PH热榜 | 2026-07-06

@granthan Congratulations

@granthan Congrats on launching AnySearch — search infrastructure that agents and developers can actually trust is a real need, and the positioning is sharp. We made you a free launch video for it (below), yours to download or re-post anywhere, no strings. I suggest adding it to your launch page in here; launches with video tend to do better than those without.

We built it with FoxPlug: paste your site and it turns what you just shipped into a launch video, images, GIFs and posts in about 30 seconds. This one is on us — make your own free at https://foxplug.com

https://www.youtube.com/watch?v=opfrqlxS23A

@emir_citak Thanks for your recognition. We adopt different update strategies for various vertical search areas in our self-built sources. Welcome to experience.

@emir_citak Glad you appreciated the hard benchmarks—we're tired of vague marketing fluff too! 🤝

To your question: you nailed it, the caching is absolutely domain-specific. Our Hierarchical Routing applies dynamic TTLs based on the vertical. Fast-moving data (like live finance) hits real-time feeds directly, while deep-research domains (like academic/legal) rely on specialized caching layers.

That’s exactly how we balance deep retrieval while keeping our overall latency incredibly low!

@fberrez1 The structured content fed back to the agent by AnySearch is in Markdown format, with a single core objective: the search results should be directly used by Agents. This means that the returned context is clean, comes with precise citations, and the agent can infer upon receiving it, rather than spending hundreds of tokens guessing first.

@fberrez1 Spot on—these are arguably the two biggest bottlenecks for agent builders right now!

1. On the "Structured" output: Currently, AnySearch infers the structure and returns Entity-Enriched Markdown (cleanly separating core facts, citations, and metadata). We standardize this to drastically reduce LLM cognitive load, giving your agent a reliable format without needing a heavy validation step. That said, letting developers pass strict JSON schemas is a fantastic idea, and we’re actively exploring it for our roadmap.

2. On aggressive anti-bot blocking: You're absolutely right—generic scraping fails when you need fresh data the most. We solve this structurally: rather than fighting Cloudflare as a headless browser, our Smart Intent Routing bypasses this entirely by tapping into directly integrated, authoritative vertical feeds (finance, health, cyber, etc.).

Really appreciate you digging into the architecture!"

@fberrez1 We don’t try to solve challenges, we just try not to trigger them in the first place, which gets us a lot further than standard crawlers in practice. By structured, I just mean a consistent markdown format (title, url, context) that works well for agents, plus a JSON API if you want actual structured data on the developer side.

@chilarai AnySearch features self data sources, covering both general and vertical search.

@chilarai Thanks! Short answer: AnySearch isn’t just one static index with a single “updated every X hours” schedule.

We route each query to the best source mix for the intent: live web, vertical sources like academic/legal/security/finance/code, and direct URL extraction when the agent needs to inspect a page. For freshness, it depends on the source: web and page extraction are queried live, while vertical sources follow the update cadence of the underlying data provider.

We also return source attribution and metadata where available, so agents can cite the source instead of treating the result as a black box.

@akbar_b Thanks! To answer both:

Structured output: we have a fixed schema per result (title, url, context) in markdown, plus a JSON API for full structured data. The schema is consistent, so your agent can parse reliably without per-query shaping.

Latency: p50 is ~1s, p95 under 5s. For a multi-step agent loop, I'd budget 5-8s per call to be safe. We're actively working on bringing p95 down.

@rnagulapalle 

Thank you for the thoughtful comment — really sharp questions.

Improving the information density of AI Search results is genuinely one of our core objective functions. On the deduplication front, our approach falls into two categories:

1. URL-level dedup. Straightforward — if the same URL is recalled multiple times, we deduplicate at that layer.

2. Information-density ranking (this is the important one). The real challenge isn't URL duplication — it's exactly what you described: different sources reporting the same story with different phrasing but near-zero marginal information gain. To address this, we've built our own information-density ranking algorithm. For multi-intent queries, rather than optimizing purely for relevance, we optimize for maximizing information density when organizing the final result set. This involves jointly accounting for relevance, cross-passage redundancy, information entropy, and a corresponding length penalty — all to ensure that every token the user consumes delivers the largest possible information set, rather than having the same story rehashed three different ways.

As for the dynamic trust problem you raised — when an "authoritative source" gets breaking news wrong — you've called out a genuinely hard one. We're actively researching dynamic trust mechanisms for this, but honestly, it's very difficult to strike the right balance across quality, latency, and cost. We're committed to solving it and plan to roll out improvements in future releases.

Thanks again for the engagement!

@hazy0 Context bloat and duplication are exactly what kill agent reasoning—spot on.

To answer your question: Yes, you can absolutely scope it. We built Private Capability Isolation (currently Enterprise-only) specifically for this use case.

While the global routing is amazing for open-ended research, for a customer-facing support bot, you can pin the search strictly to your own docs or a whitelisted set of domains. We completely agree with you—having that hard boundary is non-negotiable for production safety.

@krekeltronics Good point on avoiding 'false certainty' in agent reasoning.

We currently use Entity Enrichment to separate raw facts from citations to preserve provenance. However, explicitly exposing 'freshness' and 'failure states' as first-class fields is an interesting angle to help agents reason better about the data quality.

We'll definitely consider this as we refine our API. Thanks for the feedback!

@sezerdasekwcwb Great question.

AnySearch does not use one fixed “trusted source” whitelist. Trust is query-dependent.

For each query, we rank sources based on signals like relevance, source authority, freshness, content type, domain fit, and vertical context. A trusted source for financial data may be very different from one for academic papers, legal research, or developer documentation.

Developers can also constrain or bias retrieval toward specific domains, sites, verticals, or source types when those sources are already covered or publicly accessible.

For new sites, private sources, or domains that are not yet covered, tell us the use case and target source. We can evaluate the best way to support it as a custom or approved source.

So the default is query-aware source selection, while developers can still enforce their own provenance policy when needed.

@lz_lin AnySearch isn't a flashy skill, it's foundational. Without clean, verified context, every downstream reasoning step is built on sand. Appreciate you seeing the deeper point here!

@lz_lin Couldn’t agree more. Better agents need better inputs first. That’s a big part of why we built AnySearch — to help agents work with more reliable information before they start reasoning or acting. Thanks for putting it so clearly.

@azatv0rh Thank you for support, AnySearch is so necessary for agents.

@madalina_barbu Thanks, Visit Website for more info

@charlenechen_123 Thanks for comment. We have resolved these issues through algorithms, I think the content in the Gallery can answer your question.

@charlenechen_123 Thank you! And yes, that’s one of the core problems we’re trying to solve.

We don’t rely on ranking alone, because high-ranking does not always mean high-quality. AnySearch looks at a mix of signals: source type, originality, freshness, relevance, duplication patterns, and whether other credible sources support or contradict the same claim.

A big part of the work is reducing obvious noise: ads, SEO farms, repeated copies, and pages that look optimized for ranking rather than usefulness. But we also try not to over-filter, because sometimes a niche source can be valuable even if it is not a big authority.

So the goal is not “hide everything except one perfect answer.” It’s to give agents cleaner, structured evidence with attribution and confidence signals, so they can reason from better inputs and still know where the information came from.

@sabber_ahamed The structured content AnySearch provides is in Markdown format, which can be directly used by Agents. Existing search is designed for human browsing, that's why Agents cannot browse and make decisions like humans. AnySearch is designed to address this issue.

@ridhwikvinod Thanks, and totally agree with that distinction — “trusted by the tool” is not always the same as “trusted by your workflow.”

Yes, the goal is to let developers control source policy per query.

For new domains, private sources, or sources that are not yet covered, share the use case and target sources with us. We can evaluate the best way to support them as custom or approved sources.

Default ranking is useful when developers do not want to manage source selection manually, but when you already have your own trusted source list, your policy should take priority.

@conduit_design 
Appreciate the question! Honestly, the best way to see the difference is to try it out yourself — we built AnySearch to be as easy to use as possible. Visit the official website and register an account to obtain more free search credits. We look forward to your feedback.

@conduit_design Fair question. Parallel looks like a strong product, so I’d frame it less as “better in every case” and more as a different focus.

Parallel seems very strong around open-web search, extraction, and deep research workflows. With AnySearch, we’re focusing on being a broader retrieval layer for agents: web search, vertical sources, URL extraction, and agent-native integrations like APIs, MCP, and Skills, with source attribution and metadata that agents can carry through their workflow.

So if your use case is pure web research, I’d honestly benchmark both. If you want one pluggable search layer that fits into different agent workflows and source types, that’s where we think AnySearch becomes useful.

@conduit_design Heya, great question.

I’d frame the difference more around use case than “better or worse.” AnySearch is built as an agent-native search infrastructure layer that developers can plug into their own agents and products.

AnySearch can be called directly through MCP, Skill, and API, returns structured results, and routes across both general web and vertical sources like finance, academic, legal, business, code, health, patents, and more.

We also put a lot of emphasis on developer control, including source constraints, domain-level policies, provenance, and privacy-friendly usage.

The best way to compare is to try both with your own agent workflow and queries. We’d love for you to test AnySearch directly and see where it fits better for your use case.

@lesley_liu2 Try it, I look forward to your feedback.

