PH热榜 | 2026-06-17

Congrats! Curious on how does Framer handle conflicts when the AI's design suggestions clash with existing component constraints?

Can branches be nested or is it limited to one level deep from the main published version?

what sets it apart from other website builders?

Love that Agents can design, write, and organize all in one place, but what guardrails exist to prevent the AI from accidentally breaking responsive layouts during automated edits?

The Branching feature is a game-changer. We're a small nonprofit team building our donor-facing platform and being able to try different page layouts without risking the live site is exactly what scrappy teams need. Congrats on the launch.

congrats on the launch. branching is the feature i didn't know i needed until now. letting teams explore without touching prod is the kind of thing that quietly unblocks a lot of back-and-forth. excited to see where the agent stuff goes inside the canvas.

So happy to see Framer launch their new version. Developers may feel differently, but as a designer, Framer is just so delightful and easy to use. Sure, there's a slight learning curve, but its overall UI and functionality is very similar to Figma, so once you get into it, it will start to click. In comparison, Webflow feels like using Geocities (reference for fellow elder millennials). Can't wait to start testing out and integrating the AI features into my sites.

Stunning update! Regarding the AI agents assisting with copy writing on the canvas—can we train the agent on an uploaded brand style guide or specific company voice data, or is it relying on standard, generic prompts for text generation?

The branching feature caught my eye. I build my own pages and the thing I always dread is testing variations without breaking what already works. Looking forward to trying this one.

Very interesting approach. Do you think AI website builders eventually become the primary interface, with designers acting more like editors and creative directors, or do you see them remaining productivity tools for experienced designers?

This is cool but how does it handle agent drift? Is there a design system page? Or best practice around this?

Congrats on the huge Framer 3.0 launch! Bringing AI Agents directly onto the canvas to help with layout organization and writing sounds like a massive workflow acceleration

Hey Product Hunt, Swytchcode CLI is live today! 🚀

Over the last year, we kept seeing the same pattern. Building AI agents was easy. Getting them to reliably execute actions in production was not.

Agents would call APIs with invalid payloads, fail because of auth issues, retry actions that shouldn't be retried, or break when an API changed. Debugging these failures quickly became a bigger problem than building the agent itself.

The agent wasn't the problem. The execution layer had zero protection.

That's why we built Swytchcode CLI.

Swytchcode sits between your AI agent and every API it calls.

1. Schema validation before every request. Field renames and breaking API changes don't silently break your agent.

2. Authentication handled. OAuth, API keys, and enterprise SSO without exposing credentials to the agent.

3. Idempotency guarantees so duplicate executions don't create duplicate outcomes.

4. Policy enforcement to keep agents operating within defined guardrails.

5. 2000+ APIs out of the box, including Stripe, GitHub, Slack, Resend, HubSpot, Notion, Jira, Twilio, OpenAI, Anthropic, Gemini, Binance and many more.

Works with Claude, Cursor, Copilot, Openclaw, Gemini, windsurf , Hermes agents. No rewrites. No new infrastructure.

We believe the next wave of AI products will be defined not by how well agents think, but by how reliably they execute in production.

Try it now:

npx swytchcode

We'd love feedback from AI engineers, agent builders, and anyone experimenting with agentic workflows.

Join our Discord community : https://discord.com/invite/zuSXSv5GWs

Explore the docs and get started : https://docs.swytchcode.com
Explore usecase examples: https://github.com/swytchcodehq

Congrats! Curious how does Swytchcode standardize idempotency handling when each API has wildly different native mechanisms or none at all?

Solid niche to own! Curious about the long tail: for the APIs in your 2000 with no native idempotency key, are you synthesizing one off a payload hash and deduping on your side? Overall, congrats on the launch!

Heyy, I love the Product direction here , breaking api changes silently killing priduction agents is in noght mare scenario beouse the llm just try to hallucinate a workaround if it gets a 400 error. Schema validation at the gate is the right way to handle this, congrats for CLI launch 👏

that’s a real pain point. awesome to see this evolution of the product

interesting product!

