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gastownhall
gastown
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gastownhall / gastown

gastown

Gas Town - multi-agent workspace manager

25Distinct people
26Mentions
0Explicit recommenders
18.8KGitHub stars
REPOSITORY AT A GLANCE

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What it is

Gas Town - multi-agent workspace manager

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Where it is used

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

What people are saying

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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 month26 dated mentions

Observed mentions: 2026-01-02 03:41:51 UTC to 2026-09-02 14:12:26 UTC.

0510152026-01-01 00:00:00 UTC to 2026-02-01 00:00:00 UTC (exclusive): 14 mentions; 4 submissions, 10 commentsJan 20262026-02-01 00:00:00 UTC to 2026-03-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-03-01 00:00:00 UTC to 2026-04-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2026-04-01 00:00:00 UTC to 2026-05-01 00:00:00 UTC (exclusive): 4 mentions; 1 submissions, 3 comments2026-05-01 00:00:00 UTC to 2026-06-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 commentsMay 20262026-06-01 00:00:00 UTC to 2026-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-07-01 00:00:00 UTC to 2026-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-08-01 00:00:00 UTC to 2026-09-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2026-09-01 00:00:00 UTC to 2026-10-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsSep 2026

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
Jan 20262026-01-01 00:00:00 UTC2026-02-01 00:00:00 UTC14410
Feb 20262026-02-01 00:00:00 UTC2026-03-01 00:00:00 UTC101
Mar 20262026-03-01 00:00:00 UTC2026-04-01 00:00:00 UTC202
Apr 20262026-04-01 00:00:00 UTC2026-05-01 00:00:00 UTC413
May 20262026-05-01 00:00:00 UTC2026-06-01 00:00:00 UTC202
Jun 20262026-06-01 00:00:00 UTC2026-07-01 00:00:00 UTC000
Jul 20262026-07-01 00:00:00 UTC2026-08-01 00:00:00 UTC000
Aug 20262026-08-01 00:00:00 UTC2026-09-01 00:00:00 UTC202
Sep 20262026-09-01 00:00:00 UTC2026-10-01 00:00:00 UTC101

