Your best thinking shouldn't disappear when an AI chat ends. Review Markdown plans, research and specs, leave feedback on exact passages, and use comment IDs to direct your next agent session. Keep decisions and open questions in project files you can revisit. Try the free sample demo: no sign-in, project upload or AI API key. Demo comments are temporary; agents run outside the demo. Built with GPT-6 Astra. Public self-hosted release planned.
What became possible in your product with Astra that was not practical before?
Maker
**From idea to product:** Honestly, I knew Astra could help me code. I did not expect it to help carry the work from ideation and architecture through implementation, refactoring, usability reviews, sales pitches and launch content. Astra led the build, with supporting models and tools where useful.
**Depth beyond a prototype:** We could keep questioning the quality—permissions, persistence, recovery and the experience of an ordinary user. Working towards enterprise-grade engineering became practical much earlier, while proven enterprise readiness still needs further evidence.
**Autonomy made the difference:** Its real power became visible when I stopped directing every step. I gave it the outcome, boundaries and acceptance expectations, then let it work. My role shifted towards challenging assumptions and judging the product.
I am truly happy with the experience. What amazed me was how much more of the complete product journey I could take on.
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Maker
📌
Hi Product Hunt — I’m Aashish, creator of ReviewWithAI, by BriqVent.
Have you ever started a fresh AI session and found yourself explaining decisions you thought were already settled?
That frustration is why I built ReviewWithAI. Useful thinking gets scattered across chats, documents and reviewer feedback. The next draft moves forward, but the reasoning behind it becomes harder to find.
ReviewWithAI gives that work a reviewable record. Browse your Markdown plans, research and specifications. Highlight the exact passage you want to challenge. Leave a comment, find what remains open across files, and use selected comment IDs to focus the next agent session.
In the local workflow, you direct your existing Codex or Claude session to retrieve the relevant feedback, revise and reply. You decide what to accept. Keep useful conclusions in project documents so a fresh session has somewhere concrete to start. Continuity depends on maintaining that record and giving your agent the relevant context.
Try it today: open a sample, select a sentence, leave a comment and copy its ID. The free public demo requires no sign-in or AI API key. It uses supplied samples and temporary comments private to your session; it does not run agents or accept your project uploads. Please keep sensitive information out of demo comments.
GPT-6 Astra led this independent build in Codex, with supporting contributions from other models. The public self-hosted release is planned.
What gets lost most often in your AI workflow: the feedback, the decision, or the reason behind it?