Hi Chaitrali, curious to know how you guys standardize idempotency handling when each external API has wildly different native mechanisms. great to see CLI launch

Really cool! Can I use this on my projects? Like instead of me writing this protection layer swytchcpde handles that

This is exactly the execution layer that's been missing from most agentic stacks. The fact that agents can now get schema validation, idempotency, and policy enforcement out of the box — without rewriting any logic — is a huge deal for anyone shipping AI products to production. The 2,000+ API coverage is impressive too. Congrats on the launch! 🚀

Quick question: how does Swytchcode handle rollback or compensation when a multi-step agent workflow partially fails mid-chain — for example, if step 3 of 5 hits a policy violation after steps 1 and 2 already executed?

Congrats on the launch. The direction makes sense: execution failures are usually boring plumbing until one creates a real business side effect.

I am curious about the multi-tenant edge. When the same agent pattern runs across different customer workspaces, do policies and credentials live per workspace, per user, or in the manifest?

This is going to be a game changer for devs work with tons of integrations. Congratulations with the launch guys. I will always support you.

Congrats on the launch! Great product!

Do you have approximate (or maybe case study specific) numbers on how much swytchcode saves money for AI agent builders or for end users?

For a community launch workflow, I’d test an agent that collects Discord feedback, opens GitHub issues, and sends follow-up emails without redoing auth plumbing. The .swytchcode folder as a project boundary makes sense, but I wonder about handoff between local dev and production. When deploying from a CLI-built agent, does Swytchcode provide a hosted runtime, or is it expected to ship inside our own worker/server?

Nice job! Need of the hour

the npx approach is the right call - being able to drop this into an existing agent setup without architectural rewrites is exactly how this kind of tooling should work. durable state across API calls is the piece most CLI tools get completely wrong. curious how conflict resolution works when two agents are hitting the same endpoint concurrently - that's usually where state layers fall apart in practice

Standardizing this layer of the stack for agents looks very promising. There is so much unseen functionality behind the scenes of these types of integrations that can become a huge challenge to manage.

Which integrations are you seeing in practice the most?

Congrats on the relaunch!

This is a strong framing: the agent is not the hard part, reliable execution is. In B2B workflows, policy enforcement often needs business context, not just API/schema context. Can Swytchcode scope policies by role or risk level, for example allowing an agent to update HubSpot freely but requiring approval before sending customer-facing messages or changing billing data?

The part I like here is treating execution as a separate reliability layer, not as prompt quality. In production agent work, retries, auth, idempotency, and policy are where the expensive failures hide.

The emphasis on idempotency and durable state is massive. In marketing automation, the absolute last thing you want is a glitch causing an agent to double-trigger an email sequence or webhook to a customer. How does Swytchcode handle those retry loops cleanly under the hood?

"The agent wasn't the problem, the execution layer had zero protection" is so true. I build voice agents that call tools mid-conversation, and the failures are almost never the model, they're retries firing twice or an API quietly changing its schema. Curious how you handle auth across 2,000+ APIs when the agent is acting on behalf of different end users, do you manage per-user OAuth tokens and refresh, or is it mostly single-account keys for now?

Hi Product Hunt — we're Charlie Labs and we built Daemons for software teams that are already using coding agents and discovering a second-order problem: faster code creation also creates more operational debt.

Daemons are persistent, role-scoped teammates that work across GitHub, Linear, Slack, and Sentry.

📜 Our thesis is simple: agents create work. Daemons do the rest.

How it works:

1. Teams define the roles and boundaries in Markdown.

2. Daemons then keep recurring loops moving — issue hygiene, docs and dependency maintenance, bug triage, CI repair, and follow-through — with reviewable PRs, issues, reports, escalations, fixes, etc.

3. Continue to improve the underlying Daemons with Charlie's help

We would especially value feedback from teams using coding agents today: which recurring engineering or operational loop is still falling between the cracks for you?

Most teams can run several daemons consistently on our free plan.

Start here: https://charlielabs.ai/

Love this framing. Coding agents have gotten good at creating work but not at shepherding everything that comes after (PR reviews, CI failures, stale issues). Do the daemons leave a comment and wait when the right action is ambiguous, or do they try to resolve it automatically? Congrats on the launch.

@Daemons by Charlie Labs This feels like a practical step beyond code generation , keeping the follow through work moving is where many teams still struggle .

Love the role-scoped approach. Clear boundaries plus persistent execution seems much more practical than adding another general-purpose agent.

The daemon model is clever here. Persistent watchers that accumulate context over time solve the state gap that one-shot agents miss. Building async coordination pipelines, you'll realize fast that handoffs degrade without a continuous observer. How do you handle conflicting writes when two daemons simultaneously target the same PR thread or Linear issue?