What Hacker News says

26 sources
wrote something similar for my own use/work stuff; seems everything is converging towards similar ideas. IMO, this style of workflow/agentics is how all SWE'll look like long term. Automate everything into a big pipe-y thing. How it's gonna be modelled is up in the air though. lots of different approaches: mine: https://github.com/portpowered/you-agent-factory https://github.com/ComposioHQ/agent-orchestrator https://github.com/gastownhall/gastown https://github.com/openai/symphony
In Dynamic Workflows in Claude Code
I mean, Google already has Mu Zero, which Im willing to bet has evolved quite a bit in private because if anything is going to get us closer to actual AI its that. Realistically, one can build a AI capable of reasoning (i.e recurrent loops with branches) using very basic models that fit on a 3090, with multi agent configuration along the lines https://github.com/gastownhall/gastown. Nobody has done it yet because we don't know what the number of agents is required and what the prompts for those look like. The fundamental philosophical problem is if that configuration is possible to arrive at using training, or do ai agents have to go through equivalent "evolution epocs" to be able to do all that in a simulated environment. Because in the case of those prompts and models, they have to be information agnostic.
In AlphaEvolve: Gemini-powered coding agent scaling impact across fields
From the most recent comment, looks like this is a bug, triggered by the system inadvertently activating an internal release tool [0]. Still a pretty wild bug, but not as dramatic as the title suggests. Which is kind of unfortunate honestly, the chaos of every gas town instance automatically contributing to itself would be beautiful to see. - https://github.com/gastownhall/gastown/blob/main/internal/fo...
In Does Gas Town 'steal' usage from users' LLM credits to improve itself?
I'm looking forward to trying this. I've had a positive but high-variance experience with Gastown[1], which is in the same genre. I hope that Scion does better. My main complaints with Gastown are that (1) it's expensive, partly because (2) it refuses to use anything but Claude models, in spite of my configuration attempts, (3) I can't figure out how to back up or add a remote to its beads/dolt bug database, which makes me afraid to touch the installation, and (4) upgrading it often causes yak shaving and lost context. These might all be my own skill issues, but I do RTFM. But wow, Gastown gets results. There's something magic about the dialogue and coordination between the mayor and the polecats that leads to an even better experience than Claude Code alone. 1. https://github.com/gastownhall/gastown/
In Google open-sources experimental agent orchestration testbed Scion
Hi HN, With the emergence of the Model Context Protocol (MCP), we are rapidly connecting large language models (LLMs) to critical infrastructure, APIs, and local files. However, the current standard assumes an extremely trusted 1:1 topology. On the other hand, newer agent-based worms (such as the BYOMCP exploits or OpenClaw) demonstrate that malicious payloads can dynamically overwrite an agent’s context window. I have just submitted an article to arXiv (which is currently in the queue under cs.NI) that uses the Rice theorem, Kolmogorov complexity, and recent cryptographic proofs to demonstrate why attempting to solve this problem using asymmetric “security wrappers” is unfeasible from a mathematical standpoint. Guaranteeing 100% AI safety is computationally undecidable. Instead of static filters, the article proposes a reactive topologic
Read the rest
al defense mechanism: the Byzantine MCP Router (BMR). It acts as middleware that establishes a 1:R:N topology. Rather than relying on a single model, it sends the MCP tool request via multicast to several different base models. To ground the theory in real-world engineering, the paper includes a case study on Steve Yegge's recently released "Gas Town" orchestration framework for Claude Code (https://github.com/steveyegge/gastown). It demonstrates how persistent Git-hook memory in standard hierarchical topologies creates a permanent incubator for agentic worms if a worker agent's context is hijacked. Key concepts: 1. Action-Space Consensus: High-dimensional vector embeddings are used to find a semantic consensus strictly based on the intent of the tool calls, inherently blocking prompt injections that diverge from the quorum. 2. Extended Petri Nets (EPN): Inhibitory arcs can guarantee true human-in-the-loop accountability, preventing "fake accountability". 3. The Morpheus Principle: A quarantine routing mechanism isolates extreme outliers (which could be constructive, creative anomalies rather than just errors) for human review. Since the arXiv index takes a while, you can find the full updated paper (v7 PDF), the source code, and high-res architectural diagrams in the GitHub repo here: https://github.com/wdulz/byzantine-mcp-router I would love to get your technical feedback.
In The Byzantine MCP Router – AI Safety and Security via Semantic Consensus
> No productivity studies of individual developers tackling tasks show a 10x speedup; results tend to be anywhere from +20% to minus 20%. The only study showing a -20% came back and said, "we now think it's +9% - +38%, but we can't prove rigorously because developers don't want to work without AI anymore": https://news.ycombinator.com/item?id=47142078 Even at the time of the original study, most other rigorous studies showed -5% (for legacy projects, obsolete languages) to 30% (more typical greenfield AND brownfield projects) way back in 2024. Today I hear numbers up to 60% from reports like DX. But this is exactly missing the point. Most of them are still doing things the old way, including the very process of writing code. Which brings me to this point: > There have been absolutely zero indicators that this is true. I could tell you my
Read the rest
personal experience, or link various comments on HN, or point you to blogs like https://ghuntley.com/real/ (which also talks about the origanizational impedance mismatch for AI), but actual code would be a better data point. So there are some open-source projects worth looking at, but they are typically dismissed because they look so weird to us. Here's two mostly vibe-coded (as in, minimal code review, apparently) projects that people shredded for having weird code, but is already used by 10s of 1000s of people, up to 11 - 18K stars now. Look at the commit volume and patterns for O(300K) LoC in a couple of months, mostly from one guy and his agent: https://github.com/steveyegge/beads/graphs/commit-activity https://github.com/steveyegge/gastown/graphs/commit-activity It's like nothing we've seen before, almost equal number of LoC additions and deletions, in the 100s of Ks! It's still not clear how this will pan out long term, but the volume of code and apparent utility (based purely on popularity) is undeniable.
In Labor market impacts of AI: A new measure and early evidence
This smells like Claude's own version of Gas Town by Steve Yegge. Probably more constrained and less of a crazy bull ride. But seems we are heading this way, from initially: - a Senior Dev pairing with Junior Dev (2024/25) - a tech lead/architect in charge of several Developers (2025) - a Product Owner delegating to development teams (2026?) --- - https://github.com/steveyegge/gastown - https://steve-yegge.medium.com/welcome-to-gas-town-4f25ee16d...
In Claude Code's new hidden feature: Swarms
Originally I thought that Gas Town was some form of high level satire like GOODY-2 but it seems that some of you people have actually lost the plot. Ralph loops are also stupid because they don't make use of kv cache properly. --- https://github.com/steveyegge/gastown/issues/503 Problem: Every gt command runs bd version to verify the minimum beads version requirement. Under high concurrency (17+ agent sessions), this check times out and blocks gt commands from running. Impact: With 17+ concurrent sessions each running gt commands: - Each gt command spawns bd version - Each bd version spawns 5-7 git processes - This creates 85-120+ git processes competing for resources - The 2-second timeout in gt is exceeded - gt commands fail with "bd version check timed out"
In Gas Town's agent patterns, design bottlenecks, and vibecoding at scale

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