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Vylor AI
Multi-repo AI engineering — at up to 8× lower token cost
Vylor is a cloud-based AI engineering workspace for your entire multi-repo architecture. Work through engineering problems with AI like another engineer who already understands your codebase. Vylor connects the relevant parts of your system so you can explore solutions, make technical decisions, and iterate in real time. Move from idea to implementation across APIs, frontends, and infrastructure, with up to 8× lower model costs.
We started Vylor with a simple philosophy: how can people and AI work better together?
Initially, I imagined AI taking complete engineering tasks from start to finish. We experimented with that approach quite a bit, and it works surprisingly well, until it doesn't. AI will eventually make a decision you wouldn't have made, miss something you already knew mattered, or take the implementation in a direction you don't want.
I realized I didn't need AI to disappear and come back with a perfect solution. I needed the iteration loop to be fast.
Let AI investigate the codebase, write the boilerplate, implement the functions, wire the APIs, and make the changes. I'll bring the system knowledge, priorities, and technical judgment. We'll work through the solution together and I'll decide when it's ready.
That's what Vylor became: a way to work through engineering problems with AI, rather than waiting for AI to finish them for you.
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About Vylor AI on Product Hunt
“Multi-repo AI engineering — at up to 8× lower token cost”
Vylor AI was submitted on Product Hunt and earned 4 upvotes and 1 comments, placing #33 on the daily leaderboard. Vylor is a cloud-based AI engineering workspace for your entire multi-repo architecture. Work through engineering problems with AI like another engineer who already understands your codebase. Vylor connects the relevant parts of your system so you can explore solutions, make technical decisions, and iterate in real time. Move from idea to implementation across APIs, frontends, and infrastructure, with up to 8× lower model costs.
Vylor AI was featured in Software Engineering (42.9k followers), Developer Tools (517.6k followers) and Artificial Intelligence (476.1k followers) on Product Hunt. Together, these topics include over 201.2k products, making this a competitive space to launch in.
Who hunted Vylor AI?
Vylor AI was hunted by Ahmad Baraka. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Vylor AI stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Ahmad Baraka
Hey everyone! 👋 I'm Ahmad, founder of Vylor.
We started Vylor with a simple philosophy: how can people and AI work better together?
Initially, I imagined AI taking complete engineering tasks from start to finish. We experimented with that approach quite a bit, and it works surprisingly well, until it doesn't. AI will eventually make a decision you wouldn't have made, miss something you already knew mattered, or take the implementation in a direction you don't want.
I realized I didn't need AI to disappear and come back with a perfect solution. I needed the iteration loop to be fast.
Let AI investigate the codebase, write the boilerplate, implement the functions, wire the APIs, and make the changes. I'll bring the system knowledge, priorities, and technical judgment. We'll work through the solution together and I'll decide when it's ready.
That's what Vylor became: a way to work through engineering problems with AI, rather than waiting for AI to finish them for you.
Try it out:
Test directly in our sandbox: vylor.ai/try
Connect your stack & use code PRODUCTHUNT5 at checkout for a $5 credit to unlock advanced flagship models on your features.
I'm really curious to see whether other engineers work this way too. 🚀