@nicole_h94 definitely

@nicole_h94 Yep! AnySearch uses its retrieval and ranking pipeline to filter out low-quality, duplicate, and SEO-heavy content.

@mihriban1537007 I strongly agree that traceability is the core of trust. People won't be satisfied with "we searched", but rather need to see the real verification of every piece of information. Enabling agents to point out "this conclusion comes from here" is itself a key difference in product experience.

@song_kirby Completely agree, the search layer is truly important for agent.

@song_kirby Exactly. A smart agent with messy inputs still ends up doing messy work.

That’s why we care so much about retrieval quality, structure, deduplication, freshness, and attribution. The goal is not to make the agent “think harder,” but to give it cleaner context so it can reason with less noise from the start.

@alstonzhuang Thank you. As inputs, AnySearch is really useful.

@alstonzhuang Exactly. That’s the idea.

We don’t think search infrastructure should be the agent, or pretend to do all the reasoning. It should give the agent cleaner, fresher, better-attributed inputs so the agent can make better decisions.

Better ingredients, better cooking.

@masato_furuno1 Data from different sources perform variations in format. By transforming them into structured contents that can be used by Agents, and by sinking the tasks of cleaning, and filtering to the infra layer, we make the data Agents receive is clean, referenced, and directly inferable.

@reda_roqai_chaoui That’s exactly the balance we care about.

We don’t treat trust as a hard whitelist where everything else gets removed. Instead, we look at signals like source type, originality, freshness, relevance, duplication patterns, and whether other credible sources support or contradict it.

The goal is to reduce obvious noise like ads, SEO copies, and low-value duplicates, while still keeping useful edge-case information visible with context. So instead of “trusted or deleted,” it’s more like “useful evidence, with the right confidence and attribution.”

@vaishnavi_goel Exactly, that's the part we're proud of. One bad info can suddenly break the result your agent gives. Let us know how it works for you!

@vaishnavi_goel That’s one of the core reasons we built AnySearch. Agents and AI workflows need trustworthy, structured information, not just more links. We’re working to help filter out low-quality signals before they enter the context window, so agents can reason with better inputs and hallucinate less. Would love for you to try it!

@luki_notlowkey Thanks! Yep, that’s exactly the kind of downstream agent use case we care about.

AnySearch returns structured results with source attribution, so agents can cite where a claim came from instead of treating search as a black box. Results are also relevance-ranked, and we expose confidence/freshness-style signals where available so developers can decide how much weight to give each source.

We try to be careful with this though: confidence shouldn’t mean “the AI is definitely right.” It’s a signal for the agent to combine with its own policies, cross-checking, or human review when the stakes are higher.

@manuelabarcenas Thanks so much! We'd love your feedback!

@manuelabarcenas Thanks Manuela! You can plug AnySearch into any agent or workflow you already use and give it a spin. Excited to see how it works in your setup :)

@manuelabarcenas Really appreciate it. Would love to hear what you think once you’ve tried it.

@shrivas_vishal We conduct parallel searches on multiple trusted vertical sources at the ame time, rather than scanning the entire web in line and then slowly filtering through the results.

Benchmark testing is one thing, but real experience is another - your query type, proxy link, and processing logic will all make a difference. Instead of looking at numbers, why not directly throw in a few complex queries yourself for testing?

We would be delighted to see how much time you can save in your practical use cases.

@hana_salazars Thank you for your recognition and suggestions! If you have any specific needs you would like us to solve, please feel free to leave a message on our official website. This will affect the priority of our development efforts.

@hana_salazars Thanks — really appreciate the suggestion.

We agree that niche and smaller websites can be very valuable for agent workflows, especially in vertical use cases where the best source is not always the biggest one.

Verified custom sources are a great idea, and we’ll definitely consider this as we continue improving AnySearch. Thanks again for the thoughtful feedback.

@octolens  @charlotteschmitt  With 15+ sources feeding into one endpoint, how much does the AI filtering actually trim down before it hits the agent? Curious whether context gets bloated fast if the agent is pulling raw mentions from Reddit, HN, and podcasts all at once. Does the API give you something like a relevance score per mention so you can set a threshold on what actually gets forwarded?

@octolens  @charlotteschmitt Congrats on the launch!

@octolens  @charlotteschmitt rooting for you guys!!

@reda_roqai_chaoui very very close! Usually just a few seconds.

@rick_borduur Thanks for the review, glad you are liking it!! I agree that it's easiest to get value if you have an existing product or brand.

@worksforme Thanks! We gather context on your business during onboarding and then add context to each keyword you add as well, that helps us score each post for relevance and filter out the ones you shouldn't be wasting your time on.

@busmark_w_nika yes finding supporters or interesting product use cases in the wild is one benefit. E.g., Tally found out that OpenAI was a user via Octolens :)

Thanks Nevo!!

@solodnev basically everything you can do in app + more. You can create keywords and filtered feeds and alerts (e.g., set up a slack alert all via Claude). You can also run any kind of analysis question based on your mention data which is really neat.

Thanks,@ridhwikvinod! When you sign up or add a new keyword we go back one week historical, from then on its about the new mentions coming in.

Thanks Andrè!

We don't do any auto posting or spamming on socials.

Thank you! Appreciate all the support and feedback since basically day 1 of Octolens.

@cafersxhm Thank you! We've put a lot of effort into a clean and easy UX so appreciate this feedback :)

@ryanbutz great to hear!

@pietrozullo Thank you, love to hear this!

@jason_scott8 Thanks! We do have a releance filter as well as tags which help triage. We also have a quick summary of why we think the post is important to you / your business.

With our MCP you can also add your own layer of what you think is important + your goals. I think we can definitely also expand and create some more skills with value add next actions steps and suggestions.

@vikramp7470 Thanks!! We track mentions of keywords in GitHub issues :)

@dora_akulshina thanks Dora! Glad to hear it

@kardelengk2rpc Thanks for the feedback! Noted on Slack customization - as a workaround right now you can use @Val Town from @stevekrouse to customize easily.

@artstavenka1 The lag in podcasts is only about 5 minutes! We have a great Podcast partner in @arvidkahl and Podscan.

@flxmgdnz Thanks for the support and feedback from day 1!!

Thanks, Jonathan!

@galdayan For sure! There is no auto posting or commenting on our end so you have full control over what you build. I 100% agree that you should have a human in the loop and have your original content - that's the only way social platforms and your own social strategy will be successful.

Thanks Luigi! You and @Manufact (mcp-use) have been the best resource for our MCP work!

@victoria_brooks Love that description! That's exactly what we're going for, something that makes typing faster and smarter without ever taking over. There when you need it, invisible when you don't.

@samasante As someone working in the AI space, I really appreciate the focus on privacy and on-device intelligence. The per-app customization and offline autocomplete make this a thoughtful productivity tool. Congratulations on the launch!

@samasante @hnshah Many congratulations to Sam and Hiten on shipping the second version of Typeahead. The AppSumo team and I were really impressed with v1, and it’s great to see so many exciting updates in v2. The LTD is a steal deal, hope the community grabs it. :)

@samasante Congrats on the launch!

@hi_i_am_mimo Good questions! We recommend Gemma 4 (around 5GB) and offer a selection of lighter models to suit your Mac. It's easy on memory too, using only a few hundred MB of RAM even with the larger model. It frees up further when you step away and runs only while you're actively typing.

In code editors it works from the surrounding text as context, so it's best for the prose around your code, like comments and markdown. For writing the code itself, we would still recommend a dedicated tool like Copilot.

@levi_mitchell1 Just open the Insights tab and it's all there, the time you've saved and the keystrokes you've skipped, visualized and cleanly laid out by app. Staying on your Mac just means it's all private, on-device and never sent to the cloud.

@deepanshu_garg9 Thanks Deepanshu, appreciate it! Your tone stays anchored to the style you've set for that app, so a long pasted thread or doc won't pull your voice off. Context is read live as you type with no warm-up, and it focuses on what's relevant around your cursor rather than the whole paste. So it keeps up on the fly, the style holds your tone and the context sharpens the suggestions.

@stella_reed1 Good observation, and it's exactly what we set out to solve. Typeahead knows what you write, how and where, then follows your instructions to match your style, down to dialect, slang and the nuances that make it sound just like you. Slack stays casual, Mail stays sharp, none of it blurs together. Write in whatever voice is yours and Typeahead runs with it 😃

@owen_parker4 Should feel much lighter than anything you tried before! And V2's new engine makes suggestions even faster, with a bunch of performance optimizations to make sure it's as energy efficient as possible. It frees up memory when you're not using it, then picks up again the second you start typing.

@hannah_parker5 Thanks Hannah! That was exactly the thinking. I personally write very differently in Slack than in email, and I love that Typeahead V2 handles this so well. Really glad it clicked for you.

@zoe_sullivan Very reliable! Typeahead is automatically disabled in all major password managers, wallets and finance apps right out of the box, so it only runs there if you deliberately switch it on. It also keeps clear of any password or secure field across every app.

You can see exactly where it's active in the Apps tab, and with everything running on-device, nothing you type ever leaves your Mac.