Finally someone tackling the operational hangover. Free plan means no excuse not to try it.

In my experience the operational debt quietly stacks up behind the create step but everyone's still optimizing that create step. How's the aggressiveness dial? The docs-drift deciding when to shut up is the hard one. Is that threshold hand-tuned in your md.file? Congrats with the launch!

Liked the approach of "operational hangover" created by coding agents. My concern or rather a query is; as organizations will deploy dozens of specialized daemons, does the coordination cost between daemons become the next bottleneck? In other words, who manages the managers? thoughts on that ?

Strong thesis. Most teams are focused on code creation, not the maintenance burden that comes after.

With persistent teammates working across GitHub, Linear, Slack, and Sentry simultaneously, how does the system maintain state consistency when the same issue gets updated in multiple platforms at once?

Just ran the terminal prompt—under 60 secs is no joke. Agent replied on Teams and held context when I responded. Solid.

I like the role-scoped teammate framing. This feels close to the real future of agents: not one-off prompts, but recurring responsibilities with boundaries and reviewable output. How are you measuring daemon performance over time, fewer stale PRs, faster CI recovery, fewer ignored issues, or something closer to an “owner” score for each role?

The useful framing is not “AI writes code.” It is that unresolved operational queues finally have a worker with context and memory. PRs, issues, CI, and docs only get safer if the daemon is constrained by explicit runbooks and review gates.

I like that Daemons by Charlie Labs focuses on a specific workflow instead of trying to be a broad all-in-one tool. The part I would want to understand better is the first-time setup: how quickly can a small team get from a blank workspace to a useful result?

the 'agents create work' framing is spot on. every team I've seen go heavy on coding agents ends up drowning in the review/triage overhead nobody planned for. curious how you handle the trust question — do teams typically start with daemons on low-stakes repos first, or jump straight in?

Amazing! I have tinkered with self maintaining docs earlier and this looks like a much cleaner way to give more control on when the tasks are invoked. I am assuming teams could choose to make them a CI/CD gate or choose to do retrospective cleanup? Can they be customized beyond the .md to run custom scripts etc?

the "after coding agents create it" framing is exactly right, that's the gap most teams feel but can't articulate yet. curious how Daemons handles CI failures that are flaky vs actually broken by the agent's changes, that's usually where async signal gets noisy and the daemon would need to know the difference to avoid spamming reviewers. congrats on the launch.

Congrats on the launch. The bit I’d watch is not only when a daemon should act, but how it proves the loop is actually done.

For CI/docs/issue cleanup, do you store a small receipt of trigger, context, action taken, and verification result, or is that mostly visible in the GitHub/Linear trail?

Love the name.

"Agents create work, daemons do the rest" is a sharp framing. To answer your question: the loop that falls between the cracks for me as a solo builder isn't code creation, it's keeping things alive after they ship, dependency and cert renewals, a deployed service that silently dies overnight, the small maintenance no one schedules. Curious how you set the autonomy boundary: how do you decide what a daemon fixes on its own versus what it just flags for a human to approve?

The "agents create work, Daemons do the rest" thesis is spot on — it tackles the second-order problem that most teams don't see coming until they're drowning in stale PRs and ignored CI failures. Defining daemon roles in plain Markdown is a smart choice too; it keeps behavior reviewable and version-controlled. Congrats on the launch! 👏

Curious: as teams scale up to many daemons running in parallel, how do you prevent alert fatigue? Is there a way to set a "quiet hours" policy or prioritize which daemons get to surface updates vs. just silently act?

Hi Product Hunt!

We built Quartz because our own inboxes had become impossible to keep up with.

AI made it easier than ever to send emails at scale. We think AI should also help people defend their inboxes from that noise.

Quartz is an AI-native email app that protects your focus and helps you get through email faster. It learns your style and preferences over time, so it gets better the more you use it.

And because email is private, Quartz runs entirely on your device. Your emails are not sent to AI providers.

Excited to share it with you today. We’re currently in public beta and free to use.

We’d love to hear what you think!

Running the AI locally and keeping emails end-to-end encrypted is the right call — most people don't realize how much of their inbox ends up on third-party servers. The "learns your voice" for drafts is the feature I'm most curious about.

How long does it take for Quartz to actually learn your writing style — is it noticeable after a few replies or does it take weeks?

