In partnership with
Most voice-AI products come with the same shape: a subscription, a rate limit, and a cloud dependency you can't audit. VoiceStudio breaks that shape. It clones a voice, designs a new one, dubs a video, and transcribes audio, supports 646 languages, and runs locally. No per-minute meter, and no audio leaves your machine unless you tell it to. The project also ships a local API and MCP server, so it slots straight into an agent stack instead of sitting next to it as a standalone app.
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Sponsored
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The AI notetaker that gets the hard words right
Your AI is only as good as what you feed it. Feed it a transcript with your product names, acronyms, and numbers spelled wrong, and you spend the afternoon hand-fixing the output.
Wispr Flow Notetaker uses your dictionary and calendar, so product names, acronyms, numbers, and uncommon names come out spelled right. It pops up when your meeting starts and captures Zoom, Google Meet, Teams, and Slack huddles with one click, no bot joining the call.
Then your meetings show up inside Claude or ChatGPT through the built-in connector. No copy paste. Try Notetaker free on Mac and Windows.
The Drops
RepoVoiceStudio
65.8k stars · debpalash/VoiceStudio
Open-source, fully-local alternative to paid voice APIs: cloning, voice design, video dubbing, dictation, transcription, and audiobook creation across 646 languages.
Here is the real problem it solves. Every serious voice feature today assumes you'll ship your audio to someone else's server and pay per character or per minute for the privilege. VoiceStudio runs the whole pipeline, clone, dub, transcribe, on your own hardware, with a local API and MCP server so agents can call it directly instead of routing through a vendor.
Quick start: Install steps are in the README.
Catch: local workflows run on your hardware, but remote services are optional and usage analytics requires consent, worth checking the defaults before you flip them on.
AffiliateHubSpot
Before you build a voice pipeline or a GTM workflow file from scratch, it's worth knowing some of that plumbing already comes prebuilt inside the CRM you might already have open. HubSpot, a CRM with prebuilt AI agents that run on the customer record. A Customer Agent answers support, a Prospecting Agent researches and drafts outreach, a Data Agent cleans the records. The CRM underneath has a free tier; the agents are add-ons.
Use it for: putting support, prospecting and data-cleanup agents on the record your team already keeps.
We may earn a commission.
MCPgrowth.engineer
248 stars · GetBrew/growth-engineer
An open-source catalog of go-to-market tools and workflows, written as markdown files any agent can run, with a read-only MCP server attached.
Use it for: handing an agent a real outbound workflow, like a funding-signal play, without digging through a dozen vendor docs to find which endpoint does what.
Catch: it hands the agent the workflow file, you still need the underlying tool's credentials for each step.
RepoOpenDots
5.3k stars · CopilotKit/OpenDots
An open-source template for persistent AI coworkers, each with its own computer, that move between text, voice calls, and Slack.
Use it for: standing up an always-on agent that browses, drafts, and waits for your approval in chat before it saves anything, rather than a one-shot chatbot reply.
Catch: it's a starting template, not a hosted product. You run it yourself, and live conversations need CopilotKit's intelligence layer, hosted, local Docker, or a licensed self-hosted deploy.
RepoCoucou
5.2k stars · Louis-CFM/coucou
A tiny open-source notch companion for Mac (and top-of-screen on Windows/Linux) that watches your AI coding agent sessions live, now with an iPhone and Android companion app.
Use it for: approving Claude Code permissions from your notch or your phone without tabbing back into the terminal every time an agent needs a yes.
Catch: it's built around the notch and menu bar paradigm, so the desktop experience is Mac-first even though it now runs cross-platform.
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Start Here
Turn a pile of customer messages into the one change worth making
One prompt today instead of a how-to. It is one of ours, tested on ChatGPT and Claude. Copy it, paste it into the free app you already use, and fill in what the messages are, where they came from, and what you're actually hoping to learn from them.
