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Building a SaaS product usually involves more than just writing code. You need market research, product planning, website design, and someone to catch problems before launch. I wanted to see if an entire workflow could happen inside one AI workspace. So I tested Teamily AI 2.0 by building LaunchPilot,... a SaaS platform that helps founders turn product ideas into structured launch plans. I created a team of specialized AI agents: → Research Agent analyzed competing products, audience needs, and opportunities in the market. → Product Strategy Agent used those findings to plan the platform's features and user experience. → Website Builder turned the strategy into a functional website with interactive sections. → Review Agent checked the output for inconsistencies, unclear messaging, and unsupported claims. Then I changed the target audience from solo founders to startup teams. Instead of explaining the changes to every agent individually, I updated the requirements in our shared conversation so the team could adapt its work. Research, planning, website creation, and revisions are all connected inside the same workspace. That's what makes Teamily interesting. It's not just about getting answers from AI, but coordinating specialized agents and people to complete an actual project. Explore:show more

Dhaval Makwana

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52,140 görüntüleme • 3 gün önce •via X (Twitter)

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29 Yorum

Blair Hayes profil fotoğrafı

Blair Hayes3 gün önce

@Teamily_AI An AI team workflow for full SaaS launch is brilliant

Amelia | AI & Tech profil fotoğrafı

Amelia | AI & Tech3 gün önce

@Teamily_AI Coordinated agents beat isolated answers for real work daily

Shara profil fotoğrafı

Shara3 gün önce

@Teamily_AI Chaining research, planning, design and QA tests agent coordination well.

Leon Ai | tech & tools profil fotoğrafı

Leon Ai | tech & tools3 gün önce

@Teamily_AI Coordinated agents beat single prompt answers

Aaliya profil fotoğrafı

Aaliya3 gün önce

@Teamily_AI This is a good way to turn an idea into something people can actually use.

Aryan Rakib profil fotoğrafı

Aryan Rakib3 gün önce

@Teamily_AI The shared context between agents is what really makes this workflow stand out.

Tanvir profil fotoğrafı

Tanvir3 gün önce

@Teamily_AI This is a great example of AI-powered teamwork.

Aakash Kanojiya profil fotoğrafı

Aakash Kanojiya3 gün önce

@Teamily_AI This is where multi-agent systems start making sense for real businesses.

JORDAN profil fotoğrafı

JORDAN3 gün önce

@Teamily_AI Thanks for sharing this

Parul Gautam profil fotoğrafı

Parul Gautam3 gün önce

@Teamily_AI AI is moving from answering questions to getting actual work done.

carmilla profil fotoğrafı

carmilla3 gün önce

@Teamily_AI The storytelling makes the product reveal so much more engaging

Utkarsh Sharma profil fotoğrafı

Utkarsh Sharma3 gün önce

@Teamily_AI Going from market research to a working website in one workspace is impressive.

Roshni profil fotoğrafı

Roshni3 gün önce

@Teamily_AI So true! Coding is only half the battle when building a SaaS.

Alice The Ai Expert profil fotoğrafı

Alice The Ai Expert3 gün önce

@Teamily_AI Teamily turns one idea into a full launch!

Manish Kumar Shah profil fotoğrafı

Manish Kumar Shah3 gün önce

@Teamily_AI This could make early-stage product development much more efficient.

Waz profil fotoğrafı

Waz3 gün önce

@Teamily_AI plant one wrong claim in the research notes and see if Review Agent stops it before the site goes out. that tells you if the review step is real.

Vini profil fotoğrafı

Vini3 gün önce

@Teamily_AI Whole SaaS workflow, one agent.

ᗩshhh profil fotoğrafı

ᗩshhh3 gün önce

@Teamily_AI appears pretty useful

Mujeeb Ahmed profil fotoğrafı

Mujeeb Ahmed3 gün önce

@Teamily_AI Teamily 2.0 looks impressive!