Hey folks, I'm really excited to try out some fresh email AI innovations -- most providers feel boring and don’t do what I need. Let's rock!

How does the filtering work? This would be extremely useful if it had some learning mechanism that delivered personalized results.

We just shipped v0.1.84 and it's a nice mix of "finally" fixes and quality-of-life polish. A few highlights:

🔗 Links in plain-text emails are now tappable. Bare web addresses in plain-text messages are live, clickable links now — no more copy-pasting URLs into your browser. Just tap and go.

🍎 Sign-in is reliable again on older macOS. Connecting your account could crash on macOS 14.0–14.3. That's fixed, so sign-in works no matter which version you're on.

Plus a round of refinements:

• Recipient names with commas or quotation marks now display correctly — no more split-up addresses or stray escaped quotes in recipient chips.

• Draft with AI now has a clear submit button, so it's obvious how to send your prompt.

• Settings panels share consistent, polished typography for a cleaner, more cohesive feel.

• The Telemetry panel shows your analytics ID as a read-only field — handy for privacy checks and support.

Appreciate not having to add yet another service to the chain just to get the AI-powered goodies in the email client. Local LLM is the way. Congrats on the launch! 🚀

Whoa, this looks really slick! Big kudos on making the AI fully local, too 👍👍👍 I might actually stand a chance at processing my 5k unreads 🤔

the 'drafts in your own voice' bit locally is what i'd watch — no per-user training step means few-shot on your sent mail, so the voice match lives or dies on which examples get picked.

Been dreaming about this for a while but for comms more broadly: telegram, whatsapp, etc. I think Eric (former YC partner) tried this. Good luck!

Congrats on the launch! This tool would definitely make my life easier. Does it support adding multiple emails/domains, to tackle everything at once?

Our changelog for today so far

It looks like there is a chance I'll finally start reading my emails :D

Really interesting local first approach. Just curious, which model(s) are you running locally?
Also, can I define any custom categories? Like emails about credit card transactions or UPI payments?

Very excited to try this out! Would that send a push notification when an email is very important so I can respond asap?

Hey, congrats with the launch! What's your vision on future pricing? Downloading and testing the app anyway 💪

Local first AI on Tauri for inherently private data (email here, but the pattern generalizes to trading, health, code) is the architectural answer to "I want AI but not in the cloud." The hardest part isn't the model. It's the bundling and update story. How are you handling the Gemma 4 E4B model size in the Tauri bundle, shipping it bundled, downloading on first launch, or external dependency? And how do you handle model updates without re-downloading the entire 4GB+ weight file each time?

The "learn from sent emails in this thread first, then to same person, then others" hierarchy is a smart loop. I'd be curious what happens for users with very short reply history. Does the model fall back to a base "professional but warm" voice, or does it just produce neutral drafts until enough signal accumulates? The cold-start problem is the part most local-first AI tools handle poorly.

Congrats on the launch.

Great project! You mentioned how cold emails create clutter and this tools helps dealing with that.

Do you think we can expand this into agent2agent communication? Like both sides essentially have AI messaging each other and if things make sense, the issue gets escalated to humans.

One of the reasons we treat cold emails as spam is because there are so many of them. However, if there is a proper processing layer, I actually do wish people to reach out to me and let me know how they can bring value.

Any plans for Windows anytime soon?

Local-on-Mac with Gemma on-device is a great privacy angle, that's exactly why I run my own AI tools on my own machine too. One thing I haven't seen asked: since the model runs on the Mac, what happens to sorting and drafts when the laptop is asleep or closed? Does it catch up the moment you reopen it, or do you need it awake to keep processing? Congrats on the launch.

Focus and privacy in the same product is rare for an email client. Does it handle multiple accounts in one inbox?

Local-first is the right instinct for email agents. The hard part is less summarization and more trust: what can act, what only drafts, and how quickly a user can audit why something happened.

Hi! 🚀 🚀🚀

Congrats on the launch! Looking forward to seeing how this grows.

An email product built around focus! I love that:)

Is there a way to identify which emails are important besides manually marking them myself?

How about integrating them with office emails? Mostly office emails consist of 1000+ unread emails, which needs sorting and prioritizing. Any idea how we can integrate with office emails?

Hi everyone!

Android 17 puts apps closer to the agent layer.

With AppFunctions, an app can expose its own actions as local tools for Android MCP. @Gemini and other assistants can discover those actions and run workflows with access to the app’s local state.

