PH热榜 | 2026-02-25

If you've played around with @OpenClaw, you know the drill: 30-60 minutes of SSH, environment config, dependency juggling, unexpected crashes, and manual updates... It's fun at first, then we move on.

@KiloClaw fixes this:

• One-click deploy

• 50+ chat platforms

• 500+ AI models via @Kilo Code

OpenClaw is awesome. KiloClaw makes it accessible to everyone: kilo.ai/kiloclaw - Thank you, ?makers

Interesting launch — but I think there’s an important elephant in the room here.

Tools like OpenClaw and other “personal AI assistants” were compelling largely because they aimed to keep computation and data local. Once you move that into a hosted/cloud environment, you reintroduce the exact risk many users were trying to avoid: PII, system context, files, and behavioral data flowing to third-party infrastructure.

If sensitive prompts, logs, or system-level interactions are still traversing cloud endpoints, doesn’t that fundamentally defeat the purpose of a personal/local-first AI assistant?

I’d really like to see clear documentation around:
– What data leaves the user’s machine
– What is stored, for how long
– Whether any telemetry or logs are retained
– How you prevent unintended data exfiltration

Convenience is great — but privacy is the whole value proposition here. Without strong guarantees, this just becomes another cloud AI wrapper.

This is one of best products i have ever seen this year! cheers for the launch!

Tried OpenClaw earlier and honestly couldn't get through the setup. It felt powerful but the time and infra needed to get it running was a blocker. I even needed my tech team to set it up, that didn't happen because we couldn't align the timing.

Would like to try KiloClaw to understand how this part is simplified.

The move from self-hosted to managed infra follows the same arc as databases a decade ago — same privacy debate, same setup/maintenance tax, same eventual outcome. Most teams traded local control for managed convenience once the offering was mature enough. Curious if dedicated instances for teams with stricter data requirements are on the roadmap?

@OpenClaw finally showed us what a real personal AI might look like. But even as my non-technical friends started hearing about it the setup and maintenance of it was too cumbersome for developers - much less everyone.

That's why I'm so excited for KiloClaw. Up and running in a dedicated environment in seconds with no SSHing or figuring out API keys.

The gap between "this open source tool is incredible" and "I actually run it in production" is where most developer tools lose people. SSH, environment config, dependency juggling ... that's not the work anyone signed up for.

I've been through this exact cycle building my own infrastructure. You spend a weekend getting something deployed, it works great, then three weeks later a dependency update breaks it silently and you're back to debugging infra instead of building product. Curious about the 500+ AI models integration. How are you handling model-specific quirks in tool calling and context window management across that many providers? That's always been one of the trickiest parts in my experience.

KiloClaw is the easiest and safest way to claw!

Congratulations on the launch 🎉 🎉

a killer launch from the @Kilo Code team, congrats!
I have been trying other solutions in the past few weeks and this is definitely the most elegant and gives you loads of control.

I think this is a great step in increasing adoption of AI assitants like OpenClaw. As a developer the setup already takes me some time, so I can only imagine what its like for someone non-technical.

Glad to see this. will try this today

Wow! that saves a lot of money and time, well done!

This lowers the entry barrier massively A lot of people want to experiments with Openclaw but don’t want to babysit servers Hosted just makes sense.

Openclaw came out, mac minis were bought

People without it used cloudflare moltworker

But the non-technical + no mac mini people were left behind.

In what real way is this (is it?) more user-friendly than Cloudflare during deployment?

@OpenClaw is changing the landscape of AI, but for a lot of people the technical and security barriers are too high to use it comfortably. @KiloClaw solves this by handling the hosting, configuration, and model connections so you can use OpenClaw with no setup or maintenance headaches.

I'm excited for people who were intimidated by OpenClaw to finally see how awesome it is through KiloClaw!

Been using this since early access, pretty flaky experience with frequent downtimes 🤣 but generally positive experience so far as this is my first time using OpenClaw. Learnt a lot of new stuff and really impressed with the whole ecosystem.

Congrats on the launch!

SO I could use this as the brain on my raspberry pi voice assistant at home????? Im not a developer, is it easy? haha. ( dont trust chatgpt opinion on this)

I'm finding my KiloClaw super helpful as a research assistant -- some glitches in the first release but now running smoothly and really amazing to have the always-on agent working for me!

Kudos to the team! Nothing but great things i've seen from this team — especially @realolearycrew, one of the GOATs :)

Wow! It's amazing. What about the pricing? Is there a free trial?

