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Appaca – AI Workspace for Operators

Hacker News

Appaca – AI Workspace for Operators

Appaca is my third pivot. A couple of years ago, I started working on an idea on no-code platform that generates code. The goal is to help devs and agencies ship products faster for their clients. I went through Antler startup accelerator and got initial funding. I was working on the right problem, but wrong solution. Instead of no-code, I should have jumped into LLM a lot earlier. I felt defeated when Lovable, Base44, and Bolt came out strong, showing the world what LLMs can do in software development. No one cared about my product anymore. I pivoted my startup second time after that, to an AI agent builder for businesses. After my first MVP launched, I got some decent tractions with that. A lot of people wanted to make AI agents that they can monetise. So, I focused on making a platform that helps them build and ship monetisable AI agents. The product made some revenues, but the churn was super high. Later, more mature companies like Zapier and N8N started their AI agents. My competitors in the US and Europe are raising serious money. As a solo founder in Australia, I couldn't get the funding to compete with them. I realised some of my users are using it for their internal operations. So, my last pivot before running out of my current runway is Appaca. With my experience building an app builder to AI agent builder, I rebuilt the entire platform and make it an AI workspace where the team can build and run their internal ops tools by chatting with AI, and connect tools with their existing system. This space seems a bit competitive as well. But, I have a conviction that Appaca can be the platform people use to run their businesses. Appaca is different from general vibe coding tools. The goal of Appaca is to give users a user experience, rather than a builder experience. All apps built on Appaca runs directly in the platform without any concept of hosting, deployment or bug fixing. I want people who use Appaca to feel like the platform itself evolves and adapts to the way they work. Each tools they created should feel like it's part of Appaca. It's still in a very early stage. I am currently working on the right positioning and messaging. I hope you give it a go, and please let me know your honest thoughts. Thanks.

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, apps · Missing: mac, macos, cursor
99%99% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: created, started · Missing: supports, reddit linkedin, podcasting
94%94% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: apps, users, way · Missing: mobile apps, ios, personal
46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, ide · Missing: https docs, excited, just released
42%42% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, host, builder · Missing: plus, intuitive, reviews
34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: revenue · Missing: arr, mrr, profit
23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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