Evia AI profil fotoğrafı

Evia AI3 gün önce

@Teamily_AI Impressive demonstration showing seamless collaboration beautifully orchestrated

Md Riyazuddin profil fotoğrafı

Md Riyazuddin3 gün önce

@Teamily_AI This is where AI workspaces get really interesting.

Vyera profil fotoğrafı

Vyera3 gün önce

@Teamily_AI the catch problems before launch part is the one i'd trust ai with least tbh. curious how it did on that bit

Veyra | AI & Tech profil fotoğrafı

Veyra | AI & Tech3 gün önce

@Teamily_AI One shared conversation keeping every agent aligned is huge

Hana Ai - Marketing Network profil fotoğrafı

Hana Ai - Marketing Network3 gün önce

@Teamily_AI Coordinated agents beating solo prompts every time

Vincenzo Nudo profil fotoğrafı

Vincenzo Nudo3 gün önce

@Teamily_AI A review agent on the same model tends to wave through what the research agent made up, since they share the same blind spots. I'd still check the market part against a few real calls with founders.

Mushfiq Sajib profil fotoğrafı

Mushfiq Sajib3 gün önce

@Teamily_AI Having shared context across specialized agents makes revisions much easier than managing separate AI workflows.

E1ev3n. profil fotoğrafı

E1ev3n.3 gün önce

@Teamily_AI My research notes lived in a different tab from my code within a day of starting a build last month. I keep the research and the build in the same place now and my launch checklist stopped losing items. I want to see whether one workspace holds up past the first week.

Fakhr profil fotoğrafı

Fakhr3 gün önce

@Teamily_AI Turning idea into something exceptional! Here’s the way

Alex Ai | Tools & Updates profil fotoğrafı

Alex Ai | Tools & Updates3 gün önce

@Teamily_AI AI agents building LaunchPilot from research to website is impressive

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Kaitee

50,970 görüntüleme • 1 ay önce

The client cuts the budget in half. Your AI team invents a cheaper quote to make it fit. Would you catch it? 👀 I tested Teamily AI Teamily AI with a real-world project scenario: 📌 One landing page, 3 social posts, and a project plan. 💰 Budget: $2,000 ⏳ Deadline: 10 days Four specialist AI agents collaborated in one chat through a saved Loop. 🔍 Research flagged a critical issue: the enquiry form had no submission destination. 📋 Planning used that finding to scope the work. ⚠️ Review caught a scheduling conflict between Day 8 publishing and Day 9 approval. 💻 Webpage Developer turned the plan into a live project dashboard using Teamily Website Builder. Then I changed one requirement: “The budget is now $1,000. Day 10 stays.” I reran the saved Loop. The updated brief flowed through the team without repeatedly prompting every agent. But there was a problem. The team proposed a $750 “trimmed” page. Our fixed estimate was $900. That lower price had never been approved. I challenged it. The Review agent rejected the unsupported quote and sent the correction back to the developer. The final dashboard exposed the real situation: $1,600 in core work $1,000 available $600 budget gap Instead of pretending everything could fit, the workflow made the trade-offs visible. And I took it further. Inside Open Studio, I used a comment to ask the developer to make the budget gap and available options clearer at the top of the page. The developer refined the dashboard, and I could review the before-and-after result in the same workflow. That’s the difference between generating AI outputs and coordinating AI agents around a shared project. ✅ Multiple agents collaborating in one chat ✅ Saved workflows that adapt when requirements change ✅ Review that challenges unsupported assumptions ✅ Website editing through Open Studio ✅ Clearer decisions without rebuilding everything from scratch The real value of AI isn't making every answer look perfect. It's making problems, costs, and decisions impossible to ignore. The finished dashboard was built with Teamily Website Builder. 🔗 Explore the dashboard and compare the budget options: 🚀 Put your next project through the same test: #Ad #AI #AIAgents #AITools #WebsiteBuilder #Automation