This is a big update for teams already living inside @Notion.

What excites me most is that Notion Custom Agents aren’t just “chat with AI”, they’re autonomous workflows that actually run on triggers and schedules. That shift from reactive to proactive is incredible.

A few things I love:

• Q&A Agents that instantly answer repeat questions using Notion + connected tools (goodbye Slack noise)

• Task routing agents that automatically triage incoming work (this alone can save ops teams hours weekly)

• Status update agents that gather context and draft recurring reports (async teams will love this)

• Plain-language Agent Builder... describe it, and it builds it

• Granular permissions per agent (huge for enterprise confidence)

• Full audit logs + reversible changes (critical for trust)

• Works inside existing workflows (no rebuilding knowledge)

Lowkey excited to see what workflows Notion power users build with this. :)

Get started here: https://www.notion.com/product/agents

P.S. Follow me on Product Hunt for discovering the latest and greatest AI / SaaS products: @rohanrecommends :)

We already love notion and have been building these ourselves so far stoked to check it out.

I'm in love with this feature and have been testing it for a while. Seriously fantastic and for the most part, it just works.

My only caveat, and I hope Notion is listening to feedback on X and Reddit, is that the cost of Credits (used to run Custom Agents) is extremely high ($10 for 1,000 Credits.)

A few days of running some reports and reformatting website content into a few pages cost over 7,000 credits—that's $70 of credits over 5 days for pretty routine tasks. And that's for a single Agent.

I simply can't justify that cost. At that price I think this is more aimed at Enterprise users. Would love to see the price brought down for more accessibility.

The "no rebuilding knowledge" point is the most underrated part — most AI tools require you to re-explain your entire context each time. Agents that already understand your linked databases, SOPs, and project structures skip that friction entirely. Do they traverse across linked databases and nested pages, or is scope limited to individual docs?

This is a big deal for teams already living in @Notion . The "set it once, runs while you sleep" promise is exactly what async-heavy teams need — especially when your docs, tasks, and comms are already in one place.

Curious how the agents handle ambiguity, like when a task trigger fires but the context is incomplete. Does it ask for clarification or just make a judgment call? That's usually where automation breaks down in practice.

Building AI-orchestrated workflows myself and the hardest part is always graceful failure, not the happy path. Would love to see how Notion handles that edge case

Huge upgrade to Google Opal today!

With Opal’s new agent step, workflows aren’t just linear automations anymore, they can actually analyze the goal, decide the best approach, and call the right tools (Veo for video, web search for research, etc.).

That’s a meaningful shift from “flow builder” to “decision-making system.”

The addition of Memory is huge. Persistent context is what turns demos into real products. Combine that with Dynamic Routing (@ Go to) and Interactive Chat, and you’re basically getting conditional logic + user-in-the-loop + long-term context, without code.

Example Opals you can build now:

🏠 An Interior Design Collaborator that remembers your home’s aesthetic.

📖 An Interactive Storybook creator that evolves with your choices.

💡 An Idea Generator that interviews you to refine your vision.

My take: this makes “Super Gems” on Gemini way more powerful because now your workflows can think before they act. If Google keeps tightening the loop between Gemini, Veo, and Opal, this could become one of the most underrated no-code AI builder ecosystems out there.

The wild part is how normal it feels now. Organizing the world’s information sounds dramatic, but when you think about Search, Maps, YouTube, Drive, Gmail… they basically became the default layer of the internet. Search used to be about links. Now it’s slowly becoming about answers. That shift is massive. Curious are you thinking about this from a product perspective or just browsing Product Hunt launches?

The app is weird.

I try to check app in the library and create my own and in both cases got error.

Looks the limits is poor.

👋 Hey Product Hunt!

I'm Jeff from Arzule.

🚨 The problem

Partnerships are one of the most powerful growth channels in B2B SaaS but most teams still run them across spreadsheets, scattered notes, Slack threads, and gut instinct.

It’s hard to know:

• 💰 Which partners will actually drive revenue

• ⏳ How to prioritize limited time and resources

• ✅ What to execute next after signing

• 📈 How to measure ROI across co-marketing, referrals, and integrations

Discovery is hard. Ongoing management is just as hard.

🧠 Why we built Arzule

We saw partnership leaders spending weeks researching companies, manually tracking touchpoints, and guessing what was working.

