Mimo Reviews

1. Rached Noureddin

   almost 3 years ago
   Mimo The Minimalistic looking app

   been using mimo for a time and finished Python course as a noob, i can say it's a good experience since they made the course like having a bike with third wheel which is great for home learners, your brain not ready to debug something you don't know, that stage also is tought as a last lesson, how to debug your program, my experience was all in all great, and this coming from me a Lazy Person :)

   🏁 Competitors: Free Code Camp, Codecademy, SoloLearn, LinkedIn Learning

   👍 Pros:    Easy to use|Solid learning method|Repetitive questions explaination|Constantly improving

   👎 Cons:    English language only

Langfuse Reviews

Mimo mentions (21)

• Recommend a mobile app to learn JavaScript - HTML and CSS as well.

  Mimo is an excellent learning app and beginner friendly. Source: over 3 years ago

• Is going to collage even worth it if AI is going to replace us anyways?

  Web and Python Development: https://getmimo.com (Checkout out the website version). Source: almost 4 years ago

• Supplement learning on my phone

  I think what you are looking for is: https://getmimo.com/ (there might be some similar ones). Source: almost 4 years ago

• 100 Days of Code : Day 1 to 5

  Mimo : an application, when I don't have too much time or don't have access to my PC. - Source: dev.to / almost 4 years ago

• React-Redux Roadmap Zero to Advanced: Part 1 🚀

  Mimo App: Learning to code can be easy and fun. Start learning now! (getmimo.com) Beginners can use this app to build your basic foundation on HTML, CSS, JS. Backend developers who deliberately suck at front-end can also use this app to get clarity on the basics. - Source: dev.to / almost 4 years ago

Langfuse mentions (28)

• Strands Agents + Langfuse Evaluations

  In this project we will build a Python banking assistant agent using Strands Agents and make it observable and continuously evaluated using Langfuse — step by step. - Source: dev.to / 3 days ago

• Best AI Monitoring Tools in 2026: LLM, Agent, and MCP Observability Compared

  Langfuse is the open-source standard for LLM observability. It traces every LLM interaction — prompts, completions, latency, token usage, cost — and provides the tooling to debug, evaluate, and optimize LLM applications in production. Think of it as "Datadog for LLM calls" with a focus on prompt engineering workflows. - Source: dev.to / 22 days ago

• What is an LLM evaluation harness? A deep dive into lm-eval-harness

  You're monitoring production traffic. You need Langfuse / Phoenix / Helicone / Braintrust for that. Online eval is a different problem class: implicit feedback, drift detection, hallucination rates on your data, not on HellaSwag. - Source: dev.to / about 1 month ago

• How to track LLM costs per customer in production

  Gateway or proxy attribution. A reverse proxy in front of the model-provider API records the request, computes the cost, and exposes per-customer breakdowns. Open-source options include Helicone, LiteLLM, Langfuse, and OpenLLMetry. Hosted equivalents serve as the AI cost observability layer for teams that want centralized visibility: LangSmith, Datadog LLM Observability, Arize Phoenix. Adds a network hop.... - Source: dev.to / about 1 month ago

• Per-user cost attribution for your AI APP

  Same approach works with Langfuse, Phoenix, Braintrust, or your existing OTel pipeline — the metadata.userId pattern is the universal part. - Source: dev.to / about 1 month ago