What these are and where they came from: [WHAT THESE ARE]
What I am hoping to find out: [WHAT I WANT TO KNOW]
The messages:
[THE MESSAGES]
Give me, in this order:
1. Themes. Name each one in plain words, in the order of how many separate people raised it. Under each: how many people, and up to two quotes word for word out of what I pasted. Where you cannot tell whether two lines came from the same person, say so and count them as one.
2. Said quietly. Up to three things people described without naming, each with the words they used instead. Only where the words support it. If nothing in what I pasted supports one, say that nobody described a problem they did not name, and move on.
3. Where people disagreed. Two customers wanting opposite things, both quoted. If nobody contradicted anybody, say so.
4. The one change. The single thing I could change that touches the most themes, described by what it would do rather than how to do it. Say which themes it touches and which it leaves alone.
5. What is not in here. What I said I wanted to find out that these messages do not answer, and what I would have to ask to find it out.
Rules. Every quote is word for word from what I pasted. Do not tidy a quote, do not join two into one, and never write a sentence in a customer's voice that is not in front of you. Count only what is there. Each theme says how many separate people raised it, and one person may sit under two themes as long as the note says so. No theme's count may exceed the number of messages I pasted: on three messages that is three. If what I pasted supports fewer than three themes, give fewer and say how little you had to work with rather than splitting one complaint into three. If I wrote "no particular question", leave out sections 4 and 5 and stop after section 3.
The line that makes it work: "Sort it into what they are telling me, and add nothing they did not say." That single constraint is the whole prompt. Most people ask an AI to summarize feedback and get a tidy paragraph that flatters the data. This version forces it to count, quote, and admit what it can't answer, which is the only version of a summary you can actually act on.
TRY THIS: Open whatever has your last batch of customer emails, reviews, or support tickets, copy ten of them as-is, and run the prompt right now. You'll have themes ranked by how many people actually said them before your coffee's cold.
This is one of 100 in the AIgent prompt pack. The other 99, plus guided builds with Mike on video, are inside the AIgent membership, dropping this week.
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If sorting your own customers' words into the one change worth making is worth two minutes, a newsletter that sorts the week's AI tools into the ones worth your time might be worth a subscription. AI Chief, the newsletter on the AI tools worth your time rounds up the tools and breakthroughs that save you time so you stay sharp without reading everything yourself, free to subscribe. We may earn a commission. |
Frontier Signals
A merge rate going from 2,500 to over 30,000 changes a day forced Anthropic to move its monorepo off Git. They built and shipped an in-house version control system, Scion, plus a new code review surface and search layer, because standard developer infrastructure couldn't keep pace with autonomous coding. If your team's CI is already groaning under a handful of agents, this is the ceiling you're heading toward. (Anthropic)
Security researchers say the "agent goes rogue" narrative is a dodge. The real pattern is frontier labs shipping without basic security controls, then calling the resulting breach misalignment instead of a preventable bug. Worth remembering before you grant an agent write access you haven't audited. (CSO Online)
Anthropic is warning that small AI models could soon self-replicate across IoT devices, smart fridges and vacuums included. The company's own test found real obstacles to pulling it off today, but flagged a worm with no central point to shut down as a plausible next-generation threat. File this under "watch, don't panic yet." (Ars Technica)
AI models went from solving 2% to 35% of theory problems in physics, economics and statistics in two years, per new MIT research. That is frontier theory work, not a coding benchmark. If your moat is "this requires deep domain expertise," that moat is eroding faster than most roadmaps account for. (Wired)
AI-powered decompilation is quietly becoming a preservation tool and a threat to paid software at the same time. The technique letting hobbyists port old games to new hardware can also open-source a paid app against its maker's will. (Simon Willison)
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Before You Go
Reply and tell me what you're running VoiceStudio for, dubbing, dictation, or something stranger. I read every reply.
If today's prompt saved you from writing a feedback summary by hand, forward this to whoever owns your support inbox. They'll use it more than you will.
See you Friday.
Before you go: we started a room for people actually building with agents. Tell us what you want us to build next. Join the community →
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