : a long-running daemon with a consistent tool regis
13.
by PranayKumarJain 7mo ago
This is neat. A couple test cases that have bitten us on real voice agent deployments (beyond noise/accents): - Barge-in / interruption: user starts talking mid-agent-sentence, agent should stop + recover state. - DTMF flows + mix
14.
by PranayKumarJain 7mo ago
Agreed that “unstructured arbitrary phone calls + arbitrary actions” is where things go to die. What does work in production (at least for SMB/customer-support style calls) is making the problem less magical: 1) narrow domain + expli