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I used Emergent to build and prepare a website intended for a live launch. The concept of the platform is promising and the early build experience suggested it could be a very useful tool. However, over several days I encountered repeated technical and deployment problems that ultimately prevented the site from going live.
During development I experienced:
Deployments reporting as successful while requested changes did not appear on the live site
Inconsistent behaviour between preview and production environments
Multiple requests needing to be repeated before partial fixes were applied
Credits being consumed while trying to resolve issues that appeared to be platform-related rather than user error
A major concern was the level of customer support during this period. Responses were often delayed, acknowledgements did not translate into timely resolution, and there were gaps in communication while the work was effectively at a standstill.
Most recently, the build engine itself indicated it was unable to resolve one of the problems, leaving no clear path to complete deployment despite continued attempts.
In preparation for launch, I had already invested in supporting services such as voice generation through 11 Labs and a Canva subscription to create promotional materials linked to the build. These were arranged specifically for rollout, so the inability to achieve a stable deployment resulted in additional wasted expense beyond the platform itself.
As someone trying to move from development to an operational launch, this created a significant setback in both time and cost despite sustained effort to work through the issues.
The overall idea behind the platform is strong, but in my experience the reliability of deployment, consistency of updates reaching production, and speed of support response were not yet dependable enough for a live environment.
โข Slow or inconsistent customer support responses when issues arise. โข Acknowledgement of problems does not always lead to timely resolution. โข Deployment process can report success even when changes have not actually gone live. โข Repeated troubleshooting cycles may consume credits without resolving the underlying issue. โข Communication gaps during fault resolution can leave projects at a standstill. โข Limited transparency on what is happening behind the build/deployment pipeline when errors occur. โข Platform can feel difficult to rely on for time-sensitive or production launches.
Based on our record, Gitpod seems to be more popular. It has been mentiond 76 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
# Example of setting up a Gitpod workspace # Open your repository in Gitpod with one click Https://gitpod.io/#https://github.com/your-repo. - Source: dev.to / over 1 year ago
For my part, I often develop on cloud environments. I was lucky to come across Gitpod in 2019 and I have been using it everyday since, whether for Zenika projects, personal projects or open source projects. - Source: dev.to / about 2 years ago
We will use VScode workspace running on Gitpod as an IDE, you can use VScode on your local machine but you need to skip steps or change some details related to Gitpod. We will begin by setting up the workspace, preparing the requirements, and installing the dependencies. - Source: dev.to / almost 2 years ago
Next, we need to install Docker by downloading it from the official website if you haven't already. Alternatively, use a free online platform like Gitpod or a VPS to run a Docker instance, if possible. Otherwise, install it on your local computer. - Source: dev.to / almost 2 years ago
If you prefer instead to have a look at a fully working & effect-native app we've prepared a demo cli app that you can directly open in Gitpod or locally (if you prefer), you'll need to provide an OpenAI API Key in order to integrate with the OpenAI API. The demo app allows you to train a model via embeddings from a set of files and then allows you to prompt the trained model with questions. - Source: dev.to / over 2 years ago
GitHub Codespaces - GItHub Codespaces is a hosted remote coding environment by GitHub based on Visual Studio Codespaces integrated directly for GitHub.
Lovable - The world's first AI Fullstack Engineer
replit - Code, create, andlearn together. Use our free, collaborative, in-browser IDE to code in 50+ languages โ without spending a second on setup.
bolt.new - Prompt, run, edit, and deploy full-stack web apps
Codeanywhere - Codeanywhere is a complete toolset for web development. Enabling you to edit, collaborate and run your projects from any device.
AWS Cloud9 - AWS Cloud9 is a cloud-based integrated development environment (IDE) that lets you write, run, and debug your code with just a browser.