Even after signing great partners, execution would stall because there was no structured system of intelligence guiding the relationship.

⚙️ How Arzule works

• 🔍 AI-powered partner discovery that continuously finds and scores high-leverage partners based on fit + ecosystem signals (with automated outbound)

• 🗺️ Structured activation plans that turn strategy into a 30-day execution roadmap

• 🤝 Ongoing partner management with measurable revenue attribution, commission tracking, and partner health analytics

• 🧾 Clear reasoning behind every recommendation so teams understand the “why”
  

✨ How we’re different

Traditional PRMs focus on record keeping.
Arzule is a system of intelligence for partnerships (and later other rev ops workflows) which helps you decide who to work with, what to do next, and what’s actually driving revenue.

🎁 Launch day offer

If you request access or email us at founders@arzule.com today, we’ll offer extended pilot access + hands-on onboarding for your first partner workflow.

We’d love feedback and tough questions. We’ll be here all day. 🙌

Congrats!

Congrats! How does Arzule validate that its partner scoring actually correlates with revenue outcomes over time?

Hey! Congrats on the launch
Curious how you differentiate vs the established ecosystems of PRMs? Salesforce, Impartner, Zift, Partnerstack and so on? Lots of players in that market, what are you all thinking when it comes to those players?

Hey everyone 👋🏼 I'm Vincent, 4th launch here!

The idea with floors.js is stupid simple: what if your website felt like Habbo Hotel?

You paste one script tag. Your pages become isometric 3D rooms. Visitors appear as blocky avatars with random names. They can walk around, chat, and you see it all in real-time.

Why?

Think about this: you see people with your analytics, but they can't see you.

→ With floors.js, you're in the room with them, and can message them while they're still browsing.

Under the hood:
- Vanilla JS embed, no framework needed (~4kb gzipped)
- Three.js for isometric 3D rendering
- WebSockets for real-time presence
- No cookies, no tracking, no signup for visitors - GDPR-friendly by default
- Auto-detects your links and turns them into rooms
- SPA-compatible (React, Next.js, Vue, Nuxt, Astro)

The landing page IS the demo! Open floorsjs.com in two tabs and you'll see yourself appear.

And say hi if someone's there (probably me right now).

I'd love your feedback, and happy to answer anything!

Such a fun idea! Feels like being back in my youth :D

You brought me back 20 years back with the Habbo Hotel inspiration, love the idea! Congrats on the launch!

Super refreshing compared to typical chat widgets. The one-line script + no signup friction is a big plus, and the nostalgia + utility combo is honestly pretty clever.

Hey Product Hunt! We’re excited to be back with another launch.
We built Fellow because we knew meetings could be more productive. But as AI evolved, we realized the real problem wasn’t just capturing what happened, it was everything that comes after:
- The follow-up email you didn’t send
- The doc you never created
- The action item that fell through the cracks
The all-new Ask Fellow is our answer to that: not just an AI notetaker that listens, but an AI Meeting Agent that actually does the work for you.
We’d love to hear what you think, and what you’d want it to do next!

Huge congrats to the team on this release!!!

This is great, as a constant daily user I'm extremely excited with the new integrated AI functions

Wow! Beautiful design and UI :)

Looks really cool, congrats! Do you have a special focus on Mobile?

can you make it available in France ?

Cool! I love the minimalistic design. Although functions are limited this way, the room for unecessary elements are also removed.

Hi everyone!

Diffusion models, or dLLMs, are currently one of the most promising paths outside the standard autoregressive route. Everyone is exploring this space right now, from @Seed Diffusion to @Dream 7B and even @Gemini Diffusion. But the standout player is definitely Inception with their Mercury series, and they just pushed their second generation live.

The architectural shift changes everything about latency. Mercury 2 abandons standard left-to-right sequential decoding. Parallel refinement drives the generation instead. Think of the model less like a typewriter printing one token at a time and more like an editor revising a full draft simultaneously.

This parallel approach makes the inference insanely fast. Hitting over 1,000 tokens per second gives you a 5x speedup over leading speed-optimized models. This fundamentally alters the equation for multi-step agentic loops or real-time voice apps where latency compounds across every single step.

The API is strictly OpenAI compatible, so you do not need to rewrite any code. You can apply for early access to the API or just chat with it right now to feel the raw speed of a next-gen diffusion model.

Love the approach here, diffusion for LLMs is exciting to see at scale.

