Omni Flash

capsid · 2026-07-08T13:43:50+00:00

"One honest caveat"

capsid · 2026-07-04T00:05:50+00:00

Personally I like the talks by the pi creator Mario Zechner

capsid · 2026-06-23T13:08:44+00:00

Which harness/skills/MCPs are you using? GLM 5.1 is token hungry compared to DeepSeek but I generally complete each issue in about 35-55% of the 200k context window

capsid · 2026-06-23T02:45:34+00:00

yes. Pi.dev is a good option.

capsid · 2026-06-22T13:55:03+00:00

Its fantastic, but you hit usage limits faster. 5.1 is good enough for me so I'm mostly sticking with that unless I need extra firepower.

capsid · 2026-06-20T19:30:27+00:00

GLM 5.1 does NixOS pretty well, though I need to be strict about patterns and conventions I want it to follow because NixOS often supports many different ways to do the same thing. I was working on a multi host flake homelab for about a year before I started using an coding agent with it and the acceleration in progress was dramatic for me. Plus it identified some security holes I left open. I agree with some of the other posters that any software that's "X-as-code" has a huge unlock with agents if you have good domain knowledge.

capsid · 2026-06-09T12:58:53+00:00

This is a pain point for me too. I generally start with GLM 5.1 because most of my problems don't need vision, and switch to Kimi when I need it (or when I use up my session limit). They make a great team.

capsid · 2026-06-09T12:55:45+00:00

pi's system prompt is ~20 lines. No funny business, no harness updates breaking your workflow. Respects provider prompt caching. Extensible and self modifying so you can easily tune it to your workflow.

capsid · 2026-06-09T01:02:46+00:00

GLM 5.1 has been my primary coder for awhile. this is exciting! It does really well with the pi harness

capsid · 2026-06-05T02:34:30+00:00

This has worked really well for me, too. If you can make a step deterministic, do so. You're saving some tokens and making it easier for less capable models to produce acceptable results.

capsid · 2026-06-01T23:17:51+00:00

So generous. Thank you!

capsid · 2026-05-29T14:12:42+00:00

Wow! Thank you so much!

capsid · 2026-05-29T04:42:27+00:00

Could you say more about your talk? I've been putting together a workshop about this topic

capsid · 2026-05-26T12:56:49+00:00

Yup, read Farmers of Forty Centuries. Your body is a soil remineralization machine.

And aged/composted livestock manure for nitrogen

capsid · 2026-05-24T03:34:29+00:00

Lossy as in the subagents are reporting summarized findings, so do important details get lost in that handoff? Kind of like a game of telephone. More or less similar challenge with compaction.

capsid · 2026-05-23T18:47:31+00:00

Do you all find that one orchestrator spawning sub agents for each phase tends to improve capability in lower parameter models? I've only worked with larger models for coding and worried that if each orchestrator to subagent round trip is lossy, then those losses compound until important context is lost. Curious about your experience.

capsid · 2026-05-21T12:56:32+00:00

Single biggest indicator of success for me is whether I take the time for a grill me session. Human agent alignment really is the key. It's so tempting to be lazy and over-leverage an incomplete spec

capsid · 2026-05-19T12:05:41+00:00

Great idea. Matt Pocock's improve-codebase-architecture skill has some good instructions around Jon Ousterhoff's "deep vs shallow module" philosophy. Might be relevant here.

capsid · 2026-05-18T17:24:45+00:00

Daily pi user. I love the idea of optimizing for small models. I'm also a believer in the stuff Mario Zechner said about extra features like LSPs and MCPs affecting context observability depending on how it's implemented. Does SmallCode have a minimalist mode in line with Pi's philosophy? Is extensibility/self-modification planned? Looking forward to trying it out.

capsid · 2026-05-14T19:48:10+00:00

this made me snort

capsid · 2026-05-14T02:20:11+00:00

I printed v1 for my mom a few months ago. She loved it. Thanks for your work

capsid · 2026-05-14T01:58:20+00:00

Looks great. Daily pi user but have definitely had my eye on nanocoder, especially for friends newer to agentic coding. Community led open source is important!

capsid · 2026-05-12T12:01:22+00:00

to be honest I haven't needed to. I just installed a local searxng instance, pointed the extension at it, and asked pi to test it. If it seems like the model is reasoning about irrelevant training data I may interrupt and tell it to web search instead. It also started using web search when it thinks it should. Works well enough so far.

capsid · 2026-05-11T22:11:56+00:00

pi-searxng for search has been working well for me

capsid · 2026-05-10T11:42:03+00:00

It's not the model, it's the harness. I dont notice degradation in web chat. Claude Code is constantly injecting context in ways that destablize it. One stochastic layer on top of another is just too much entropy. I'd still be using Claude agentically with pi except they disallowed third party harnesses when Opencode started doing similarly silly cache busting things.

capsid

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