HackerReposA FIELD GUIDE TO OPEN SOURCE
ProSponsor the shelf♧ 0
← Back to top all-time
Significant-Gravitas
AutoGPT
Python2023–2025
Significant-Gravitas / AutoGPT

AutoGPT

AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.

AI & Machine Learning
Explore on GitHubRead Hacker News discussions
25Distinct people
28Mentions
0Explicit recommenders
188KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month28 dated mentions

Observed mentions: 2023-04-02 17:39:36 UTC to 2025-06-12 12:49:17 UTC.

0510152023-04-01 00:00:00 UTC to 2023-05-01 00:00:00 UTC (exclusive): 17 mentions; 7 submissions, 10 commentsApr 20232023-05-01 00:00:00 UTC to 2023-06-01 00:00:00 UTC (exclusive): 5 mentions; 1 submissions, 4 comments2023-06-01 00:00:00 UTC to 2023-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-07-01 00:00:00 UTC to 2023-08-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2023-08-01 00:00:00 UTC to 2023-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-09-01 00:00:00 UTC to 2023-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-10-01 00:00:00 UTC to 2023-11-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2023-11-01 00:00:00 UTC to 2023-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-12-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2024-02-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2024-02-01 00:00:00 UTC to 2024-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-03-01 00:00:00 UTC to 2024-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-04-01 00:00:00 UTC to 2024-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-05-01 00:00:00 UTC to 2024-06-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsMay 20242024-06-01 00:00:00 UTC to 2024-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-07-01 00:00:00 UTC to 2024-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-08-01 00:00:00 UTC to 2024-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-09-01 00:00:00 UTC to 2024-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-10-01 00:00:00 UTC to 2024-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-11-01 00:00:00 UTC to 2024-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-12-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-01-01 00:00:00 UTC to 2025-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-02-01 00:00:00 UTC to 2025-03-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025-03-01 00:00:00 UTC to 2025-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-04-01 00:00:00 UTC to 2025-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-05-01 00:00:00 UTC to 2025-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-06-01 00:00:00 UTC to 2025-07-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsJun 2025

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Apr 20232023-04-01 00:00:00 UTC2023-05-01 00:00:00 UTC17710
May 20232023-05-01 00:00:00 UTC2023-06-01 00:00:00 UTC514
Jun 20232023-06-01 00:00:00 UTC2023-07-01 00:00:00 UTC000
Jul 20232023-07-01 00:00:00 UTC2023-08-01 00:00:00 UTC101
Aug 20232023-08-01 00:00:00 UTC2023-09-01 00:00:00 UTC000
Sep 20232023-09-01 00:00:00 UTC2023-10-01 00:00:00 UTC000
Oct 20232023-10-01 00:00:00 UTC2023-11-01 00:00:00 UTC110
Nov 20232023-11-01 00:00:00 UTC2023-12-01 00:00:00 UTC000
Dec 20232023-12-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
Jan 20242024-01-01 00:00:00 UTC2024-02-01 00:00:00 UTC110
Feb 20242024-02-01 00:00:00 UTC2024-03-01 00:00:00 UTC000
Mar 20242024-03-01 00:00:00 UTC2024-04-01 00:00:00 UTC000
Apr 20242024-04-01 00:00:00 UTC2024-05-01 00:00:00 UTC000
May 20242024-05-01 00:00:00 UTC2024-06-01 00:00:00 UTC110
Jun 20242024-06-01 00:00:00 UTC2024-07-01 00:00:00 UTC000
Jul 20242024-07-01 00:00:00 UTC2024-08-01 00:00:00 UTC000
Aug 20242024-08-01 00:00:00 UTC2024-09-01 00:00:00 UTC000
Sep 20242024-09-01 00:00:00 UTC2024-10-01 00:00:00 UTC000
Oct 20242024-10-01 00:00:00 UTC2024-11-01 00:00:00 UTC000
Nov 20242024-11-01 00:00:00 UTC2024-12-01 00:00:00 UTC000
Dec 20242024-12-01 00:00:00 UTC2025-01-01 00:00:00 UTC000
Jan 20252025-01-01 00:00:00 UTC2025-02-01 00:00:00 UTC000
Feb 20252025-02-01 00:00:00 UTC2025-03-01 00:00:00 UTC101
Mar 20252025-03-01 00:00:00 UTC2025-04-01 00:00:00 UTC000
Apr 20252025-04-01 00:00:00 UTC2025-05-01 00:00:00 UTC000
May 20252025-05-01 00:00:00 UTC2025-06-01 00:00:00 UTC000
Jun 20252025-06-01 00:00:00 UTC2025-07-01 00:00:00 UTC101

What Hacker News says

28 sources
incomingpain·Jun 12, 2025
>I’ve been using Cursor and other AI coding tools, and I noticed a pattern: they go from requirements → code → fix when it breaks. It works, but it’s reactive. I write what I want, it half-understands, breaks something, and I patch it. This is last generation AI coding. I was literally using qwen2.5 coder instruct yesterday; so i havent moved on yet. Next gen is with similar options to: https://github.com/Significant-Gravitas/AutoGPT or https://www.langchain.com/agents honestly havent tried either of those. >What I wish existed is a flow like this: Requirements → Generate Tests → Generate Code → Run Tests Isnt that what github copilot is doing? This is what i didnt like about it; but im sure more talented devs appreciate what it's doing. >Would you use something like this? Would you pay for it (e.g. Cursor-level pricing, ~$20/mo)? What wo
Read the rest
uld break this in your workflow? Why not go for the sky? Requirements -> fully generated project that just works and i dont care how it got there. Scotty on the enterprise was just writing prompts and never looking at unit tests.
In Ask HN: Would You Use a Dev Tool That Does "Requirements → Tests → Code"?
oceanparkway·May 28, 2024Submission