The UI still matters, but the app’s core capabilities can now become callable system-level tools.

It also changes the baseline for app design. Developers now have to assume their apps may run across phones, tablets, foldables, desktop windows, floating bubbles, and handoff surfaces, and @Google is pushing Compose as the default way to build for that world.

the AppFunctions story is interesting but feels like it'll fragment badly in practice - every app defining its own tools means discoverability just becomes chaos at scale. iOS shortcuts went through this exact problem and it never really resolved. also the multi-surface adaptive layout thing has been 'coming soon' since the first foldables launched. show me one concrete use case that only works because of this specific architecture and i'll be more convinced

AppFunctions and Android MCP are the most interesting parts here. If apps can expose real local actions to assistants, Android starts feeling less like a launcher and more like an agent-ready platform.

Thant Awesome! Can't wait to try it

Love the framing of "missions" instead of chores — that reframe alone makes it way less overwhelming for ADHD brains. The room/time/energy context is a smart touch too.

Do shared households get separate profiles per person, or is the task list shared across everyone?

Hey Product Hunt 👋

We built Dopami because we kept asking the same question: why does TikTok know exactly when to grab my attention, but my to-do list doesn't?

The answer is behavioral algorithms. TikTok learns your habits, your active windows, your patterns and serves content at the exact moment you'll engage. It works flawlessly. The problem is it works against you.

We built the same engine. But instead of serving you a Reel, it surfaces the right chore at the right moment.

Here's what that means in practice:

No alarms to set. No rigid routines to maintain.
Dopami observes when you open the app, which missions you complete, in what order, at what time.
The more you use it, the more precisely it knows when to nudge you not with a generic reminder, but with a specific mission calibrated to your energy right now.
The rest of the product:

Chores organized by room → zero decision fatigue
Every task earns XP, unlocks levels and trophies → your brain gets the dopamine hit it needs
Due dates feed the algorithm → deadlines drive priority automatically
Up to 6 household members → everyone sees what needs to be done, not just you
Dark-mode-first design → built to calm, not overwhelm
Who it's for: Adults with ADHD, parents managing households, roommates who are tired of the mental load falling on one person.

Where we are: Currently in closed beta free while we learn. Launching at $9.99/month with a 30-day free trial.

We're two founders one ADHD, one not which means the product gets stress-tested from both sides every single day.

If you've ever stared at a pile of dishes for three days knowing you needed to do them but couldn't start: this is for you.

Would love your questions and feedback. We read everything. 🧠

Nathan & Néo, co-founders of Dopami

Such a cute mascot that a chore will feel more like a game :)

Not sure it would actually get me to do the chores but looks fun!

Love the concept! Quick question — does Dopami also help with scheduling tasks and sending reminders/notifications if we forget to complete them?

The mental load framing is the part that gets me. It isn't the chores themselves, it's the constant background tracking of them.

would be better if you add your x handle on the website

Android or iOS?

We are glad that you like the application so much; feel free to invite as many people as possible to increase your chances of winning a free plush toy :)

We're doing something a little unhinged to celebrate our launch here

We just opened a waitlist lottery the more people you invite, the higher you climb, and the better your prizes.

Top spots win exclusive Dopami Founder Packs: early beta access, limited mascot collectibles, and a lifetime head start before we go public.

It's exactly the kind of mission your ADHD brain will actually want to complete.

https://www.do-pami.com/beta/

Every person you bring in = one more entry. The leaderboard is live. Go. 🧠⚡

Hey Product Hunt 👋

I'm Mansehej, the maker of Tapfree.

I built Tapfree for Chrome because typing on the web, especially on my Chromebook felt really clunky. When you're moving fast, your ideas don't arrive as perfect sentences. They come as fragments, quick reactions, and rough thoughts you need to shape into something coherent.

Most dictation tools don't help much. They transcribe words literally, miss context, butcher names, and leave you fixing formatting by hand. Writing an email, a chat reply, or a document all need very different handling. They also struggle with touch support, failing to provide a well integrated user experience.

What makes Tapfree different is how it understands context. Tapfree uses the webpage context, not just the tab you're in, to produce cleaner, more relevant dictation. It subtly appears itself in the text fields you need it the most, without disrupting your flow.