@lakshminath_dondeti So much packed into this release! Here are some highlights:

✍️ Writing styles + custom instructions, set per app
🌐 Write in any language (plus the whole app translated into 16 languages)
🧠 More intelligent about which context it pulls from the apps you're using
⏱️ Pacing controls so suggestions match your rhythm
🔒 Private by default, off automatically in password and finance apps
👨‍💻 Opt-in terminals and code editors
⚡ New engine with faster suggestions
🔋 Lighter memory footprint and easier on your battery
📊 Insights showing the time you've saved
✅ One-time purchase, free updates for life

It's live now, would love to hear what you think.

@roopesh_donde Thanks Roopesh! Yes, fully offline. The model lives on your Mac, so once it's downloaded you can write on a plane with zero connection. You only need internet to grab the model the first time or pull an update.

@roopesh_donde yes it also runs fully offline!

@crystalmei Great question. It works anywhere the app has a real text field, native apps, chat apps like Slack and Discord, browsers and web editors, Electron apps included. Smart context capture reads the conversation you're in so suggestions fit what's actually being said, in whatever app you're writing. Terminals and code editors are fully supported too (you can opt in per app in 2.0)!

@galdayan That's right! All on-device, no telemetry and your words never leave your Mac. We recommend Gemma 4, a 5GB one-time download, and we offer a few lighter options too depending on what works best for you.

It stays really light on battery because it only draws power in short bursts while generating, then drops to almost nothing at rest and unloads when you step away. Over a full day of typing it's on-demand rather than always running, so it's not something that'll drain your laptop.

@tehreem_fatima5 You create writing styles, assign one per app and add custom instructions in your own words, and Typeahead switches automatically as you move around. It also reads the live context of what you're writing to keep things sharp, so you get the right voice from day one, no training required!

@luki_notlowkey It already runs on local open-source models! Typeahead uses open models like Gemma and Qwen, fully on-device via llama.cpp, and you can pick between them using the built-in downloader. You can even bring your own GGUF. A few of our non-English speaking users have loaded models from Hugging Face tuned for their language and have been getting great results.

@alexandru_bodea Thanks Alexandru, glad it's working great! It's light because it works in short bursts, drawing power only for the moment it's generating a suggestion, then settling to almost nothing at rest and unloading the model when you step away. That on-demand approach keeps energy usage minimal, and your M5 Pro will handle it with ease 😃

@sabber_ahamed Great distinction! It switches on app focus. You can assign a style to each app and Typeahead loads it automatically as you move between them. The window or thread title doesn't trigger the switch, but it's read as context to keep suggestions relevant. So the app sets your voice and writing guidelines, and the context sharpens what it writes.

@christian_knaut Glad you appreciate the local angle! You get full control over how Typeahead writes through custom styles and instructions you set per app. On top of that, our context engine reads what you're actively writing to match your voice in the moment, so suggestions feel sharp and personal right away rather than after weeks of training. And it's fully private: no telemetry, no analytics, nothing ever leaves your Mac 🔒

@akshay_shyam Buying once and having it keep getting better is exactly the idea! And you've basically described how it already works: better models arrive through the built-in downloader as optional updates, so you choose if and when to grab them, with no pressure to change what you already have. It all stays on-device, so suggestions get sharper over time with nothing changing on privacy.

@emmanuel_costa5 Thanks Emmanuel! Sounding like you instead of flattening your writing into the same generic voice is exactly what we set out to do, so it's great to hear that clicked for you. And it all staying on your machine means your writing is always yours, which matters to us just as much. Really appreciate you sharing this 🙏

@mikkel_banner Love this idea! We're really grateful for the support and direction from our early users, as it's enabled us to build exactly what people have been asking for and move this fast to bring you V2.

We have a clear vision for everything still to come for Typeahead, with plenty more to share soon and a public roadmap included. You're welcome to email us any time with thoughts or suggestions at hello@typeahead.ai

@nathan_jake Great suggestion! Personalization is definitely something we're putting a lot of focus into. Our main goal is to get you great suggestions out of the box, through custom writing styles, instructions and per-app control you set, without making you train it over weeks. We've got plans for more smart learning features down the line too, but built right, so it genuinely understands what you write and why, rather than just repeating things you've typed before.

@krekeltronics Exactly the right thing to watch, and it's controllable per app. You can switch off window and clipboard context in the app with your customer notes while leaving it on where you're drafting public text. Sensitive apps are off by default, and since it all runs locally, any context it uses never leaves your Mac. You're always in control of the context Typeahead has access to.

@dhiraj_patel5 Thanks Dhiraj! It handles those really well. The context engine intelligently captures relevant text from the window as you type, so content that loads in dynamically gets picked up in real time. Suggestions stay accurate, even in busy web apps like CRMs.

@ekelikilkn72240 Good news, this is already here in V2! It's exactly what Writing Styles do. You can create named presets like Work Email, Casual Chat or Academic, each with its own tone and instructions, and Typeahead switches between them automatically as you move from app to app. Your email stays formal, your chats stay casual, no default voice everywhere. There are even a few ready-made styles to get you started (Professional, Friendly, Concise) ✍️

@hasankzlasnnhs This goes well beyond basic autocomplete! Most other tools simply guess the next word from your last few keystrokes. Typeahead understands what you've written, where you're writing and the tone you're using. You can also fine-tune your suggestions with custom writing styles and instructions per app. It's very good at knowing exactly what you're going to write next.

@zain_sheikh Love this idea! Right now your styles and instructions stay local to each Mac, which is by design, everything lives on your device and nothing touches the cloud. We're planning to add an import/export option in the next update so you can carry them over to a new machine. Fully local and account-free, as always ✅

@nurullahbekik Thanks for the kind words! A lot of care went into that inline feel. The ghost text matches each app's font and sits exactly at the cursor, so it always feels like it belongs in the app you're in. You can even customize how the suggestions look, pick a color, make them bolder or keep them subtle. Really glad the craft comes through 😃

@cteerakit Congrats on launching Sunrise — a real Today view, an overdue section and a kanban board on top of Google Tasks is exactly what Tasks has always been missing. We made you a free launch video for it (below), yours to download or re-post anywhere, no strings, and it is whitelabel. You can add it to your launch page in here; launches with video tend to do better than those without.

We built it with FoxPlug: paste your site and it turns what you just shipped into a launch video, images, GIFs and posts in about 30 seconds. This one is on us — make your own free at https://foxplug.com

https://www.youtube.com/watch?v=3nMxVFc2h8g

@cteerakit Well, I have been waiting for this one for long. Thank you for solving a problem for me!

@cteerakit What stood out most wasn't just the journaling experience, but the clear focus on creating a safe and judgment-free space for mental well-being. The guided templates, encouraging feedback, and privacy-first approach make the product feel intentional rather than just another AI-powered journal. One thing I'd love to see over time is more personalized insights that help users recognize patterns in their mood or habits while still respecting privacy. Curious what has been the biggest driver of long-term retention for your users: guided journaling, bedtime stories, or the encouraging feedback feature? Congrats on building something that genuinely aims to improve people's daily lives!

@sonal_waghchoure Changes you make inside Sunrise actually do hit the Google API instantly, even if you have Google Tasks open in another tab. Not sure why you face the sync issue. I'll keep an eye on this one.

However, there is a known limitation. If you edit a task directly inside Google Tasks, it doesn't send a real-time signal back to Sunrise, so Sunrise currently requires a quick page refresh to pull those outside changes in.

@sabber_ahamed It pulls them automatically! There is absolutely no need to re-enter anything. Any changes you make in Sunrise sync right back, and vice versa.

@leo404 Great technical question! On the Tasks page, the columns represent your Task Lists, so dragging a card moves the task to that list on the backend and will show up in Google Tasks. On the Upcoming page, the columns are dates, so dragging a card changes its due date directly in Google.

The only part stored Sunrise-side only is the exact visual order of cards within a single column, since Google’s API doesn't support custom sorting.

@julia_shtogren I have already submitted Sunrise to Google for approval, though the process is taking a bit longer than expected. If you prefer to wait until Google gives us the official green light, that is totally fine too.

@natalia_iankovych It is definitely not just an Android thing. Even most iPhone users still rely on Google Workspace and Google Calendar for work, and Google Tasks just happens to come bundled right with it.

@gaspard_dupuich Offline support is actually already built in! Sunrise caches your tasks locally so you can view them offline, and any edits you make will automatically sync back to Google once you're reconnected.

While the functionality is there, I haven't extensively tested it yet. If you happen to give it a spin while traveling, I’d love to know how it works for you!

@omri_ben_shoham1 The Kanban board writes changes directly back to Google Tasks in real time!

If you drag a task between date columns, it updates the task's due date in Google. If you drag it between columns representing different task lists, it actually moves the task to that list on the Google backend.

@nathan_jake To be honest, I'm a total mouse user, so I hadn't even thought about that! But you’re so right—it would be a game-changer for power users. Definitely going to look into adding this. Thanks for the awesome idea!

@dhiraj_patel5 Absolutely! That is the core foundation of how Sunrise works.

@stacey_connolly2 You should be able to do that right now.

On any page featuring a Kanban view (Try Upcoming tab), you can drag and drop tasks directly between columns. The app handles the changes contextually: if you drag a task into a specific date column, it will automatically update the due date. If you drag it into a different task list column, it will move it to that list.

