Secure your GitHub account with two-factor authentication. (It is recommended to use the GitHub Mobile app.). - Source: dev.to / about 2 years ago

If Git is the #1 Version Control System, GitHub is the #1 cloud service for Git. It allows code issues reporting, code-reviewing and, most importantly, it will keeps the repository on the cloud if your cellphone suddenly explodes. Microsoft has been doing a great job on the GitHub app: It has most of the features available on GitHub desktop. Edit files, submit, approve and comment on pull requests, everything from... - Source: dev.to / over 4 years ago

Peer Review : Instead of meetings, advance reading, some kind of Microsoft Office document versioning and comments, a git pull request is fundamentally better in every way, and easier too. GitHub even has a mobile app to make peer review as frictionless as possible. - Source: dev.to / over 4 years ago

Users may also be interested in future development around the GitHub mobile client, which currently does not support being able to edit or contribute new files. For now, people can use the app to post "LGTM" to PRs, add thumbs-down emojis to issues, and get notified when your PRs are rejected. - Source: dev.to / over 4 years ago

Interacting with GitHub from your mobile : Technical post – Showing how to do some common procedure using the official GitHUb app on a mobile (Android) – Example of processes : Modifying a file, Creating a new branch, creating a new Pull Request, Reviewing a Pull Request, merging a Pull Request – Nice to have: Some small videos for each procedures to allow the user the see them done "live" – Easy to write but I am... - Source: dev.to / about 5 years ago

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 / 9 days ago

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 / 28 days ago

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

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

Same approach works with Langfuse, Phoenix, Braintrust, or your existing OTel pipeline — the metadata.userId pattern is the universal part. - Source: dev.to / about 2 months ago