Show HN: Autospec – open-source agent that generates E2E tests for your web app

Hi HN, I'm excited to share some early tinkering on a project, autospec, an open-source QA agent for web applications. Right now it's not fully packaged for use, but I wanted to get the idea out early and am looking for design feedback, suggestions, and open source collaborators to join in. I wrote it over memorial weekend :) autospec uses vision and text language models to explore and generate commonsense e2e tests for web applications. The goal is human-like evaluation: assessing the entire UI as a user would, making decisions based on the actual state of the application at each step, with zero initial configuration, and the ability to immediately adapt to new features. Why I Built It: I've experienced the difficulty in building the right amount of automated tests and at the right layer of abstraction to both provide good coverage, avoi
Read the rest
d flakiness, and avoid constant rewrites when implementation changes. This is the first AI-driven application I've built. I was inspired by a couple of things: * SWE-agent's [1] focus on agentic performance * backend-GPT's README rant [2]: "The proper format for business logic is human intelligence." * zerostep [3], autogpt [4], and other browser-controlled AI projects Potential Next Steps: * Save passing specs as playwright code and only fallback on spec failure to the AI agent, to see if the test can be self-healed according to the original spec. * Create a curated benchmark of both common open source web apps that should pass, and versions with introduced bugs * NPM package to run like `npx autospec --url https://example.com` * Github action and Vercel checks API integration to run on preview deployments * Handling app auth securely+easily * Continue exploring the balance between vision UI interpretation and DOM analysis [1]: https://github.com/princeton-nlp/SWE-agent [2]: https://github.com/RootbeerComputer/backend-GPT [3]: https://github.com/zerostep-ai/zerostep [4]: https://github.com/Significant-Gravitas/AutoGPT Thanks! Zach
8 points · Open discussion
traverseda·May 15, 2023
>They're not autonomous. They won't be autonomous. https://github.com/Significant-Gravitas/Auto-GPT >This program, driven by GPT-4, chains together LLM "thoughts", to autonomously achieve whatever goal you set. As one of the first examples of GPT-4 running fully autonomously, Auto-GPT pushes the boundaries of what is possible with AI. >As an autonomous experiment, Auto-GPT may generate content or take actions that are not in line with real-world business practices or legal requirements. It is your responsibility to ensure that any actions or decisions made based on the output of this software comply with all applicable laws, regulations, and ethical standards. The developers and contributors of this project shall not be held responsible for any consequences arising from the use of this software.
In Uncensored Models
NumberWangMan·May 3, 2023
I don't think that doing the math by hand to simulate a machine intelligence makes it not intelligent, any more than doing a simulation of all the electrochemical signals in a human brain by hand would make a human not intelligent. Aside from the infeasible amount of time it would take, it's the same thing. As for autonomy, LLMs don't have autonomy by themselves. But they can be pretty easily combined with other systems, connected to the outside world, in a way that seems pretty darned autonomous to me. (https://github.com/Significant-Gravitas/Auto-GPT). And that's basically a duct-tape-and-string version. Given how new these LLMs are, it's likely we're barely scratching the surface.
In Google DeepMind CEO says some form of AGI possible in a few years
cube2222·Apr 25, 2023
It's a really cool area of putting AI in a feedback loop (langchain-like) with its own tools, which I think is where the magic happens, and where we'll see much more happening in the future. This should really super-charge engineers doing stuff in areas where they're not super-comfortable in, but comfortable enough to verify the AI isn't doing anything stupid. I made something vaguely similar for your local terminal[0] and other locally-available tools. The idea is to give you a chat with an assistant that can use these local tools. Here it's Python for data analysis, in my case it's more "give it access to your terminal, so it can answer questions / do tasks on your local machine" which is something web-based options can't do right now. I.e. ask it about your system details (processes, wifi) or to do things (configure something). Have it
Read the rest
automatically run the relevant commands, analyze the output, and respond either in natural language or i.e. plot a chart. AutoGPT[1] is another very interesting project in this area. [0]: https://github.com/cube2222/cuttlefish [1]: https://github.com/Significant-Gravitas/Auto-GPT
In ResearchGPT: Automated Data Analysis and Interpretation
break_the_bank·Apr 19, 2023
This takes in the entire README here https://github.com/Significant-Gravitas/Auto-GPT#-installati... and converts it into something that you can run on your system in much fewer steps! If you have Docker running & the CLI installed; Kurtosis allows you to spin up the entire thing with just `kurtosis run github.com/kurtosis-tech/autogpt-package` (think of this as install on brew) While the run command is `(echo "python -m autogpt" && cat) | kurtosis service shell autogpt autogpt` I plan on adding support for Weaviate & Milvus running locally. So that instead of Redis you can do one of those backends if you want to. This takes a lot of heavy lifting away from the user & unlike a docker compose you can spin up things conditionally based on the parameter passed. More-ever you don't need to have the compose file locally.
In Show HN: Run Auto-GPT locally in 2 lines

Showing the 15 most recent of 28 sources. Enable JavaScript to search and browse every indexed mention.

MAKE YOURSELF AT HOME

A few shortcuts

/
Search the collection
?
Open this guide
Esc
Close dialogs and navigation

Your saved repositories and interests stay in this browser.