The client cuts the budget in half. Your AI team invents a cheaper quote to make it fit. Would you catch it? 👀 I tested Teamily AI Teamily AI with a real-world project scenario: 📌 One landing page, 3 social posts, and a project plan. 💰 Budget: $2,000 ⏳ Deadline: 10 days Four specialist AI agents collaborated in one chat through a saved Loop. 🔍 Research flagged a critical issue: the enquiry form had no submission destination. 📋 Planning used that finding to scope the work. ⚠️ Review caught a scheduling conflict between Day 8 publishing and Day 9 approval. 💻 Webpage Developer turned the plan into a live project dashboard using Teamily Website Builder. Then I changed one requirement: “The budget is now $1,000. Day 10 stays.” I reran the saved Loop. The updated brief flowed through the team without repeatedly prompting every agent. But there was a problem. The team proposed a $750 “trimmed” page. Our fixed estimate was $900. That lower price had never been approved. I challenged it. The Review agent rejected the unsupported quote and sent the correction back to the developer. The final dashboard exposed the real situation: $1,600 in core work $1,000 available $600 budget gap Instead of pretending everything could fit, the workflow made the trade-offs visible. And I took it further. Inside Open Studio, I used a comment to ask the developer to make the budget gap and available options clearer at the top of the page. The developer refined the dashboard, and I could review the before-and-after result in the same workflow. That’s the difference between generating AI outputs and coordinating AI agents around a shared project. ✅ Multiple agents collaborating in one chat ✅ Saved workflows that adapt when requirements change ✅ Review that challenges unsupported assumptions ✅ Website editing through Open Studio ✅ Clearer decisions without rebuilding everything from scratch The real value of AI isn't making every answer look perfect. It's making problems, costs, and decisions impossible to ignore. The finished dashboard was built with Teamily Website Builder. 🔗 Explore the dashboard and compare the budget options: 🚀 Put your next project through the same test: #Ad #AI #AIAgents #AITools #WebsiteBuilder #Automation

Ryan Carter

121,889 görüntüleme • 10 gün önce

I built a whole coffee shop website before my coffee got cold ☕ And it wasn't just me and a bot. Teamily AI 2.0 is a Humans + Agents platform, people and agents in one chat, so a partner I'm working with was right there with me on the same live site Tried Website Builder with an AI business agent, one prompt and it handed me a menu, cart, reviews and WhatsApp ordering Then the real test came in, my partner dropped a message in the group: 15 min delivery instead of 30 So I circled the number on the live site, wrote one line and sent it to the agent, it changed just that and left everything else alone Published v2 in two clicks, and my coffee was still warm 😌 Not every first draft is perfect, but fixing things right on the live page, with my partner and the agent picking up each other's changes, is what got me Teamily AI is a human-agent collaborative workspace, and honestly it's great for small businesses and teams like ours Watch the number change at the end 👀 Built and edited with Website Builder on Teamily AI 2.0

I built a whole coffee shop website before my coffee got cold ☕ And it wasn't just me and a bot. Teamily AI 2.0 is a Humans + Agents platform, people and agents in one chat, so a partner I'm working with was right there with me on the same live site Tried Website Builder with an AI business agent, one prompt and it handed me a menu, cart, reviews and WhatsApp ordering Then the real test came in, my partner dropped a message in the group: 15 min delivery instead of 30 So I circled the number on the live site, wrote one line and sent it to the agent, it changed just that and left everything else alone Published v2 in two clicks, and my coffee was still warm 😌 Not every first draft is perfect, but fixing things right on the live page, with my partner and the agent picking up each other's changes, is what got me Teamily AI is a human-agent collaborative workspace, and honestly it's great for small businesses and teams like ours Watch the number change at the end 👀 Built and edited with Website Builder on Teamily AI 2.0