It also handles the way people actually talk. You say "Could you get some coffee... sorry, tea on the way back?" and Tapfree writes: "Could you get some tea on the way back?". It catches your corrections mid-sentence so you don't have to go back and fix them.

Tapfree also works natively, system-wide on ChromeOS.

If you give it a try, I'd love specific feedback:

How do you feel about the "there when you need it" approach to integrating into the text field?
Any "wow" moments with the context understanding?
What would make it even more useful for you?

Thanks so much for checking it out!

Feedback from this community means the world to a solo builder! 🙏

- Mansehej

Does it support Chromium based browsers like Dia?

Awesome product! Tried a bunch of things like this but not really clicked with any of them. This applies page context more intelligently, and doesn't change what I'm trying to say like a lot of the alternatives. Sometimes I'll look at a Wispr flow dictation and wonder how on earth it arrived at the transcription, but Tapfree consistently captures the intention of what I'm trying to say.

Interesting one! How does it decide a phrase was a retraction vs me thinking out loud? Did you tune that toward catching every correction?

Does this mean I can dictate in linux apps on my Chromebook?

What's the privacy policy like? Do you store the context anywhere?

Voice dictation that actually reads the screen context is a game changer — so tired of dictation tools that have no idea what you're working on. This feels like the missing piece for hands-free productivity.

Does it work across all websites or only specific ones? Curious if it handles things like coding environments or doc editors well.

solo built chrome extensions reading text fields across every site is exactly the kind of thing that needs tight permission scoping, since youre potentially sitting close to password fields and forms. congrats on the launch, just make sure the extension isnt grabbing more than it needs to

With the move to desktop browsers, did you add global keyboard shortcuts to trigger the dictation without needing to click the injected mic?

Yeah! Love this kind of solutions focused on save time on our daily routine. Voice dictation can change our performance and I'm sure many founders gonna take the most of it. All the best!!

Congrats on bringing Tapfree to Android 🎉 Excited to see how this makes everyday tasks smoother, wishing the team big success ahead!

Does it work with touchscreens?

The "repo as harness" idea is clever — giving agents durable context instead of a fresh chat window every time is exactly what long-horizon tasks need. Context drift is probably the #1 reason agent work falls apart mid-task.

Is the plan file something you generate once and manually update, or does it evolve automatically as the codebase changes?

How do you keep the plan from getting stale as humans change the codebase between runs?

"Context matters more than the model" is the lesson it took me a year of vibe coding to actually believe. My best and worst sessions use the same model... the difference is whether I handed it a real plan or just vibes. The part I still fight is drift, the agent quietly wandering off the plan three steps in. Does Deep Work Plan keep checking the work back against the plan, or is the plan mostly an upfront thing?

spec-written-into-the-repo is the right model - a persistent plan that survives context resets and that any agent can pick up is fundamentally different from a prompt you're manually re-feeding each session. the acceptance criteria + validation gates combo is the piece most agent frameworks don't bother with. curious how it handles cases where the atomic tasks turn out to be wrong mid-run - can you edit and resume without blowing the state?

Writing the plan into the repo rather than the context window is the right architecture. Durable state that survives model swaps and context resets is what makes long multi-step tasks actually viable. The validation gate pattern catches drift before it compounds. How are the gates implemented? Are they executable assertions the agent runs itself, or do they require human sign-off?

Finally, something where you don't have to go through seven circles of hell just to sign up!

This solves a real pain for creators — recording once and getting both formats natively is way better than cropping after the fact. The quality always suffers when you crop.

Does it split the feeds in post or actually record two separate video files simultaneously?

I like that Dualora fixes this while recording, not after. Seeing both 16:9 and 9:16 live on screen feels much more practical than guessing and hoping the crop will work later.

Curious if you plan to add safe-zone guides for captions, UI overlays, or platform-specific crops in the future?

As a content creator this definitely caught my eye. It truly is a struggle finding a way to use landscape video as short form content as well. I can't wait to try this one out!

Why didn't i know Your app during recording my tutorials :( I did double job.

Is Figma required? Where I struggle with design systems in AI-native development is maintaining and verifying against a single source of truth.

Love the vision of an AI that understands your patterns and taste. I wonder how does memoire actually learn and quantify something as subjective as a designer's aesthetic preferences over time?

Routing multiple agents against the same Figma source is the right call. Text specs drift from design intent the moment a file changes. It's a translation layer that doesn't survive iteration. When Claude and Codex generate diverging implementations from the same component spec, how do you surface and resolve those conflicts?

