Alternatives
Products that do what Making AI chat sessions durable to network failures does
The experience with AI chat apps can be a bit fragile — there's no resilience to network failures, and responses aren't deterministic like traditional search. As Garry Tan put it (https://x.com/garrytan/status/1927038513108701662), "It feels like catastrophic data loss when a given response comes back and fails halfway, and then the next retry is not as good." Vercel recently released a "resumable-stream" package (https://github.com/vercel/resumable-stream) to solve this problem using Redis as a backing store. I felt that we could simplify the…
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
- 11
Trace, evaluate, and improve AI agents in production
30d ago · telerik.com
- 12
- 13
- 14
- 15
- 16
- 17
- 18IB
Hi everyone, I’ve been using ChatGPT to analyze my journal entries and to reflect with. It works great, I really liked it. I’ve managed to gain some good insights about myself and made improvements. However, there are a few problems: - ChatGPT only remembers key facts about you, it has limited memories - ChatGPT couldn't recall the content of conversations you had with it - For individual ChatGPT products, your private conversations might be used to train future models (see: https://help.openai.com/en/articles/5722486-how-your-data-is...) So, I decided to build my…
2025 · pensiv.me
- 19
- 20CS
If you have developer documentation and want to boost your community with AI this is for you! Just pull in the base url of the site add some customization and get a sharable link for your chat, link it anywhere you want. I saw this trend in some places like gcp with Gemini, or Langchain or Supabase ask ai, but they're all custom-implemented solutions, not everyone wants to advocate developer resources to create the rag, deploy it and maintain it, you just want devs to build with your stuff, the more they can do the better, the quicker the better, and if they get a smooth experience while…
2024 · explainit.mzslabs.com
- 21SA
Hi. My name is Eric Brandon and I’ve built an AI chat app that feels really different. While you talk with an AI model in a chat pane, a second AI model is reading over the conversation and seeking out useful, interesting, surprising, amusing, and fact-checking information that wouldn’t have appeared in the main chat. You can read those “discoveries” on their own, or click them into your main chat to steer the conversation in a new direction. This is based on the observation that talking to smart people is usually more enjoyable, interesting, and informative than talking to a smart AI.…
Jan 2026 · github.com
- 22AP
We’ve been power users of AI tools for the past year, and we kept running into three constant frustrations: 1. Too many subscriptions – Paying separately for OpenAI, Anthropic, Perplexity, and others quickly adds up. 2. Losing memory & context – Switching between models or platforms means you start over each time. 3. Privacy concerns – With most closed-source models, your data may be stored or used for training. That’s not acceptable for sensitive or professional use cases. So we built AgentSea: a private and safer chat interface where you can access the latest models, agents, and tools in…
2025 · agentsea.com
- 23IO
Hello so I finally released the new version of aidev.codes. It is extremely alpha, has not been thoroughly tested at this point. Its quite different from the previous version. The new aidev.codes: - is buggy but actually works (compared to the old version) - has a ChatGPT-style interface (and uses the chatgpt-turbo model which is actually better than the other models for code) - integrates the stability.ai API to automatically generate images - can create a simple but fully customized and interactive web page and instantly host it for you - can optionally host your page on a custom subdomain…
2023 · aidev.codes
- 247D
hi all. i’ve been shipping a small open project that tries to answer that question with evidence, not vibes. in 70 days it reached \~800 stars. the core claim is simple: many AI failures are not noise. they repeat because the geometry and ordering underneath are stable. if so, we should be able to name each failure mode, set acceptance targets, and stop shipping the same bug twice. ### what it is * a compact Problem Map of 16 reproducible failure modes in RAG and agents. * each item has a minimal fix and measurable gates. examples: * Semantic ≠ Embedding: metric and normalization mismatch.…
2025 · github.com
Ranked by how close each launch is in meaning, then by votes. Refine with a description →