Chidanand Tripathi

100,553 görüntüleme • 1 ay önce

Creating a good product video usually means juggling ideas, visuals, editing, audio, subtitles, and endless revisions. I wanted to see if I could simplify that workflow. So I tried Pexo. I gave it my product details, screenshots, references, and the audience I wanted to reach. From there, I could explain the creative direction in plain language and keep refining the video through conversation. What surprised me was that Pexo isn't just generating clips. It's a conversational AI video agent that brings together visuals, audio, subtitles, and graphic treatments to create a complete video. And when something needed changing, I could simply explain what I wanted instead of starting from zero. The workflow became: Idea → Materials → Conversation → Video → Feedback → Refinement For product launches, SaaS demos, brand stories, or social content, that makes the creative process feel much more interactive. The biggest takeaway for me: AI video is becoming less about writing one perfect prompt and more about having an ongoing creative conversation. If you have a product or idea you want to turn into a video, give Pexo your URL and requirements and try it yourself. Pexo #MadeWithPexo

Katherine

74,976 görüntüleme • 1 ay önce

.#ad I ran a client pricing project using Loop in Teamily 2.0 with Teamily AI—and stayed the decision-maker. Scout researched the market. The pricing strategist turned that research into a recommendation. I reviewed it, changed one decision (a flat $49 price, no second tier), and the agent updated the recommendation to reflect my input. Then I triggered the same saved Loop again with new inputs for another client, a boutique coffee roastery, and reviewed a different pricing recommendation. One reusable workflow, with agents doing the research and me making the final calls. Try Teamily AI here: #TeamilyAI

.#ad I ran a client pricing project using Loop in Teamily 2.0 with Teamily AI—and stayed the decision-maker. Scout researched the market. The pricing strategist turned that research into a recommendation. I reviewed it, changed one decision (a flat $49 price, no second tier), and the agent updated the recommendation to reflect my input. Then I triggered the same saved Loop again with new inputs for another client, a boutique coffee roastery, and reviewed a different pricing recommendation. One reusable workflow, with agents doing the research and me making the final calls. Try Teamily AI here: #TeamilyAI

Amalia

118,881 görüntüleme • 3 gün önce

i used to think an AI team meant me + a few agents. then i tried Teamily AI, a Humans + Agents platform where other people sit in the same group as the agents, on the same context. different thing entirely. so: what if an AI team could find the best new generation of AI careers for you? i put 3 agents and a partner i'm working with in one group and gave them the same question: 1. AI Engineer - researched 10 genuinely new AI-native careers 2. Principal Architect - ranked the 7 most interesting ones into a page with Website Builder 3. QA Tester - opened that page, challenged the list, rejected 3 and suggested better replacements then I jumped in again with "prioritize roles with real demand and low competition", and the Architect rebuilt the page with the QA swaps and that ask. one agent researched, one ranked, one challenged the work, and a human pushed it further. one question to a finished page, all in one chat. this is what an AI team actually feels like. final page: Teamily AI try it:

i used to think an AI team meant me + a few agents. then i tried Teamily AI, a Humans + Agents platform where other people sit in the same group as the agents, on the same context. different thing entirely. so: what if an AI team could find the best new generation of AI careers for you? i put 3 agents and a partner i'm working with in one group and gave them the same question: 1. AI Engineer - researched 10 genuinely new AI-native careers 2. Principal Architect - ranked the 7 most interesting ones into a page with Website Builder 3. QA Tester - opened that page, challenged the list, rejected 3 and suggested better replacements then I jumped in again with "prioritize roles with real demand and low competition", and the Architect rebuilt the page with the QA swaps and that ask. one agent researched, one ranked, one challenged the work, and a human pushed it further. one question to a finished page, all in one chat. this is what an AI team actually feels like. final page: Teamily AI try it:

aditya

13,579 görüntüleme • 1 ay önce

I gave an AI coding agent a real project and one simple outcome: Understand the project, research similar memory-agent projects, and turn the findings into a Word document. No step-by-step instructions. I wanted to see if Qoder could actually handle the work.

I gave an AI coding agent a real project and one simple outcome: Understand the project, research similar memory-agent projects, and turn the findings into a Word document. No step-by-step instructions. I wanted to see if Qoder could actually handle the work.

