Six months from now half of these abstractions will have been renamed or removed once real users push back on the cognitive overhead. Google has a pattern of releasing infrastructure that's perfectly shaped for Googles problems and awkward for everyone else's
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.
I swore to not be burned by google ever again after TensorFlow. This looks cool, and I will give this to my Codex to chew on and explain if it fits (or could fit what I am building right now -- the msx.dev) and then move on. I don't trust Google with maintaining the tools I rely on.
I want to experiment more with agents but my employer only pays for Claude Code, and TOS disallows using the subscription API for other purposes. Anyone else in the same boat? Token based pricing also gets expensive fast.
Their agent tooling is shaping up to be the well known issue of product cancellation. They have how many different takes on this now? (gemini-cli, antigravity, AI studio, this, Gemini app)
I've not been impressed with any of them. I do use their ADK in my custom agent stack for the core runtime. That one I think is good and has legs for longevity.
The main enterprise problem here is getting the various agent frameworks to play nice. How should one have shared runtimes, session clones, sandboxes, memory, etc between the tooling and/or employees?
Not if you go custom, you have unlimited latitude.
Examples, I modified file_read/write/edit to put the contents in the system prompt. This saves context space, i.e. when it rereads a file after failed edit, even though it has the most recent contents. It also does not need to infer modified content from read+edits. It still sees the edits as messages, but the current actual contents are always there.
Another example is my AGENTS.md loader. The agent does not decide, it's deterministic based on what other files/dirs it has interacted with. It can still ask to read them, but it rarely does this now.
Six months from now half of these abstractions will have been renamed or removed once real users push back on the cognitive overhead. Google has a pattern of releasing infrastructure that's perfectly shaped for Googles problems and awkward for everyone else's
Like Kubernetes?
Yes, and unironically.
And angular.
kubernetes isnt difficult
really?
100%. Great assessment.
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/
I swore to not be burned by google ever again after TensorFlow. This looks cool, and I will give this to my Codex to chew on and explain if it fits (or could fit what I am building right now -- the msx.dev) and then move on. I don't trust Google with maintaining the tools I rely on.
nice plug
Reading this headline, I rather thought of a different SCION:
> https://en.wikipedia.org/wiki/SCION_(Internet_architecture)
They kinda buried the code deep in their docs:
https://github.com/GoogleCloudPlatform/scion
I want to experiment more with agents but my employer only pays for Claude Code, and TOS disallows using the subscription API for other purposes. Anyone else in the same boat? Token based pricing also gets expensive fast.
Their agent tooling is shaping up to be the well known issue of product cancellation. They have how many different takes on this now? (gemini-cli, antigravity, AI studio, this, Gemini app)
I've not been impressed with any of them. I do use their ADK in my custom agent stack for the core runtime. That one I think is good and has legs for longevity.
The main enterprise problem here is getting the various agent frameworks to play nice. How should one have shared runtimes, session clones, sandboxes, memory, etc between the tooling and/or employees?
It's all just system prompts under the hood and nothing more.
Not if you go custom, you have unlimited latitude.
Examples, I modified file_read/write/edit to put the contents in the system prompt. This saves context space, i.e. when it rereads a file after failed edit, even though it has the most recent contents. It also does not need to infer modified content from read+edits. It still sees the edits as messages, but the current actual contents are always there.
Another example is my AGENTS.md loader. The agent does not decide, it's deterministic based on what other files/dirs it has interacted with. It can still ask to read them, but it rarely does this now.
Don't forget a while loop and a TODO.md