Hey Product Hunt 👋

I'm Charlie, and Typerino is the screenwriting and playwriting app I wanted and couldn't find.
I love the craft and I've spent a lot of time inside the existing tools. I've spent my career as a software designer & builder, so naturally I built my own.

The writing engine is designed from the ground up around a single goal: that it should feel great and look great. Typing should feel crisp and delightful. No perceptible delay between thought and word on the page, even in a feature-length script. Industry-standard formatting is there, the writing surface is clean and quiet, and it runs natively on both Mac and Windows.

I'm calling this 1.0, but I think of it the way screenwriters think of a first draft — the thing you ship so you can start making it better. It's not everything I want it to be yet. It is something I trust you to write in. I'll be patching and adding fast, and I'd genuinely love your notes on what to sharpen next.

Easiest way to feel the difference: download it, open a blank script, and just type for thirty seconds.

This is so nicely designed. Have you thought about making themes or ereader export?

This looks really promising! I've already started to import my scripts from StudioBinder to keep working Typerino!

The “just type for thirty seconds” point is a good way to frame it. For writing tools, speed and feel matter as much as features, especially when someone is working on a long script.

I am sure Typerino is a great product, just curious what makes it better than celtx or other tools? I have used Celtx for a couple of stage play scripts a few years ago.

I miss the early days of social apps when they were mostly about keeping up with people you actually knew. Curious to see how this evolves.

Genuinely refreshing to see a social app built around mutual connections and no public likes. Most attempts at "calm" social media still sneak in engagement mechanics. The European privacy angle + no data selling is a strong differentiator too.

How do you handle discovery on Mirlo — if there's no algorithm, how do new users find people they'd actually want to connect with?

I'm from India and I'm really excited to try this out one day. I was an early Instagram user back when it was just about sharing photos before everything got so toxic. I really miss that simplicity and I hope Mirlo can bring it back, good luck!

Great initiative. A social media network that focuses on the ‘social’. I’ve installed the app and will try to get my friends use it!

こんにちは。リリースおめでとうございます。
わたしも少しだけ近い思想でSNSを構築しているので興味が湧きました。
実際にどのように他の人と繋がるのですか？すでに知っている知人同士のコミュニティとなるのでしょうか？
インスタグラムのDM機能だけを切り取ったようなアプリなのでしょうか。
お時間があれば教えていただけると嬉しいです。ありがとうございます。

the "mutual connections only" detail is the one that actually makes this different. every other "anti-algorithm" app still has public replies or likes, which just recreates the performance anxiety in a slightly quieter room. curious how you handle the cold start problem though, since that mutual-only constraint means it's pretty hard to find anyone until you already know someone on it.

Super useful for creators who want to stay brand-safe without manually hunting down every slip. The mouth blur on top of the bleep is a nice touch — covers both audio and video platforms.

Does it handle different languages or is it English-only for now?

This solves a real headache for creators who post across multiple platforms with different content policies. Manual bleeping is tedious and easy to miss. Curious how it handles context — some words are fine in one setting and not another. Does it let you customize the word list or is it one-size-fits-all? Congrats on the launch!

For audio/video tools, the edge cases are usually timeline alignment and review speed, not just detection accuracy. A profanity censor that stays frame-accurate and easy to audit is much more valuable than one that is merely clever.

This looks genuinely useful for creators and editors who spend way too much time on repetitive cleanup work. One thing I'd be curious about is how accurate the detection is across different accents and speaking styles.

Hi everyone!

After 38 years, Wolfram Language 15 is still adding real core functionality.

Stephen frames Wolfram Language this way:

something beyond a programming language—it’s a full-scale computational language... intended not just to be written by humans, but also to be read by them, as a way to help formalize and crispen up their thoughts.

In his view, when AI generates Wolfram Language code, the value is that it shows “in precise terms” what the AI understood — something humans can inspect, run, and trust.

Hi everyone, I'm Fabian, co-founder at ai-coustics.
The launch page covers very well what our newest product does but let me add here why we built it.

Voice agents are moving into the real world, where audio is messy: think cars, call centers, kitchens, noisy streets. And in the real world they fail in ways the transcript never shows. Especially competing voices - like a TV in the background or a far-field speaker - and artifacts like packet loss on a bad connection can throw off agent's performance. Teams see the bad outcome but have no idea the cause was audio. That blind spot is where trust in production voice AI breaks down.