Give it a spin and let me know how it feels. If you run into any issues with it, just let me know so I can get it fixed right away.

@galdayan That is a great point. Because I use separate project management tools for work, I hadn't hit that specific wall myself just yet. However, the good news is that I am actually planning to migrate my own work setup over to Google Workspace soon. I have no doubt I will be running into the exact same multi-account friction you just described.

Right now, Sunrise is focused on a single sign-in. But handling multiple Google accounts simultaneously is absolutely on my radar, and it is something I will be actively exploring as I build out the next phases.

Thanks for bringing this up!

@sharun_kanan Thank you for the support!

Regarding recurring tasks, you've highlighted a known limitation within the Google Tasks API. The API does not expose recurrence schedules or future repeat dates to third-party developers. As a result, future instances cannot be viewed ahead of time in your upcoming schedule.

I'm considering adding native recurring task support directly inside Sunrise. However, because of the API limits, these native recurrences would not sync back to Google Tasks and vise versa. I'm still evaluating which route to go.

@semihazfcr Right there with you! I used to try solving this by forcing everything into a single task list and sort by due date, but that completely wastes the benefit of having separate lists. With this I can finally use my lists 😂

@prachi_nagwan At the moment, Sunrise does not send separate notifications or reminders. Because the app integrates natively with Google Tasks and Google Calendar, I purposely avoid duplicating features that Google already handles well. If you have notifications set up on your iOS or Android devices for Google Tasks or Google Calendar, those native alerts will continue to work perfectly in the background.

That said, I'd love to know more about your workflow on what specific use case or type of reminder would you find useful to have directly inside Sunrise that the native Google alerts don't quite solve for you?

@max_beyer How will you avoid the legal pitfalls that beset DoNotPay?

👋 Hey Jai, Emile, and Max — love the name AirKaren

This is a brilliant idea. Customer service has become an absolute endurance sport designed to wear you down until you give up. Airlines in particular are masters at it — lost bags, mysterious “technical issues,” 8-hour delays with zero compensation offers. The fact that you’re making it dead simple (just chat → they fight for you) and free in beta is huge.

A few quick thoughts/feedback as someone who’s seen a lot of these tools:

- Airlines is the perfect beachhead. High regulation + frequent pain points + decent payout potential when you win. Great choice.

- The “set it and forget it” escalation (finding regs, writing letters, following up) is exactly what most people won’t do. If you can actually deliver results here, word-of-mouth will be insane.

- Suggestion: Once you expand, banks/credit cards and telecom (especially surprise fees, wrongful charges, and terrible cancellation processes) feel like natural next verticals. Insurance is another goldmine of frustration but might be more legally complex.

Would be curious how “Karen” handles edge cases — does she get better with every case (your collective data), or is it mostly rule-based + LLM per user?

Either way, rooting for you. Taking on bureaucratic corporate moats with good UX + persistence is the kind of thing the world actually needs more of.

Drop some early win stories when you have them — people love seeing the underdog actually win for once.

Best of luck on the launch!

@max_beyer I got stranded in Burlington Vermont for 12 hours because my Greyhound left 30 mins early, @karen pls fix

@andrasczeizel Hey Andras! You nailed exactly why we started here: the compensation is almost always owed, but people just give up because the process is pure busywork.

On rejections, we split failures into two buckets. Technical hiccups (a form times out, a page changes, a CAPTCHA) get retried a few times automatically. Karen persists through the mechanical stuff. However, a substantive pushback, meaning that the claim is contested or genuinely gray, doesn't get auto-hammered. It routes to a human review queue. We'd rather have a person build the strongest next move on a disputed claim than have a bot fire off weak auto-appeals that airlines learn to ignore. Fuller autonomous escalation is on the roadmap, but the whole thing falls apart if Karen starts sending stuff that's easy to dismiss.

Thanks for the thoughtful question!!

@_jai Very sharp. I love the business model, it's a win-win for us consumers.

@keirodev Thank you for the support Kevin! Good question :)

Multilingual is absolutely on the roadmap and, to some extent, we can handle it now. The good news is that most airlines (particularly larger carriers) will allow us to talk to them in English. For other dispute types, however, that's absolutely something we'll build in!

@artstavenka1 Great question! Yes, that's the logic for us – EU261 in particular is nice because the agent can cite the regulation directly (and a deterministic compensation amount) instead of asking for goodwill, which changes the tone of the whole interaction. On hotline vs. form: while we only launched a few days ago, we suspect that the form with repeated escalation and bumping over the phone/email might be the way to go :) Happy to share more details if useful.

@galdayan Fair question, and glad you're asking it upfront. Right now, we're free for users — we're VC-backed and using this stage to prove out the model and build usage data before we're out of beta. Once we exit beta, we'll move to a success fee (a cut of what we recover), so no cost to you, and we'll be transparent about that fee when it kicks in.

On the incentive concern: many claim values are fixed statutory figures based on specifics of the actual incident, not negotiable ranges, so there's no lever for the AI to "push higher." Karen's job is to prove eligibility and build the case, not to negotiate a number. For the ones that are more variable, we estimate the amount owed under various regulations before we fight the claim and aim for that specific number. Hope this makes sense! Something we've put a lot of thought into.

@adam_el_gerbi Hey Adam - the good news is that it does! When you fill out a claim, we research the airline’s policies to figure out the best way to fight the claim. Let me know if you have any questions, and if you have a claim with a niche airline, we can help :)

@howillia Yessir! Please let me know if you have any questions – happy to solve this claim.

@natalia_iankovych Thanks Natalia! That is most definitely on our roadmap :) Stay tuned!

@omri_ben_shoham1 Great question – this is something we are SUPER conscious of. There is still some human in the loop right now, mainly at the step after Karen has determined that a claim is eligible and before we sic Karen on the airline. We make sure that all the guidance the agent is given is accurate and compliant with regulations before we let Karen go out on its own. Obviously not a scalable solution in the very long term, and we'd hope to have more confidence in Karen's autonomous judgment at this step once we get enough usage data. Thanks for the thoughtful question!

@reda_roqai_chaoui Good question! A lot of the time (specifically over the phone) airlines are hesitant, but normally a little persistence does the trick :)

@ryanbutz Hey Ryan! All of those are coming very soon – stay tuned 😎. Is there any specific industry you'd like to see next?

@vollos Good question! It's from an independent mailbox created through AgentMail specifically for that user's case.

@velyr_io Thanks, Flo! Really appreciate the support. On your question: we're VC-backed and using this stage to prove out the model and build usage data before we're out of beta. Once we exit beta, we'll move to a success fee (a cut of what we recover), so no cost to you, and we'll be transparent about that fee when it kicks in.

@ikratekmen32688 That means so much to us! This is exactly why we built Karen. Airlines (and big corporations in general) bank on consumers both not having the knowledge and the bandwidth to cite the actual rules. Glad she held her own!

@sharun_kanan The name earns its stripes every time someone tells us a story like this. The customer service process is beyond enraging, but Karen doesn't get tired, doesn't get disconnected, and doesn't give up. Thanks for your support!

@mia_qiao Hey Mia! Great question – this is honestly the core design decision for us.

The short version: Karen is deliberately biased toward handing back to a human whenever there's ambiguity, not toward pushing. Every claim runs through an eligibility engine before Karen sends anything, and it lands on one of three verdicts:

• Clear-cut → Karen files it autonomously

• Ambiguous → routed to a human review queue before anything goes out

• Clearly not covered → we stop and tell the user exactly why

"Ambiguous" is intentionally broad. If we can't independently verify the delay, if it's a cancellation where the notice period matters, or if the airline might invoke "extraordinary circumstances" (weather, ATC, security), a human looks before Karen acts. We never auto-reject a passenger in a gray area – the airline carries the burden of proof, not the user.

On the sensitive-details side: Karen doesn't free-form negotiate today. It works through structured, law-grounded filings that cite the specific articles they rely on, which keeps it on script. Happy to go deeper on any of these.

@nilferejbc Dang that's impressive! I clicked out of curiosity from the name alone but I am pleased to hear how effective AirKaren is.

@nilferejbc This is exactly the story we want to hear. No hold music, no repeating yourself to three different reps, just the regulation doing the work for you. Really glad it came through on the first real case!

@oliver_chen2  @justinbaduaa  @therealdanielpark Really enjoyed exploring Stanley. What stood out to me is that you're solving the entire content workflow not just generating posts. Positioning it as an "AI Head of Content" instead of another writing assistant is a smart way to differentiate in a crowded space. The strategy-first approach, built around real ghostwriting workflows, makes the product feel much more practical for founders and creators trying to stay consistent on X. One thing I'd love to see over time is performance insights that explain why a piece of content is likely to work, helping users learn rather than just publish. Curious, do you see Stanley expanding beyond X to become a cross-platform content strategist in the future? Congrats on the launch!

@andrasczeizel 
Totally. Those two hours should be spent somewhere else.

And great question. Generally speaking, "make this feel like a founder launch update" works. Stanley is trained on what good pacing and style look like for different content types, so vibe-level direction gets you a strong first cut.

But if you have a specific taste you want to hit, you can get as granular as you want with editing instructions and it follows them like any editor you'd hire. Would love for you to test it and tell me if the taste holds up.