HarriStack

117,213 görüntüleme • 1 ay önce

Moving a project from research to a finished site takes more than one answer, and usually more than one person. Teamily AI is built for that: a Humans + Agents platform where the people and the agents on a project work in one group, from the same context. Teamily AI For "The Museum of Unclaimed Buttons", the Curator agent picked the exhibits and wrote the labels, the Gallery Designer agent built the site from them with Website Builder, and a partner I'm working with joined to make the key calls with me. A priority change midway, adding three more exhibits: a blazer button, a raincoat snap, and a child’s dungaree button, plus a Provenance line for each and a material filter row for metal, plastic, horn, and pearl, flowed into the page while the team kept the important constraints (responsive, keyboard-accessible) in view. The handoff ran from the Curator's labels to the revised section, so each change had a visible place. That gave us a route from notes to page sections, with the agents building on each other's work and the two of us choosing priorities and approving the final wording. The before/after makes the update clear. Teamily AI is a human-agent collaborative workspace, great for small businesses and teams. Finished page: Code: 8P24BK

Moving a project from research to a finished site takes more than one answer, and usually more than one person. Teamily AI is built for that: a Humans + Agents platform where the people and the agents on a project work in one group, from the same context. Teamily AI For "The Museum of Unclaimed Buttons", the Curator agent picked the exhibits and wrote the labels, the Gallery Designer agent built the site from them with Website Builder, and a partner I'm working with joined to make the key calls with me. A priority change midway, adding three more exhibits: a blazer button, a raincoat snap, and a child’s dungaree button, plus a Provenance line for each and a material filter row for metal, plastic, horn, and pearl, flowed into the page while the team kept the important constraints (responsive, keyboard-accessible) in view. The handoff ran from the Curator's labels to the revised section, so each change had a visible place. That gave us a route from notes to page sections, with the agents building on each other's work and the two of us choosing priorities and approving the final wording. The before/after makes the update clear. Teamily AI is a human-agent collaborative workspace, great for small businesses and teams. Finished page: Code: 8P24BK

Doreen

55,537 görüntüleme • 1 ay önce

This is how small teams will work. Not one person driving a stack of agents. A few people and a few agents on one job, in one group. Teamily AI is a Humans + Agents platform built for that, not another solo AI tool. Most agent tools still assume you work alone. I tested it on a real content job: a waitlist page, brief to live page to post. Website Builder, my agents, and a partner, same group, same context. My personal agent already had the offer and audience. A second agent drafted the page from that, no new brief. Midway I killed the discount. It pushed back: the headline was too soft for a cold audience. Then it made the live edit. Before: discount copy. After: waitlist, tighter line. Same campaign, I hit Loop. Angle finder, copy agent, and me. One @ and it ran the post again. The copy agent still softened a claim, so I told it to use the page wording. It fixed it. My partner asked for the CTA to match the page exactly, then signed off. Not perfect. But each pass built on the last one’s work, and after a few rounds it felt like a team, not a chatbot rewriting its own draft. Teamily AI Link in the reply.

This is how small teams will work. Not one person driving a stack of agents. A few people and a few agents on one job, in one group. Teamily AI is a Humans + Agents platform built for that, not another solo AI tool. Most agent tools still assume you work alone. I tested it on a real content job: a waitlist page, brief to live page to post. Website Builder, my agents, and a partner, same group, same context. My personal agent already had the offer and audience. A second agent drafted the page from that, no new brief. Midway I killed the discount. It pushed back: the headline was too soft for a cold audience. Then it made the live edit. Before: discount copy. After: waitlist, tighter line. Same campaign, I hit Loop. Angle finder, copy agent, and me. One @ and it ran the post again. The copy agent still softened a claim, so I told it to use the page wording. It fixed it. My partner asked for the CTA to match the page exactly, then signed off. Not perfect. But each pass built on the last one’s work, and after a few rounds it felt like a team, not a chatbot rewriting its own draft. Teamily AI Link in the reply.

Wesley

36,678 görüntüleme • 1 ay önce