Forge – Cline/Roo Alternative on the CLI

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Hi HN, I am excited to introduce Forge, an open-source AI pair programmer designed to work right from the terminal. You can connect it to any backend of your choice or use our provider (free for now). I have been working hard at it and would love to get some feedback about the product. Why did I build Forge? The main reason was that I personally keep AI disabled on my IDE because it interferes with my train of thought. Current IDEs are powerful but too jarring for my taste. I hate the ridiculous animated way of applying diffs and prefer the AI to operate in the background in a separate git worktree. CLI is also powerful because I don't need to create every single tool as an MCP; I can directly install the binary and let the agent run. Recommended Workflow with Forge: Anyone who wishes to try Forge, should install it via NPM, create an account on https://antinomy.ai/app and then start the Forge interactive session by typing `forge` on the terminal. I then use the `/plan` command to switch to the plan mode and use it to iterate on a plan. Once ready, I switch to `/act` mode and tag that plan using sending a `@<TAB>` key on the terminal, then let it do its job. I would also recommend using git worktrees, so that while Forge is doing work, I am not waiting for it to finish and I can do something else. Hope you like what I have made and would love to get feedback here: https://github.com/antinomyhq/forge/issues Thank you all!

Visit product View on Hacker NewsApr 27, 2025

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

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Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting

89%89% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, io · Missing: https docs, just released, exist

61%61% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: personal, way, para · Missing: mobile apps, ios, entrepreneurs

56%56% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: arr, active · Missing: mrr, revenue, profit

12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

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

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