Engine – LLM agnostic Codex alternative

Hacker News

We built Engine with the belief that a lot of backlog type software engineering tasks could be handed off to a remote AI agent and completed async with little-to-no human involvement. Recently, a wave of new models and products has attracted a lot of attention to async coding agents so I wanted to share our approach! - To solve real engineering tasks for folks working on 'serious' projects we integrate tightly with Linear, Jira, Trello, and ClickUp and also both GitHub and GitLab. - We quickly realised that configurability and workflow was important so there are lots of ways to set up and interact with Engine. - Environment set-up is a pain at the best of times so we built an agent that helps out with this. - Engine runs on all frontier LLMs, including Claude 4, which seems increasingly important with the pace of progress and competition amongst the big labs! The free tier includes Claude 4 sonnet so would love for you to take Engine for a spin and let me know how it goes!

Visit product View on Hacker NewsMay 23, 2025

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

98%98% 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: including · Missing: supports, reddit linkedin, podcasting

69%69% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal

32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

26%26% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

24%24% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

23%23% predicted probability of success on AppSumo, 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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