Alternatives
Products that do what Polycode does
One prompt. Every model. One answer - with receipts.
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Hi all! I normally work on the PyTorch project but I've been on baby leave for the past month, so I've been playing around with AI as a user rather than a framework implementor. I really liked the agent experience with Claude Code, but I couldn't really justify spending so many dollars on API costs for random side projects. I already pay for a Claude Pro subscription though, and it turns out you can simulate many of Claude Code's features with an MCP. If you have a Pro subscription, check this out! I think it really captures the Claude Code experience quite well, without forcing you to pay…
2025 · github.com
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Hi, we're Sergey and Serafim. We've been building dev tools at 21st.dev and recently open-sourced 1Code (https://1code.dev), a local UI for Claude Code. Here's a video of the product: https://www.youtube.com/watch?v=Sgk9Z-nAjC0 Claude Code has been our go-to for 4 months. When Opus 4.5 dropped, parallel agents stopped needing so much babysitting. We started trusting it with more: building features end to end, adding tests, refactors. Stuff you'd normally hand off to a developer. We started running 3-4 at once. Then the CLI became annoying: too many terminals, hard to…
Jan 2026 · github.com
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One key to access every coding model in 3 flat prices
May 2026 · devpass.llmgateway.io
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Hey HN! I built Retain as the evolution of claude-reflect (github.com/BayramAnnakov/claude-reflect). The original problem: I use Claude Code/Codex daily for coding, plus claude.ai and ChatGPT occasionally. Every conversation contains decisions, corrections, and patterns I forget existed weeks later. I kept re-explaining the same preferences. claude-reflect was a CLI tool that extracted learnings from Claude Code sessions. Retain takes this further with a native macOS app that: - Aggregates conversations from Claude Code, claude.ai, ChatGPT, and Codex CLI - Instant full-text…
Jan 2026 · github.com
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Hi HN, I was once given the advice: Don't waste expensive frontier model credits (GPT/Claude/etc.) on bulk work. Send the boring, repetitive, high-volume jobs to a smaller model, and save the expensive prompts for when you actually need frontier-level reasoning. I complained and told my manager that I shouldnt have to think about using certain models for certain coding tasks, and that one model should handle everything. Well, here we are anyway. If anyone needs a place to absolutely abuse an LLM with high-volume tasks, come beat ours up at https://yolo-auto.com. Here are…
Jul 2026 · yolo-auto.com
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Hey HN, founder of Peony here. Most founders use DocSend to share investment or sales docs and have to pay $65 to $300 a month to get the security and analytics features. It pains me to see startups getting ripped off when the availability of technologies such as Clickhouse makes real time analytics almost a trivial feature to implement in 2024. We think it's time to end the carnage and democratize the technology. We set ourselves a high bar: we don't want to build another DocSend - we want it to be a far more superior product and also 10x cheaper. After a couple of months of work, I'm proud…
2024 · peony.ink
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Are you spending hundreds of dollars a month on AI coding costs? I built European Swallow AI, an API that uses reasoning models (Claude, Deepseek) for thinking and cheaper specialized coding models (Qwen, Grok) to write code, so you can save token costs while still getting high quality code. With an OpenAI formatted endpoint you can try European Swallow in Cursor, Typing Mind, Xibe AI and your own custom apps. During testing, European Swallow scored 80.5% on Big Code Bench and over 90% on the HumanEval+. It averaged $2.60 per million tokens compared with the $15 per million output tokens of…
Oct 2025 · europeanswallowai.com
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StackKit▲3AI prompts and automation workflows built for entrepreneurs
Jul 2026 · stackkit.madethis.app
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Mintlify Pro costs 250 USD per month. We wanted something similar (AI assistant and nice UI), but fully customizable and cheap. So we built GibsonAI docs in 1 day for about 50 USD. How we did it: Used Lovable for UI components + rendering MDX beautifully (Markdown stored in GitHub). Built an AI Agent for docs using Agno + Memori → personalized Q&A and “smart educator.” Stored embeddings in LanceDB and metadata in our SQL DB. Bonus: We can share our reusable design templates and source code so you can deploy on Vercel (or anywhere) and skip Lovable costs. Would love feedback on what features…
Sep 2025 · gibsonai.com
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