Tyto (Audio Insight) is the solution for that blind spot. It analyses the input audio and scores it: how noisy, how reverberant, how much interfering speech, how likely the agent is to mishear. It's a signal you can actually act on.
It works in two modes: real-time monitoring so you catch failing calls as they happen or adjust the agent flow, and post-call analysis so you can finally answer what went wrong. And it runs on the same on-device ai-coustics SDK that's already shipped in production by voice AI teams.

Easiest way to feel it: point Tyto at a recording of one of your worst calls and watch it highlight exactly where the audio fell apart. Full write-up here. Link to documentation here.

We built this for the people shipping voice agents into hard environments. Tell us what's missing, we're reading every comment. 🙌

Hey hey, Mila from ai-coustics here - I'm looking forward to seeing what you all think!

If you want to try it in your own infrastructure right away, you can get your SDK key here 😊
You can find full docs here: https://docs.ai-coustics.com/

Congrats on the launch! I'm curious what specific agent flow adjustments can Tyto trigger automatically when it detects interfering speech mid-conversation?

It basically feels like the Voice AI agents are not deaf anymore! I think there was some degree of the Audio Intelligence in some of the STT engines such as understanding certain sounds etc but the acoustics awareness is a whole new level!

For anyone who wants to try this hands-on: we’ve open-sourced the demo agent codebase so you can run it yourself or see how to integrate it into your own voice agent setup. Check it out here: [link]

Looks great! Does running on-device add latency to the live call, or is the scoring free?

This is a useful blind spot to solve. In sales and support voice agents, transcripts often hide the real reason trust broke down. Do you see Tyto feeding a live confidence/risk signal into the agent policy, like switching to confirmation mode, slowing down, or escalating to a human when audio quality crosses a threshold?

Hey Product Hunt 👋

I'm Cole, founder and CEO of Locus

I started Locus because of a frustration I couldn't shake: the hardest part of starting a business isn't the idea, it's everything between the idea and a live business that actually takes money. Domain, landing page, payments, brand, ads, outreach, and finding the first customers. I watched so many good ideas die in that gap, including a few of my own.

So we built Locus Founder. It's an AI agent you talk to like a cofounder. You text it an idea, and it does the real work:

🧠 Interviews you about your audience and taste first, so you never get a generic template; every business is 1 of 1.
🛠️ Ships a real full-stack app with auth, a database, and payments
💳 Wires up Stripe so you can take money on day one
🎨 Builds and publishes your brand, ad creatives, and cold outreach
🤖 Then runs in the background and only pings you when it needs a decision or a spend approval

The thing I'm proudest of: you can run the whole thing from your phone over text, before you even make an account.

It's live today. Text your idea and watch it work live at locusfounder.com.

We're still early, and the feedback of this community means a lot to me, especially on the onboarding. What would it take for you to trust an agent to build and run a business for you?

Super excited for this launch!

The tool I wish I had back in high school. Super excited to take everyone from idea to first sale as fast as we can!

What kinds of decisions does it ask you to approve most often, like ad spend and pricing or product changes?

An interesting concept. I'd be curious to know what level of control and approval I have before it starts making decisions or spending money. Congrats on the launch!

Finally, builts an agent that actually does the grunt work instead of just handing me another generic to-do list. Love this. @cole_dermott

great product!

Congrats with the launch!

ClipDone looks solid, good job! The only thing I can dream of is pay-per-clip pricing. I don't usually need to edit videos every month but I need it ocassionally. So I would be happy to pay 15$ per video instead of having a subscription.

$2,195 for a stand-alone face computer.

Wall Street doesn't like it, even though Lens Studio now has MCP for devs!

For me, the most useful part would probably be catching quiet changes: a subscription going up, a weird duplicate charge, or something I forgot I was still paying for. That feels more realistic than expecting people to manage a full personal finance dashboard every week.

The partner flow is also smart. A lot of money questions are not really budgeting questions, they are just “hey, do you know what this was?”

Curious how Cilantro decides what is actually worth surfacing. Does the user train it over time by dismissing/confirming alerts, or is it mostly automatic from transaction patterns?

Congrats on the launch! Can you attach receipts to your transactions?

I had fun playing with it ❤️

How do you generate samples? What AI do you use?