TL;DR: We are excited to release our PRP and can’t wait to hear your thoughts. You can download the app here and join our Discord here. Keep reading for more info!

First off - thank you all for your support and feedback as we’ve been developing Memex! 

This PRP does not yet meet our bar for a product we’d put in “the wild”. But we’ve matured our product direction to something we have conviction in, and this PRP is designed to help us further sharpen focus with the help of your usage and feedback.

Memex Product Direction

We are focused on the needs of “scientific professionals” – by which we mean professionals whose skill sets are primarily quantitative and domain-specific in nature. Think “Data scientist”, “Applied Researcher”, “Postdoc”, etc. In conversations with >150 of these types of individuals, we’ve observed a pattern: operational tasks are a time-consuming drag on their workflow – such as dependency management, deployment, creating REST APIs, bootstrapping projects etc.

Our product direction is about finding ways to automate such tasks in a low-friction, easy-to-use tool, and we believe that generative AI capabilities can be an enabler for the solution. 

When we think longterm about the product, we think of it as a “synthetic engineer” that can assist any scientific professional with their work. Imagine the situation where you’re on a team and you need to collaborate with an engineer on something – say, deployment, managing dependencies, adapting your code and artifacts to ensure they align to the interfaces required by the engineering team, etc. Or imagine you’re a researcher and you want to ensure your code follows best practices for reproducibility, or that you want to reproduce someone else's code in your environment. In these situations, our ambition is for Memex to be like a “synthetic engineer” that can automate these tasks so you can focus on what you do best.

Our vision is to accelerate scientific and technological research by amplifying the productivity of the people doing it. We believe that – if successful – that would be beneficial for humanity.

PRP Research Questions

Our primary goal with the PRP is to learn. To that end, we’ve formulated three research questions we aim to answer with it:

1. What tasks would be (most) valuable for Memex to automate for scientific professionals?

2. What is the most ergonomic way for scientific professionals to adopt + use our product?

3. What are the failure/success modes for valuable tasks?

There’s lots of exciting research momentum in the field of AI Agents, and we expect there’s a lot of scope for helping scientific professionals with agentic systems. That said, we want to avoid “boiling the ocean” with a tool that is mediocre at a lot of tasks, and instead want to identify the most valuable tasks to solve, create a benchmark that represents those tasks, and iteratively improve our system against that benchmark to meet acceptable levels of performance for users.

Current Capabilities

Our current product uses an agent system we developed that interacts with your local machine to execute tasks. The product supports gpt-4o as a base model, with both OpenAI and Azure as providers. 

Some example use cases it can perform:

• Create a simple FastAPI application

• Install an OSS model locally and use it for some task

• Troubleshoot a dependency management issue

• Clone and run a github repo

• Dockerize a project

We look forward to hearing what you use it for.

Caveats

There are known issues with the research preview we’re actively working on. We would love your thoughts on any of them if you’re interested in discussing with us.

• Performance gaps: across the board, the system experiences failures. The following are known failure modes we are actively addressing:

  • Out of date code: The PRP does not have a retrieval API connected with version specific documentation of code. Hence, the code written is dependent on the LLM, which is often out of date. We’ve experimented with a retrieval API that addresses this but have not integrated it yet.

  • Reasoning limitations: The LLMs are not great at reasoning. We are exploring methods to add “system 2” reasoning capabilities on top of the LLMs, such as tree search, re-ranking, and RL approaches.

• Safety: the system has known safety limitations that we caution against:

  • Secrets: we do not yet have a secrets management solution. So if you have a use case that involves any secrets, the system may read your secrets. All access happens through the OpenAI API – which OpenAI does not train on – but it’s never a good practice to have unencrypted keys go over the open internet. We are exploring some options to integrate with KeyChain / 1Password, etc.

  • Privilege: the system is not running in a container – it has direct access to your system shell. Hence, it is theoretically capable of deleting files or changing configurations on your machine. We’ve never experienced this in testing, but we also do not have explicit safeguards against it. We are working through some ways to address this issue and would love your thoughts on them if you’re interested in discussing it with us.

How to get started

1. Download the app: Download from here: memex.tech

2. Join our Discord: Join other PRP users to explore walkthroughs, get help troubleshooting, and build community: https://discord.gg/DZQDRDuk3m

3. Explore FAQs: We are always available in the Discord, but explore some FAQs here: docs.memex.tech

We look forward to your feedback!

Ever forward,

Memex Team