This is the prompt I use for all of my talking head videos. my prompt

@martin_tanner Thank you for your insights Martin!

Yeah, the one feature we haven't shipped yet are filters/colour grading. We're building that out right now so if you try it again same time next week it should work!

We see and hear that most of our users spend 10-15 minutes editing with Stanley rather than 1h 30 mins on capcut/davinci/Pr. We want to cut down all of the tedious tasks (trimming clips, adding captions, etc) so you, as the creative, can focus on the more important things.

We thank you for being a part of the journey and I hope you continue to employ Stanley!

@vitddnv yup - rather than competing head-on with billion dollar editing giants, we're taking our own road and making a bet so big that if it works, we'll be THE tool for anyone who wants to make content

@melisrtekimejb That's awesome!!

We are trying to upgrade our bank of audios as we speak, if you give it a week it should give you better music. Also, the song choice will be as good as the prompt that you give. If you add more preferences the output will be stronger.

Try out different video formats and let me know if the output is as good as the talking head one :)

@artem_shymko 

Hey Artem, appreciate that! Right now Stanley normalizes levels across clips so quiet phone footage and louder segments sit together, and the music bed helps smooth the rest. Heavy background noise cleanup isn't there yet though, so if your source audio is rough it's worth a quick pass before upload. Totally agree it's the real bottleneck, it's an active area for us.

@galdayan 

hey gal, I love this question!

Stanley makes the first call so you get a finished video. But it keeps alternative takes on hand, so if the take it picked isn't landing you can swap it out instead of re-editing from scratch.

The best way i'd describe it is Stanley is a head of content with a strong opinion that allows you to keep the final say, you just skip the 40 minutes of scrubbing three near-identical takes

@winnie_chen4 haha more picnic videos edited on Stanley!

@brydon_parker ay!!! Thanks Brydon!

@julia_shtogren 

Hey Julia! This is the kind of feedback we live for, thank you for actually stress-testing it.

Freeze frames and impact detection are both on our radar, and the starburst timing issue is a great catch, passing that to the team today.

Regarding music, the tracks aren't royalty-free yet, so for Instagram I'd swap in your own audio or a track from IG's library before publishing. Licensed music is on the roadmap since we know done-for-you means publish-ready. Appreciate you flagging it!

@anson_lin1 Great question Anson! There's two layers to it.

For cuts: Stanley watches and listens to your footage, so it understands both the transcript and what's happening visually. From there it finds the actual story beats, trims dead air and filler, and sequences the strongest moments the way a human editor would (hook first, no wasted seconds early where drop-off is highest).

For music: it reads the tone and pacing of your content and picks BGM that matches, then times cuts to the track instead of just laying music underneath.

All of this is trained on what actually holds attention in short-form, so the default output is engineered for retention. And if it makes a call you disagree with, our alternative takes feature shows you the versions Stanley considered so you can pick your own.

@natalia_iankovych Natalia - it's funny that you mention it because we are actually developing a mobile app right now. You said it best: "gets access to my photo library and automatically picks the best photos" is what we are building towards. Stanley, like any video editor, should be able to look through your camera roll, find the best clips, and make an engaging video from it.

We're giving our early web app users early access to the app so if you're interested make sure to make an account + try it out!

@gaspard_dupuich Gaspard, thank you for your great question!

Stanley handles awkward pauses really well. It was actually originally built to only remove pauses.

We have a few videos on our landing page that showcase videos that were editing on Stanley! Honestly, the best way to know is to see for yourself. It's completely free so check it out!

Studio.getstanley.ai

@anthony_holley3 
honestly, not yet. Stanley was originally built for short-form and YouTube-length content, and users are regularly editing 10 minute+ videos on it, so that length is well covered.

Feature film length is untested territory. In theory nothing stops it, but I won't claim it until someone's actually done it. There's only one way to find out :)

studio.getstanley.ai

@shrivas_vishal Stanley is very precise with caption accuracy, I'd honestly encourage you to give it a try and see how it fares.

In the case it doesn't work perfectly, you can even paste in the script and it will automatically add it to the video

@kemalyankosu29 yes, 100%! The goal is that users will never have to touch a timeline ever again. Any edit made should be through a prompt and having a conversation with Stanley.

Curious to see the podcast clips! Can you send me an email to daniel.park@stanwith.me?

@hana_salazars Great point Hana - I'll take that back to the team.

We are working on a feature similar to what Opusclip provides, but better. Stanley should be able to stitch together the most engaging video and give you multiple versions.

The short answer is yes, it can edit long podcasts but it won't give you multiple videos to choose from. Try it now and see how well it compares to other tools! Make sure to create an account because when we launch the clipping feature, we'll send it to your email!

@justinbaduaa  @oliver_chen2  @sharun_kanan 
Thank you Sharun! Hopefully we can see more of your content now that you're using Stanley :)

Stanley edits screen recording footage well. One of our users used it to showcase his AI resume screener and it actually highlighted on the screen what he was referring to while he was talking. Crazy stuff!

Try it out for your launch video and let me know how much time it saved

@bedirhanterkes Bedirhan! I'm so glad to hear that. It's honestly insane how it can cut vlogs so well, even I'm impressed every single day.

When you post that vlog, please send it to me! I'd love to watch it and support where I can.

My email is daniel.park@stanwith.me

@leo404 Great question. It's not a one-shot export.

You get an editable timeline after the prompt, so you can nudge specific cuts, captions, and music without redoing anything. You can use Stanley as manually as you need, but we're confident the AI takes you most of the way.

For the "Stanley cut a beat I wanted to keep" case specifically, we have a feature called alternative takes. It shows you the versions Stanley considered for a moment and lets you pick your own.

Export covers all aspect ratios, vertical and 16:9 included!

Hope this helped and would love for you to test it out!

@ferdiskge So glad to hear that! Messy vlog footage is honestly the best test for it, so this means a lot.

And yes, it stays free for the next little while. Right now we just want Studio in as many hands as possible.

If you're down to share what it made, would genuinely love to see the clip.
My email is daniel.park@stanwith.me

@fberrez1 You are absolutely right. Some compression strategies (particularly Tool result trimming) vary depending on your use case.
To evaluate the effectiveness of each of our compression algorithms, @0kham used SWE Benchmark. I invite you to read his blog post which explains everything: https://www.edgee.ai/blog/posts/introducing-compressor-v2-three-compression-layers-measured-end-to-end-for-a-50-cost-reduction

@andrasczeizel TSR is challenging for sure, we wanted to make sure we reduce the MCP surface with still 100% of the hit on MCPs use.

The classifier was the hard part. We needed to make sure there was no loss of information for the model to understand the different capabilities so went added some info to the model with the following prompt :

"Here are the available integration if needed let us the resolver Tool if you need an external integration" and then adding a list of the MCPs we detected.

The gateway then sends the right MCP request to the client which execute the query. This shouldn't need a restart of the agent or anything.

So far the model always uses the right MCP when needed, hopefully the upcoming usage from Edgee user will help us understand if we're on point every time.

@marcin_dancewicz Thank you very much. Indeed, it seemed very important to us to be precise and thorough in our explanations and benchmarks. We too often see astonishing saving figures thrown around, without any proof or scientific documentation to back them up.

@sabber_ahamed Our gateway is written in Rust, and it's super fast. The full compression takes less than 50ms on average, and it's done at every turn.

@kojimajunya At first, the model's response is a little surprising, but it's still clear and understandable. After using it for a while, I don't even notice anymore that the model's responses are brief… you quickly get used to it.

@mikkel_banner Hey Mikkel,

We ran a bunch of benchmarks to make sure our results are as close as possible to real use cases.

Feel free to check @0kham article which explains the different results we have !

@mikkel_banner Compressor V2 performs very well during long coding sessions, which is something the SWE Benchmark evaluates quite effectively. Feel free to test it and let us know what you think - we love that kind of feedback

@kyo_shino Hi Kyo,

So we thought a lot about the possible issues with caching and I agree that we need to be really careful on not invalidating cache.

Therefore the real MCP never get sent so no cache invalidation and no recomputing of cache which would end up being more expensive.

The way that it works is that the virtual MCP decides which user MCP to call and sends it to the client so that the client can call it. Once we have the result of the call we send it back to the model without invalidating the cache

The 50% we have is cost reduction, not token, but real $$$ therefore it accounts all the cache handling and everything !

@krekeltronics I can confirm that all useful elements survive our compression layers. Don't hesitate to test it and give us your feedback ;)

@stacey_connolly2 Absolutely! By default, Edgee does not store prompts. Our gateway processes and optimizes the context, then forwards it to the LLM API without storing the content. However, if you enable debug mode, we do log the content before and after compression, giving you a complete view of how we handle it.

@atakandinc76916 It's great to receive this kind of feedback, thank you so much. Feel free to post a review as well, it would help us a lot ;)
And we're also available on Discord if you ever need to chat.

@ducan Happy to help you explore our TSR feature with long session. Feel free to reach out with feddbacks ;)

Hey @reda_roqai_chaoui . Our token compression layers are made to be as lossless as possible. Feel free to read @0kham blog post who made a lot of benchmark with SWE to evaluate our compression strategies: https://www.edgee.ai/blog/posts/introducing-compressor-v2-three-compression-layers-measured-end-to-end-for-a-50-cost-reduction

@ch1rag We do not benchmark our competitors ;)
What I can tell you, however, is that we spend an enormous amount of time fine-tuning our algorithms to ensure that our compression does not trigger any additional turns, or negatively impact the efficiency of the model.

