... everyone While working with Claude Code in VS Code , I ran into a small but frustrating workflow issue. For months I ve been using Antigravity , which allows you to select code and press Ctrl + L to instantly send that snippet as context to the agent. Even better, you can repeat this multiple times in the same message, and the UI provides context chips that let you trace the referenced code easily. However, when I started using the Claude Code VS

... each model's analysis, AIFlow produces a Cross-Model Synthesis a structured reflection on how the models interact: Where do multiple models converge on the same leverage point? (That convergence is your highest-priority action.) Where do models create tension with each other? (Those tensions

... Last year in Unicorns Journal we published an interview with Sergey Bakaev , where we unpacked first-time fundraising strategy expectations vs reality, common mistakes, and what founders often underestimate when raising capital for the first time. It turned into a very honest conversation. This year, I want to continue the series but shift the focus to something even more sensitive. Co-founder dynamics. Over the past few years, I ve noticed that the most difficult tensions

... that writes for you, optimizes you, or turns you into a better-performing version of yourself. It s a system designed to help people  sound like themselves again especially in places where self-presentation has become tense, filtered, or oddly generic. The work sits at the intersection of language, presence, and honest self-expression. Less generate, more  clarify . Less polish, more coherence. The goal isn t to impress strangers it s to remove the static that creeps ...

... problem turns into an operating one. That also makes me wonder: Is US-first still the right default for AI products? Or do some products actually benefit from starting in smaller, simpler markets? No strong conclusion yet just a tension I keep running into. Curious how others are thinking about this. Comment from CY(@lightfield): @dushyant_khinchi   @josie_oy  Curious how others are thinking about this in practice. If not US-first (or not only US), what other ... ... speed, but breaks quickly at scale. Language isn t the hard part anymore it s things like performance on slower networks, local expectations around signup, privacy, and even payment friction. Tools that feel simple and accessible globally tend

... According to the 2025 @Stack Overflow Developer Survey (49,000+ participants), @VS Code and @Visual Studio remain the most used dev environments, despite the rise of subscription-based, AI-enabled code editors @Cursor  and  @Windsurf  among others. Both maintain their top spots relying on extensions as optional, paid AI services like @Github Copilot and @Kilo Code . Curious which IDE the Product Hunt community uses the most? Comment from Chilarai M(@chilarai): @fmerian  I'll need ... ... down. Another person on our team uses @opencode  instead of Claude Code, and I hear great things. I also hear that @Github Copilot  has gotten quite a bit better. So I wouldn't mind going back to VS

... talk about your brand, then turns those mentions into usable intelligence: who said what, where, with what tone, and how that changes over time. It monitors platforms like ChatGPT, Claude, Gemini, and Perplexity, runs custom prompts at scale, benchmarks competitors, and alerts you when something moves so you can respond fast. In short, Thirdeye shows you the story AI is telling about your brand and helps you steer it. AI assistants and answer engines are fast becoming the front door ... ... distribution is shifting. Either way, the contest is now on the AI surface itself. Thirdeye monitors that surface. New demand hubs are growing. Perplexity has surged to roughly 20+ million MAUs with hundreds of millions of monthly visits and tens

... Just dropped a new integration for developers working with real-world documents and vector search: Tensorlake + Qdrant = structure-aware retrieval at scale. Instead of flat blobs, you can: Parse PDFs into labeled fields extracting metadata like names, dates, balances, etc Embed with semantic structure Store and query with Qdrant filters that actually match your use case Built for RAG, document agents, contract intelligence, and anyone tired of lossy parsing. Full blog: https://www.tensorlake.ai/blog/a... Open to feedback or ideas ...

... What s New We just launched a native integration between LangChain and Tensorlake! Now you can pass unstructured documents to a LangGraph agent and trust that parsing, chunking, and field-level accuracy are handled by Tensorlake

... Signatures might feel like a formality until they delay a claim, break compliance, or derail a deal. That s why we built Signature Detection into Tensorlake, giving you the power to track and act on signature presence inside your documents: Basic Detection Detects whether any signature is present Returns bounding box coordinates and presence/absence flags Contextual Detection Associates signatures with names and roles (e.g., buyer, seller, agent) Extracts structured fields like signer_name and signature_date Works alongside your schemas ...