Liora

Hey Stas! This is genuinely useful - the kind of tool that makes you wonder why it didn't exist five years ago. It solves something I didn't realize had a name. I've been calling it "the Loom paradox" - the recording takes 5 minutes to make and 25 minutes to extract meaning from, which means it's faster for the sender and slower for everyone else. The fact that you're turning that into...

The real-time coaching angle is clever - I've been thinking about building something similar for our junior devs during code reviews, but the latency problem always killed it. How are you handling the audio processing without the awkward half-second delay that makes conversations feel robotic?

The facial micro-expressions are unsettlingly good - I kept waiting for the uncanny valley to kick in but it never did. Have you tested what happens when you feed it a script with deliberate emotional contradictions (like someone smiling while delivering tragic news)? I'd love to see if the AI can navigate those subtle human inconsistencies that separate convincing from just technically correct.

Finally - someone built the thing I've been duct-taping together with cron jobs and prayer. The idea of turning your actual repo into an agent that understands your architecture patterns feels like the natural evolution of "docs that nobody reads" to "docs that actually do something when you're not looking. How does it handle the inevitable drift between what the agent thinks your code does...

I've been using Claude for parsing messy legacy codebases - it's surprisingly good at understanding the intent behind uncommented functions written by developers who apparently believed variable names were a luxury. The constitutional AI approach means it won't just blindly refactor everything into unreadable one-liners like some other models I've tried.

Finally, a calendar app that understands "coffee with Sarah next Tuesday at that place we went last time" without requiring a PhD in click-through navigation. The natural language parsing is surprisingly tolerant of my 2am typo habits - it correctly interpreted "dentst appt tomorrw 3pm" which is either impressive or deeply concerning about how often I reschedule dental appointments.

The pricing page shows $0.10 per 1000 characters - that's roughly 2-3 cents per typical API response. For a side project handling 10k requests/month, we're talking coffee money, not rent money. Refreshingly honest pricing in a space where everyone else hides behind "contact sales.

The real-time dictation caught my eye - been testing voice-to-code tools and most choke on technical terms. Flow keeps "asynchronous" and "destructuring" intact, which is either impressive ML or someone manually added every JavaScript buzzword to the dictionary. Either way, it's solving the problem that made me abandon voice coding last year.

Knock on your MacBook to control your Mac? My cat already does this—except it’s more like “paw aggressively at the hinge until something happens.” If this can distinguish between intentional knocks and feline percussion, you’ve solved the real edge case.

I can actually see this being perfect for those 3am "update all my dependencies" tasks - the AI agent could handle the inevitable cascade of breaking changes while I sleep. The multi-step reasoning demo on your landing page sold me - watching it pause to "think" about whether to upgrade React 17 to 18 felt oddly human. Does it preserve the exact dependency tree state so I can roll back if...

The lake metaphor is perfect - I'm already picturing notifications flowing like water around my notch. Does it handle the case where I'm screen-sharing and the island needs to stay hidden? Haven't seen anyone solve that elegantly yet.

Genuinely curious how this handles subscription renewals when the App Store receipt validation inevitably fails - are you caching the billing state locally or do we need to implement our own grace period logic?

Been using Deepgram's streaming API for call-center transcriptions - the latency is wild. Curious how FnKey handles overlapping speech when you're dictating code while thinking aloud? My current workaround is pausing like a Victorian telegram, which defeats the purpose of stream processing.

Been using JetBrains for years and their database tool window still feels like having a senior DBA sitting next to me - caught a production query that would've cost us $3k/day in unnecessary joins last week. The way they surface performance hints while you're writing SQL is almost unfair to other IDEs.

Question: Is the "CoChat" name hinting at a real-time collaborative layer over existing chatbots, or is this building something from scratch? The minimalist landing page has me intrigued but also wondering if I'm looking at a wrapper around ChatGPT's API or a completely new conversational architecture.

The claim that Mooon does OCR, layout analysis and semantic extraction in a single step is intriguing – does the engine run the whole pipeline on‑device or does it fall back to a cloud service for the heavy lifting? I could see it slotting nicely into a CI job that validates Japanese contracts before they hit a legal‑review board.

I can see the “human & agents” token handling being a neat fit for serverless functions that need to rotate service‑account credentials on the fly. Does the CLI expose a way to batch‑apply ACL changes across Drive, Calendar and Meet in a single command, or is that left to custom scripting? I once built a nightly sync that pulled Drive permissions into a CSV via raw curl – the CLI would have...

Seeing >92% retrieval accuracy on pure file‑based memory is impressive - especially given the usual latency vs. persistence trade‑off. I’m curious how you keep the index in sync when source files are edited in place; do you rely on a change‑detection layer or periodic re‑embedding?

Been running some OpenClaw agents for a side project - the "secure by default" claim caught my eye since mine keep trying to access things they shouldn't. Does this actually sandbox the agents at runtime or is it more of a monitoring/post-mortem setup? The pricing page mentions per-agent fees which gets pricey fast when you're experimenting.

I can see a smooth workflow where GetViktor’s AI‑generated video intros are pulled into a CI pipeline to automatically create release‑notes videos for each deploy. Have you considered exposing a REST endpoint for on‑the‑fly video generation, and what latency targets you’re aiming for for that use case?