@dhiraj_patel5 Everything happens automatically, no need to specify anything. Edgee receives the full request from the agent, processes it as a whole, then forwards it to the model. We try to make the experience as smooth as possible.

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@alex_bravo1 Yeah, that's exactly the use case! just leave your laptop at home and enjoy life while not missing out anything!

On the connection drop: you're actually covered by design. When the app is open we stream over a live socket, but the moment it's backgrounded or you lose signal, notifications go out through APNs (Apple's push service), which does the store-and-forward for you. If your phone is offline for a few minutes, Apple holds the latest push and delivers it the second you're back online, so you don't miss the "agent is waiting for approval" moment.

And because the agent + terminal run on your machine (not the phone), nothing is lost while you're disconnected, the session just keeps waiting. When you reconnect, the full state is right there.

Hope i answered your question :)

@xavier_macia PRECISELY!

you just need your phone and in 99% of the case you're bringing it anyway, and you can do what are doing at home but anywhere

@noctis06 you can activate live activities per terminal, so every agents get their own!

and yes if connection drops, it get resumed automatically, no info lost

@galdayan thanks for the comment Gal!

in my personal experience i didn’t find any problem reviewing on my iphone, but i’m used to since im a heavily user nowadays! but for a person who’s just starting to use it can be weird the first few times, but then you develop more experience .

but what you have suggested can be really good 😄

@kojimajunya hey thanks for the question! nowdays i’m used to review diff on my phone, but for a new user can be tricky, but trust me you’ll get used too :)

@farrukh_butt1 Exacly, codemote is just the controller, not the brain, everything stay safe inside your laptop/server, you just extend the way you are using it

@eliana_jordan Hey Eliana, really appreciate your comment!

and yes I built codemote for the devs like me that want to bring everything on a walk :)

@omri_ben_shoham1 hey Omri! thanks for the question.
Right now you can't approve from the lock screen, right now the lock screen activity is only a streaming of what the agent does, to actually approve, clicking the activity, you'll go in the agents and have a full picture of what it has done. and once you are in the app, you have full access to all the file changes, everything your agents has done so far.

this is the exact flow you would do on your laptop

@akshay_shyam yes! you can connect multiple codemote instances to the same project and everyone sees!

@andrewzakonov Batches per-terminal: one buzz when a terminal goes idle/needs approval, not per stop, and it's suppressed entirely while you're in the app, so you only get pinged for sessions you're not already watching.

@ulehtml WSS over TLS on port 443, so on hotel wifi it's just encrypted HTTPS traffic, no open ports, clear the captive portal and it connects. If it drops, the app auto-reconnects with your saved token while your terminals and agent keep running on the machine, so you land right where you left off.

@krekeltronics Exactly our thesis. CodeMote isn't remote-desktop-for-agents.. the heavy work stays on your Mac, the phone is just a controller.

That means:

• Checkpoints, not blind autonomy: you see the agent's state (running / waiting on you) and approve permission prompts from your phone.

• One-tap continue/stop: Live Activities + push tell you the moment an agent is waiting, so you decide from the lock screen instead of checking every time the app.

• Logs you can actually read : live terminal streaming + scrollback, so a decision is always backed by context, not a guess.

Approval-first is the whole point. The Mac does the work; CodeMote let's you control it from your phone

@jason_scott8 Hello Jason, thanks for you comment! CodeMote currently implement a shortcuts for common actions, so you don't need to every time type the same thing

but could be even better if you could launch this shortcut easier, or even from the live activity.
you gave me a good input for a new feature!
Thanks

@zain_sheikh absolutely yes!
it is a 1:1 mirror of your workspace on your laptop/server, you have unlimited terminals, so you can open 2/3 terminal with different agents CLI on each of them, and do things like you would do on your laptop.

The requirement for codex is that you need to use the CLI version

@selinkutbag9gj Thanks Selin! really appreciate this comment :)

@poyraz860407 Thanks Poyraz! I wanted it to be 1:1 and your things stays yours!

@fberrez1 Great questions Florent, really thanks for the opportunity to explain better how CodeMote works

The agent doesn't run on your phone. It runs on your machine (Mac, VPS, wherever your code is), and your phone is just a live window into it. So if your connection drops, nothing happens to the agent, it keeps going exactly as if you'd locked your phone and stepped away. When you're back online, you pick up right where you left off and see everything that happened while you were gone. Nothing's lost, and you're never guessing whether it kept running or stalled.

And yes, it's fully live, not fire-and-check-back. You watch it work in real time and can jump in the moment it needs you. And sends you notifications when it needs you to do action, so you can fire and forget actually.

I hope I answered your concerns :) what do you think?

@cristiano_marinelli you definitely can! i’ve already coded from my motorcycle too, and is awesome! here is the video

@zaczuo Congratulations on the launch. This looks pretty cool.

@zaczuo The looks like an awesome tool. Congrats on the launch!

@zaczuo  the thing that'd actually save me time is the agent reading the same api ref i do. right now claude code building an angular component against our own design system just guesses props — invents a variant that doesn't exist — and it surfaces in review, not at build. one ref both sides pull from kills that whole class of bug.

@cooper_maruyama Congrats on launching Nixmac — nix-darwin that speaks plain English lowers the bar for a lot of people who bounced off Nix. We made you a free launch video for it (below), yours to download and re-use anywhere, no strings, and it is whitelabel. You can add it to your launch page in here; launches with video tend to do better than those without.

We built it with FoxPlug: paste your site and it turns what you just shipped into a launch video, images, GIFs and posts in about 30 seconds. This one is on us — make your own free at https://foxplug.com

https://www.youtube.com/watch?v=slm_PuhNIyk

@downs_jova35899 I just sighed with relief. We've worked really hard on it but as a developer I've found that things find a way of going wrong as soon as you show it to someone lol

@robin_de_lacroix Indeed. And you can move your configuration to any machine and get it set up straight away.

@omri_ben_shoham1 rolling back is directly integrated in the UI :) And tracking of all your changes via Git so you never lose anything.

@zain_sheikh so far it's up to the user, but it's something that is in our backlog. @cooper_maruyama spends a lot of time thinking about secrets and has IMHO very good takes on them.

@galdayan the configuration will normally be portable for the most part. for many of the apps, Nix (and thus nixmac) can take care of the installation itself, so on the new machine you don't have to worry about whether the app is installed, it will install it for you if not present yet. the shared config with per-host tweaks is something that you can achieve with the tool as well; the same repository can contain different configurations, and you can switch between those. you can instruct the code to share code between those configurations, but also have some overrides per machine if you want.

@mia_qiao Over time. I'm a nix native and built it for myself. My personal repo has hundreds of commits!

@hi_i_am_mimo Of course! I'm a heavy nix user myself, and one of the "not-optional" constraints we give ourselves is that it should never feel like it "gets in the way" to Nix natives.

@fberrez1 We do things like bundling the nixos options doc and even a custom tool that's specifically for parsing the nixos options. Nix also just happens to be very LLM-friendly, which is why it's able to one-shot even quite complex prompts, whereas if an LLM was asked to do the same thing by driving a computer and a terminal, it may fail and/or use a lot more tokens.

Also, Nix is unique in that you can `nix eval` or `nix build` and sort of get an idea if the proposed change will be successful - we do that in the background to increase the probability that the proposed change will work.

@sevilmoolkghgs If it's not on homebrew or supported by home-manager / nix-darwin, in my experience it tends to write a script that gets called on activation that tries to install it. For example, it might find a link to the dmg somewhere. I'd assume this is what most agents would do, so maybe Nixmac is not the ideal tool for something like this

@raphael_kamm Yes! We’re really excited to work on this idea!

@krekeltronics Yes, over the next weeks and months we want to understand the right balance for humans: what needs to remain visible and controllable, and what can be left to agent autonomy.

We are modeling a concept called Interception, which gives users space to influence execution at important decision points. The idea is to let humans make high-level decisions without forcing them to micromanage every interaction between agents.

Control can also come from the runtime environment itself. For example, if you add a reviewer agent with the right tools, other agents can recognize when to delegate work to it.

@dhiraj_patel5 Another very good question - I’m taking note of problems like this.

Currently, Mozaik does not handle shared-state conflicts automatically, so developers need to implement that logic themselves. We will likely introduce concepts similar to mutexes or semaphores to coordinate access when multiple agents try to modify the same state.

@whetlan That is a great question. We built the runtime around the OpenResponses specification, where context is already structured into typed items such as UserMessageItem, ReasoningItem, FunctionCallItem, FunctionOutputItem, and ModelMessageItem.

Mozaik wraps those context items with the participant ID, so agents do not just receive an event name like data_ready. They receive structured context about who produced it, what they were doing, and the intention behind it. This gives other agents enough context to interpret the event more reliably instead of guessing from the name alone.

@galdayan Thank you a lot for this question. It helps us understand what is important for builders and what people are trying to achieve.

