Building an AI Agent

Hacker News

Hello, my goal is to create an AI agent connected to each component of a software project (backend, frontend, third-party APIs, etc.) to centralize the project context and prevent developers from having to constantly update it when other components change. The agent will also be able to update each software component with a simple prompt. One of the objectives is to have a centralized knowledge base that allows developers to work faster. I want to create a tool that goes beyond code generation and assists developers in all aspects of software development. Currently, I am developing a command-line interface (CLI) application that serves as a foundation for my idea. For any questions, you can contact me at hello@9cotopus.com.

Visit product View on Hacker NewsNov 22, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, context, code · Missing: mac, agents, macos

87%87% 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 · Missing: supports, reddit linkedin, podcasting

66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

44%44% 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: interface · Missing: plus, platform, intuitive

23%23% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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