I’m curious, with parallel refinement at that speed, how do you make sure the outputs stay consistent. especially on longer reasoning tasks?

Parallel refinement instead of sequential decoding is a bold technical shift. 1,000+ tokens per second with reasoning grade quality is not a small claim, especially for agentic loops where latency compounds fast.

From a positioning angle, though, the speed story is clear, but the practical transformation could be sharper. Is the real win lower infra cost, smoother agent chains, or enabling use cases that were previously too slow to ship?

You could test framing Mercury 2 around one concrete before and after scenario, like what becomes possible at 1,000 tokens per second that was painful before.

Curious, what is the first production use case where teams feel this speed difference most viscerally?

this is just awesome!

Turning AI coding into a couch-friendly, almost console-style workflow is lowkey genius. The Accept / Reject / Scroll / Dictate loop really is the core loop of AI coding right now mapping that to muscle memory just makes sense. Also building VibePad with VibePad?? That’s founder energy. This feels like the beginning of ambient coding where your keyboard isn’t the main character anymore 🎮💻

This is such a cool idea@vova_ignatov!

Building VibePad with VibePad is a fantastic example of dogfooding. It's awesome that you've made coding feel more like gaming. I will try it for sure

I don't know how functional this is but respect. 🫡

Hi PH! I'm G, the founder of Yuma!

Today we're launching Social AI, because your brand's social media interactions shouldn't be a black hole.

The story

Yuma AI's support platform has automated over 5 million customer queries for e-commerce brands since 2023. Over the past year, we noticed something interesting: brands that run tight support operations still lose control of their social media comments, specially when the brand is growing fast. The main reason is that brands need to focus on real support inquiries through defined support channels. This leaves social comments and interactions unattended. While social interactions are not always direct support tickets, they can wreak havoc on the brand's trust and sales if not handled. And because they're public, one careless reply can reach thousands of eyes in minutes.

So we built Social AI.

What it is

Social AI connects to your Facebook, Instagram, and soon TikTok pages and uses AI to monitor, classify, and respond to every interaction on your posts, across both paid and organic. You set the rules, Social AI handles the execution. In early testing, Social AI safely automates up to 60% of repetitive social media moderation.

Here's the TL;DR:

• Connect in one click - Social AI ingests every comment across platforms in real time.

• AI classifies each comment by intent and sentiment - Support requests, positive feedback, negative content, user tags, free merch requests: each one gets categorized automatically.

• Build automations for any scenario - Use built-in templates for common actions (reply, like, hide, flag, or skip), or create fully custom rules. Each rule is scoped by platform, intent, sentiment, and user popularity. You control what gets automated and what doesn't.

• Works across paid and organic posts - Negative comments on your ads are conversion killers, and Social AI catches them before they cost you.

• Set your brand's voice - Configure the agent persona, tone, and verbosity so replies sound like your team wrote them.

• Crisis prevention - Social AI detects and escalates comments that could spiral into bigger brand issues before they do. Advanced targeting based on the commenter's follower count means high-profile users get the extra care they deserve.

• Full dashboard with real analytics - Track total engagements, automation coverage, sentiment distribution, negative exposure rate, and unanswered rate. Filter by platform, sentiment, intent, or automation status.

• 24/7 coverage - 50% of comments are posted outside business hours and on weekends. Social AI is always on so your brand is never unprotected.

Why we're excited

Social media channels are one of the last unmanaged parts of e-commerce customer support. Brands invest heavily on content and then leave their social channels to chance. We build Social AI to fix this exact problem.

We're offering a 30-day free trial so you can test it on your own pages. If you run an e-commerce brand and want to stop letting social comments fall through the cracks, reach out in comments or DM me and we'll get you set up!

Big congrats to the Yuma team on this launch! Turning social comments into real-time action is a massive win for ecommerce brands.

wow awesome product guys!

I think this is a great tool! I see a lot of brand accounts where there is no interaction with the customers at all, this definitely would solve for that. For me when I see replies to people from brand, it adds a level of trust, and through Yuma I believe brands can leverage that.

In future, do you also plan to integrate features where the AI can find relevant and related reels or posts throughout social media and drop a quirky comment or just a reply there in general? Is that possible to do?

Interesting, I really like how you're positioning social moderation as a brand safety layer, not just a support extension.

Quick question: how do you prevent tone misalignment when brands operate across different regions or product lines with distinct voices?

interesting. but does ig flag account for the ai comments? asking from interest

Congrats team, this looks awesome!