I completely understand your concern. We are exploring new possibilities, and for sure we will need to answer difficult questions around cost visibility and unpredictable communication overhead.

We are completely betting on agent autonomy, so we will probably explore concepts where agents are aware of the available budget and receive an additional layer of context about urgency, cost, and whether another interaction is worth it.

@cihanerany22p Yes, absolutely! We just need more time to develop this kind of feature, but we are definitely leaning in that direction. Real-time visibility into what each agent is doing, receiving, and deciding would make debugging autonomous agent teams much easier.

@ufukamac8zz Yes, that was exactly our starting point: why shouldn’t agents behave more like humans?!

@saniye0ike Exactly. We are not excluding agents from following a workflow and collaborating through it. Mozaik is simply a more abstract layer where the workflow does not have to be hardcoded manually and can emerge through agent communication at runtime.

@mia_qiao The main focus is agent coordination and the execution model around it. Mozaik gives TypeScript developers a runtime where agents are aware of each other, communicate through semantic events, and work asynchronously without a predefined workflow graph.

Planning, memory, and model providers can be plugged in, but Mozaik does not try to own the entire stack.

For an existing TypeScript project, the first integration is usually small: install the package, define a few agents as participants, connect them through a shared environment, and let them react to events using your existing tools and application logic.

@noctis06 That is exactly the challenge we are designing for. We plan to introduce a hierarchy flag so agents understand priority, authority, and who should resolve overlapping decisions, similar to how human teams work.

Agents are already fully asynchronous and non-blocking, so they can theoretically handle many concurrent processes. In practice, we still need to test extreme scenarios and define safeguards such as execution budgets, loop detection, and supervisor controls.

@vik_sh It's like you read my conversations. My aunt asked me to find a product exactly like this

@vik_sh Viktor, in this day & age, this is going to be helpful for so many people! I wish you all the best with this and truly hope you are successful! While I hope I never need it, it's nice to know it exists if I do!

@stanislavlysenko, this is exactly the story we built HirePilot around. Spreadsheets get messy fast once you're tracking more than a couple of applications. Glad the dashboard and autofill are actually saving you time.

@stanislavlysenko Spreadsheets are basically everyone's first system until they hit application number 15 and lose track of who they already followed up with. Really glad the dashboard is holding that together for you.

@sakina4 Appreciate that! Yeah, expanding platform coverage is very much on the radar. Workday was the hardest one to crack and we wanted that solid before pushing further, but more ATS platforms are coming as we go.

@sakina4 Sakina, thank you so much, really appreciate the support!

Yes, absolutely. Right now, HirePilot works with LinkedIn, Indeed, and Workday. And of course we’re actively expanding support to more application flows and other ATS platforms like Greenhouse and others.

Our goal is to make HirePilot useful wherever job seekers are applying, so expanding site coverage is definitely a big part of the roadmap.

@sakina4 Thank you so much, really appreciate the support! 🙏

Great question, yes, expanding autofill support to more ATS platforms is definitely on our radar. We've been having some early discussions internally about where to expand next, so users aren't limited to just a handful of sites. Nothing locked in yet, but it's a direction we're excited about. If there are specific platforms you'd love to see supported, would love to hear them!

@datysho 100%, Michael! I appreciate your and your team's leadership while engineering HirePilot!

@datysho Seeing how often job seekers bring up Workday specifically, the account for every company, the same info retyped five different ways, really shows how painful this part of the process actually is for people. Saving that time on repetitive fields adds up fast, and having everything organized in one place instead of scattered across tabs and spreadsheets makes the whole search feel a lot less chaotic.

@kerimova89863 Thanks for the feedback, Metehan! You're totally right - avoiding underpaid roles is a huge time-saver!

We do have a 'Desired Salary' filter on the Vacancies page. You can set your target pay, and it will instantly filter the feed to match your expectations. Would you find it more helpful to see the salary range (min/max) filter? Always looking to improve the UX!✨

@kerimova89863 Totally agree this saves a lot of time. We already support salary filtering for jobs where compensation is provided. The tricky part is that many companies don’t publish salary ranges, so we avoid guessing when we can’t provide a reliable estimate.

Besides salary, are there any other criteria you’d want to filter by before applying?

@kerimova89863 Great point, Metehan. Salary fit matters a lot. Adding salary filters or expected compensation by role/location is exactly the type of feature that could help job seekers avoid wasting time on roles that are misaligned from the start. Would you prefer seeing the salary range directly in the job card, or as a filter before browsing?

@sofiia_havryliuk Sofiia, exactly. Applying is only half the motion - the follow-up is where a lot of people lose opportunity..

That same-day outreach habit is something we want to make feel natural, not heavy. Find the right person, get a solid draft, review it, then send manually when it feels right.

@sofiia_havryliuk 100% agree - that same-day outreach is such a small action but it's the difference between "another application in the pile" and actually getting noticed. We built the outreach feature specifically because we saw how much of a bottleneck the "who do I even contact" question was for people. Removing that friction was the whole point.

Really excited for people to try this part especially

@naimz exactly this goal we are aiming for! Thank you for your support!

@naimz Thanks so much, Naim! Saving job seekers time was our absolute number one priority when designing HirePilot. Time is the most valuable asset when you're looking for a job. Really appreciate the support today!

@naimz Thanks Naim! Time is exactly the thing people don't have enough of during a job search, glad that's coming through.

@andryemel Andrei, thank you so much - really appreciate it!

That’s exactly what we’re trying to solve: job search has become way too scattered, repetitive, and stressful, so our goal is to make it feel much more structured and manageable for job seekers.

Wishing you and Jinna.ai the best as well - appreciate the support!

@andryemel thanks, Andrei! Making the whole process feel organized and under control was the best part of working on this. We appreciate your support and wishing you all the best with your project!

@andryemel Thank you! If we can make job searching even 10% less soul-crushing, we'll take that as a win 😄 appreciate the kind words!

@maksym_dymytriiev1 Maksym, you got it!! The “dozens of tabs” problem is exactly what we kept seeing.

People don’t just need another place to find jobs. They need one workflow where they can discover roles, apply faster, track everything, and follow up with the right person before the momentum disappears.

Appreciate all the work you put into making that feel simple.

@maksym_dymytriiev1 So true, Maksym!! Job searching today can be absolute hell, honestly. That's exactly why we obsessed over creating a unified experience :)

@natalie_chelak thank you, Natalia! As you know, this was such a big part of the product direction.

Autofill saves time, but the dashboard is what makes the search feel less scattered. Once every application, contact, and next step lives in one place, the whole process becomes easier to think through.

Appreciate you bringing that clarity into the design.

@boyok Andrii, couldn’t have said it better. That was the core bet from the start, as you know: applications, tracking, and outreach shouldn’t be three separate workflows when you’re trying to move fast in a hard market.

@val_avdeenko1 Val, good question. Right now we're focused on one side of the market, the job seeker. Employers are a completely different audience with different needs, so it's not our focus today, but it's something we could build toward down the line, opening up the job board for employers to post directly.

Thanks Mikalai. Really appreciate that. Wishing you success too.

Thanks @aditya_sriram , appreciate you stopping by.

Thanks @danshipit , appreciate that. Glad the design landed well.

@mariaelenatzanev Thanks! HirePilot works with LinkedIn, Indeed, Workday, and Glassdoor. We’re adding more platforms soon, our goal is to make applications and outreach seamless across all major job boards.

@mariaelenatzanev The personalization at scale question is a good one, that's actually the hardest part to get right. The outreach pulls in enough context about the role and company that messages don't read like a template, but there's always a ceiling on how personal something can feel without a real person behind it. We keep iterating on that balance.

@spunchev Serge, exactly 😂 Uploading a resume and then manually retyping the same experience into Workday is one of the most painful parts of job hunting.

That repetitive work is exactly what we wanted to remove first. Appreciate the support!

@spunchev Haha exactly, the "please retype everything you literally just uploaded" ritual is a special kind of pain. Glad the autofill made you laugh instead of rage-quit the form 😄 thanks for the good vibes!

@spunchev Ha, exactly the reaction we were hoping for. Uploading a resume and then retyping the same 20 fields by hand never made sense. Glad it landed, appreciate the good luck.

@martin_tanner Martin, exactly! that’s the core idea. We don’t want to remove the human from the process, especially for the qualitative parts where judgment, context, and personalization matter.

HirePilot is built to eliminate the repetitive work first: profile details, job history, education, application fields, tracking, and outreach prep. Then the job seeker can spend more time on the parts that actually move the needle. Appreciate you seeing the concept so clearly.

@martin_tanner That's a really good analogy, proposal automation is basically solving the same underlying problem: eliminate the repetitive data entry so humans can spend their time where it actually matters. Completely agree on the human-in-the-loop point too. We're not trying to automate the "why this company, why this role" part, that still needs a real person thinking it through. Our goal is just to clear out the boring stuff (personal info, work history, etc.) so people actually have the time and energy left to focus on what makes them stand out. Really appreciate the thoughtful take!

@martin_tanner , funny how often this pattern shows up once you've seen it in one industry. Proposal automation, job applications, probably a dozen other fields nobody's fixed yet. The repetitive data entry never needed a human, it just ate the time a human needed for the actual thinking. Glad the concept translates so clearly for you.