Looks awesome, congrats team!

How well does it run on lower end devices like older laptops or tablets?

I've never played Minecraft, but ig now it is time to do it!

This feels so nostalgic. I used to play it 12 years ago. Wishing have more time for that now. 😭

Looks great - congrats on the launch!

Co-creator and maintainer here!
It's been so fun to see the dev + agentic engineering world find so much joy with this tool my brother and I built for our own utility.
Give it a shot and feel free to file an issue or PR if you have any thing you want to improve.
work work!

keep creating more products like these

I installed this as soon as I found it. I personally use the Zelda pack. Great little tool that makes working a bit more fun (and efficient!)

This is one of those tools that sounds like a fun gimmick until you actually use it and realize it solves a real workflow problem. I run Claude Code sessions constantly, and the silent terminal problem is real. I'll kick off a task, switch to another window to do something else, and then 15 minutes later realize the agent has been waiting for approval the whole time. That context switch tax adds up fast when you're running multiple sessions.

The hook-based approach is smart. Having different sounds for completion vs. error vs. needs-approval means you can stay in flow on something else and still triage what's happening by ear. Useful UX pattern. Great job!

Love the UX here! What are the sources for live crime & events?

love it - wish I had this while I lived in SF. maybe you can try london next :)

nice one! What is your price?

The privacy focused angle is important here. Location data is sensitive, so keeping it simple and transparent builds trust.

Hey Product Hunt! Kenneth here 👋 Co-founder of Mito Health (YC S24).

I spent over $2,000 on blood work last year trying to track my longevity protocols. Across 4 different lab companies. Because none of them would let me order exactly what I needed at an affordable price.

• Quest & Labcorp: "Pick from these preset panels."

• Function Health: "Everyone gets the same 100 markers."

• My doctor: "Insurance won't cover that."

The result? I paid for dozens of irrelevant tests and got blood drawn multiple times, getting bruised, while missing the 5-10 biomarkers that actually mattered for what I was tracking.

Our Bespoke Lab panels fixes this:

Tell our AI what you're optimizing for (fasting, hormones, athletics, longevity, etc.)

It designs a custom panel with the exact biomarkers you need.

Order it. Do it in one sitting across 2000+ lab locations in US, and get your results in 2 days. AI interprets everything. (or you could easily export and upload it into your own ChatGPT, Claude or Gemini.)

No more paying for irrelevant markers. No more gaps in your data. No more cobbling together multiple lab orders and managing multiple PDFs.

Example from my own use case in Jan 2026:

I wanted to test a fasting-mimicking diet with proper metabolic stress monitoring.

Using this tool, I built a 95-biomarker panel covering ketosis markers, inflammation, kidney safety, and IGF-1 signaling.

Got answers in 2 days and it cost way less than my usual "generic over overloaded panels."

That's what we're launching today: custom blood work that actually aligns with your health goals.

Try it out and let me know what panels you'd build! 🩸 (Available in the US across all 50 states)

Or perhaps agent-to-agent interactions to help you order your labs based on your own health history.

🐱 Get 10% off your first test, using the code PH10OFF only for our Product Hunt friends.

I am big fan of AI solutions that focus on healthcare and improve people health via technology for affordable prices. Love the idea of making it easy for people and save their time and effort and money. Are you planning for outside US soon?

Nice work Kenneth. love your idea of asking whatever you truly want to test and not forced to. In which country is this supported. really like how clean your landing page is. How will you present the data that you collected from the blood tests. like building a cool dashboard would be really cool. just saying

I tried out the AI chat, and after about 2 minutes back and forth, the agent forgot context and started to repeat itself.

Congrats on the launch team

Android is always a brides maid.

Hi! This looks interesting, but I can't seem to acces sit in the iOS app store. The link on your page doesn't work.

never upvoted anything so fast in my life 🙌

What are the sources of the news? Can I somehow double-check them? Manage them?

Funny coincidence — I launched AIArrive today, an app literally built for commuters! 😄 When I saw 'The Commuter' I

thought we were in the same space, but turns out you're solving the news problem while I'm solving the 'never be late

again' problem. Love the thread-based approach to news though — would actually be a great combo: read your Commuter threads while AIArrive makes sure you leave on time. Upvoted! 🚀"

Congratulations on the launch! I was excited to check this out, and I think it’s a strong concept with real potential.

What’s Working Well

• The onboarding experience is quick and seamless.