@preetmishra thanks, glad to have you here.

@sakina4 , autofill is exactly where this started for me personally. Copy pasting the same info into every form 50 times a day was the first thing I wanted to kill. Glad it's making a difference.

@krishnam_gupta1 , good question. What surprised us most was how many people knew outreach could help but still avoided it, simply because messaging a stranger felt uncomfortable. That's what pushed us to build outreach directly into the product, so people don't have to figure out that first message alone.

Thanks Mary. Yeah, the market's rough right now, that's exactly why we built this. Hope it makes a real difference for you.

Jon, thanks for giving it a shot. Glad the first impression turned around. More features coming, stick around for the updates.

@shifra_williams Early testers say HirePilot helped them apply much faster and stay organized without messy spreadsheets or lost contacts.

@shifra_williams Thank you! You’re absolutely right, most job seekers spend more time managing applications than actually applying.

@shifra_williams Thank you! Couldn't agree more, it's such a massive time sink. Two years ago I was job hunting myself: hundreds of tabs open, a messy Notion table trying to track everything, dozens of resumes sent into silence. It was exhausting. That experience is exactly why I wanted to build something that actually makes applying and tracking easier, for people going through the same thing I did

@oleg_sobolevCouldn’t agree more, Oleg. That’s why we wanted to build something that gives job seekers back control and structure, instead of endless chaos. Thanks for the encouragement!

@manuelabarcenas, thank you so much - really appreciate it!

Would love to hear what you think after you check it out. Wishing you and Fellow.ai all the best as well!

@reda_roqai_chaoui , great question - and you’re right, these competitors are both strong products.

Where we’re trying to be different is that HirePilot is not only about applying faster or tracking jobs. We’re combining the full workflow in one place: auto-filling applications, tracking every role in a pipeline, and then helping users identify relevant people inside the company so they can follow up with real decision-makers instead of just sending a resume into the ATS.

So the focus is: apply faster, stay organized, and increase visibility through smarter outreach.

@shawn_esquivel Thanks so much! Great question. Right now, HirePilot doesn't auto-rewrite your resume or cover letter per job description, but we do support storing multiple resumes, so you can switch between them right in the extension while filling out an application. You'd have a master resume as the default, but if you're applying for a DevRel role vs an Engineering role, you can just pick the version that fits best on the spot.

Full dynamic tailoring based on the job description itself is something we're considering for the roadmap. Appreciate you bringing this up, it's exactly the kind of use case that helps us prioritize what to build next!

@rorbay74131 Great question. Here are the actual mechanics: it's event-driven, where the source can push, and an incremental batch where it can't. Slack messages arrive as webhooks and go straight onto the ingest queue, so new threads are chunked and embedded within seconds, while non-push sources (some wikis, mail sync) are polled at a tunable 15-minute default. We never re-embed the corpus: everything is content-hashed, so a wiki edit costs one document's worth of work, not a rebuild. And retrieval always reads the live index (our compressed "brain" layer is just an accelerator on top), so agents see fresh content immediately. Measured, not promised: in our change-to-answer benchmark today, a newly uploaded fact came back as a correct, cited answer in 15 seconds median, 30/30 trials, script in the repo. So expect seconds for pushed or uploaded content, and worst case one poll interval for everything else.

@eymenyabasoqjc Really appreciate you testing it; that’s exactly the use case we care about. For high-stakes workflows, we believe the system should either show the evidence clearly or abstain instead of guessing. In our benchmarks, Qbrin still maintains a high answer rate, but when the evidence is weak, stale, or conflicting, it chooses not to guess.

@eyll63557046664 Thanks! That was exactly the goal in production: a system should know when the evidence is weak; either it will ask to connect more data sources or say “I don’t know” instead of giving a confident wrong answer.

@keerthi_reddy12 Yes, true. RAG systems do give citations and verification! And we have done better with our patented technology!

@galdayan yes true that’s exactly where permission-aware systems usually break. For Qbrin, permissions are checked at query time, not baked into embeddings or the index. So every answer re-evaluates whether the user can access the source right now. If access changes, the next connector sync updates that state; immediate for push-based sources like Slack, and bounded by the sync interval for polled sources like Drive/wiki.

Because enforcement happens at query time, no re-embedding or rebuild is needed. And we fail closed by default: unknown identity or unclear permission = denied, not allowed.

Happy to walk through the enforcement path; we designed it to be small and auditable.

@patrik_pyoria Sounds really cool! Could you contact me regarding this?

Great question @vollos! Luckily our test users have had the exact same worry and solution is already implemented: recordOptions have redact value, which masks the value even before the browser paint it (= no way to leak if correct selecor used). there is also redact(locator) but there you need to make sure yourself to redact before the brwoser paints the value.

Looks something like this: (styleable)

@galdayan Great question! ScreenCI today supports splicing per video and per language, so you can choose which videos and languages gets triggered (could be a rule in CI based on modified files etc).

But what we have been developing behind a feature flag is a way to split videos into "sub-videos", meaning you could have a long walkthrough recorded and rendered in parts, and the "super-video" on top would stitch the parts together. Works already in code, UI still needs to be figured out with these dependencies. This would mean performance improvements but also allow larger organisations to split ownership of parts to different teams (+ some group could maintain the overlay assets and potentially narration from web editor).

That is the vision, does it sound like a good solution in the situation you have?

@zmra1131403 Great question!

The agent is the one you already have, such as Claude Code or Cursor. The generated video script itself is unaffected unless you change it via other dev tools. The video is Playwright E2E in your codebase, with some extra cababilities, which you can trigger 1. manually or 2. automatically in your continuous integration (CI) pipeline.

It is the same situation as with using Playwright E2E tests with ephemeral products, such as products which have AI responses etc. It is great if your product is abstracted in a way that you can create environment with the same seed every time, so for example the AI response would be the same every time. This helps with ScreenCI video automation, but also testability and product maintainability in general. In my experience dependency injection powerful tool for these kinds of products.

@henri_autio Exactly! That’s a great example of the problem we’re trying to solve. Even a small product or packaging change can make an otherwise good video outdated.

Our goal with ScreenCI is to make those updates much easier, so teams don’t have to re-record everything manually every time something changes.

Have you had a chance to try the anonymous free trial yet? :)

@danielatitienei Congrats on the AppOrbit launch — a verified-MRR leaderboard with a 3D revenue globe is a genuinely fun take on a crowded space. We made you a free launch video for it (below), yours to download and re-use anywhere, no strings, and it is whitelabel. You can add it to your launch page in here; launches with video tend to do better than those without.

We built it with FoxPlug: paste your site and it turns what you just shipped into a launch video, images, GIFs and posts in about 30 seconds. This one is on us — make your own free at https://foxplug.com

https://www.youtube.com/watch?v=QrpeD7x6wNk

@bostanoglu10915 it has a default 2.5x ARR that if the seller lists for sale but doesn't know what price he should ask

@cem_kone Nice idea—bringing AI tools, mentors, investors, and startup resources into one platform could save founders a lot of time. I like the focus on supporting the journey from idea validation through growth. Wishing you a successful launch!

@cem_kone Love this vision, Cem. AI-guided execution is exactly where founder support should be heading. Looking forward to seeing Foundera grow!

@alieksia 

Hey Anastasiia, thanks a lot, really glad it resonates.

Quick answers:

1. Investors - every investor profile is reviewed manually before it goes live (we check the fund/angel is real and actively deploying). We're keeping numbers under wraps during beta, but the network is growing week over week and we're onboarding new ones continuously.

2. Geographic coverage - global from day one. Grants and demo days aren't region-locked; you'll see opportunities from the US, EU, UK, MENA and beyond, with more sources being added regularly.

3. Pricing - Foundera is free for founders during beta. We'll introduce a paid tier later for power features, but the core (profile, discovery, connections, opportunities) will always stay free for founders.

Appreciate the thoughtful questions, feel free to ping if you want to dig deeper.

@abdurrahma55903 Thanks for the shoutout! Appreciate it!

@filizaltuniu43 Thanks for being an early adopter! Really appreciate the shoutout and feedback!

@priya_kushwaha1 Thank you so much! Great question - we use a few techniques to cross-verify intent from different sources to ensure that the leads we do identify are genuinely prospects. This isn't a precise science though and we do get the occasional low-intent leads, but we've been tweaking our models and data sources to get better over time. Also, on the note of founders chasing dead-ends - it was imperative that we try to prevent this. To that end, unlike most other tools, our agents proceed to have full conversations with prospects and only help book meetings with leads that are genuinely interested to help save the founders time.

@amine_aziz_alaoui Thanks for the shoutout! This is a problem that resonates quite deeply with me and I'm delighted to help do something about it!

@alieksia Great question. We use a combination of session cookies, authentication tokens and LInkedin's TOTP to support the various functionality. When you connect your linkedin account and pass the security challenge that linkedin provides, the authentication token is stored securely and then used to authenticate the agents. The TOTP is an optional additional layer that allows the agents to run in the background to find leads even if your browser is closed. If you did want to disconnect our access to linkedin, you can do so in the app directly. We've taken a lot of measures to ensure that we're compliant with linkedin policies and respectful of the limits on your linkedin account based on the type of account (Basic, Premium, Sales Navigator). More details are available on our website.