• The UI feels clean and thoughtfully designed.

• Content is easy to read, with good clarity overall.

Additional Feedback

It took me a little time to understand exactly who or what I was looking at in the feed — specifically differentiating between verified or “true” sources and shortened publisher names like “techauntie,” “morecontextgal,” “partyintheusa,” etc.

Some clearer visual distinctions between source types could really improve scannability and trust.

Additionally, stronger visual cues could help users navigate the different news categories (Tech, America, The Commuter, Goallll, etc.). Right now, the screen feels slightly scattered, and a bit more hierarchy or grouping could make the experience feel more intentional and structured.

Overall

I’ll continue using the product because I see real value in it, and I’m especially curious to see how the iOS notifications evolve.

I’m a big fan of the typography and hierarchy in The Wall Street Journal — I’d love to see how you all continue refining this into something equally useful and uniquely your own.

Great start — excited to see where it goes.

Hello! I'm Sarah from the Draftwise team — we are just so excited to be launching Playbook Studio here today.

Every lawyer and legal team we've ever talked to has the same quiet frustration: their best work (the hard-won redlines, the negotiated positions, the institutional memory built over years of deals) lives scattered across folders and email threads. Playbooks, if they exist at all, are usually outdated the moment they're finished. And building one from scratch requires hours of tedious manual work.

Playbook Studio is our answer. It analyzes your existing contracts and negotiation points and generates a deployable, customized playbook in about 5 minutes.

Imagine you're a General Counsel at a Venture Capital firm. You're operating at a pace that traditional playbook management simply can't keep up with: processing hundreds of NDAs, term sheets, and portfolio company agreements simultaneously, and often with a lean internal team and aggressive timelines where a delayed close has real consequences.

The institutional knowledge to handle this volume exists, but it's trapped: buried in executed agreements, scattered across deal notes, and locked in the heads of your team. Playbook Studio changes that equation by automatically codifying your accepted language, hard lines, and flexible positions, so you can operate seamlessly and at the pace of the business.

For context, we've seen NDA review time drop from 60 minutes to 2 minutes for teams using a playbook generated by Playbook Studio.

This isn't generic AI advice. It's your positions, your risk tolerances, and your accepted language — codified automatically in your customized playbook. In a world where every tool is converging on the same general AI-generated market-standard output, your precedent is your competitive advantage, but only if you can access and action it effectively.

We're offering a free 2-week trial starting today. Simply upload an existing NDA or contract template, and you can be up and running in minutes.

Would love to hear from anyone who's wrestled with playbook management. What's been the biggest barrier for your team? Let's dig into it here together👇

Amazing one, loved it. One question .. is this a service-based like I request the model and team build it or its self-service based where form the website I generated automatically after answering the form questions

Hey there 👋

I'm the solo-founder of Synlets, and I wanted to tackle a problem I've seen since i started my career in Software and especially after AI began reshaping our beloved software industry 😀.

So 3 things kept bugging 🐛 me:

🔴 Backlogs that never shrink — Every team I've worked with has a graveyard of tickets sitting in Jira/Asana/Linear that nobody has time to get to.

🔴 AI left non-technical people behind — Engineers got Copilot, Cursor, Claude Code... but project managers and non-technical founders? Still waiting. The dream is simple: describe what you want, get it shipped. Instead, it's still "manually make a ticket, chat with engineers, try to fit it into the sprint, watch it get deprioritized, repeat." And even when tickets do get made, they're often missing codebase context, infrastructure details, and technical nuance — so engineers spend half their time just figuring out what was actually meant. This process I have seen countless times....

🔴 Engineers still get the boring stuff — engineers still spend time on routine tickets that really don't need them. There are even reels on insta/tik-tok when engineers get a ticket, they simply dump the request into AI and make a pull request immediately 😀. Meaning a lot of the times easy/mid level tasks don't even need an actual engineer they can just be made by AI agent and then be assessed.

So I've built Synlets —where you can assign a ticket to AI agent, get a working PR back. It handles implementation, runs code review against your team's standards, and fixes issues automatically. PMs can assign work to AI the same way they assign it to an engineer. No IDE, no terminal, no prompting.

The goal isn't to replace engineers. The goal is to delegate easy/mid level tasks to AI agents that realistically don't require an engineer to implement it. We are trying to free engineering time for hard problems while AI handles the rest 🚀

Would love ❤️ to hear what you think — happy to answer any questions!