Dreaming / log analysis

[FredKSchott]

Anthropic just announced this feature of their managed agents platform:

https://x.com/claudeai/status/2052067400690851842?s=46

This makes a lot of sense to me. You can improve a lot about your agent by just asking another agent to review the logs of past runs and look for trouble spots.

This makes a lot of sense for a manager agent platform. The question is how to map that to a self-hosted agent deployment like Flue?

In Cloudflare for example, we have the logs stored via persistence in DO. So we could maybe have an /analyze endpoint that you hit? Or something we do nightly?

But we dont have access to your code, so it's not as easy to translate that analysis to a fix. Hmm...

[stainlu]

this thread clicked for me after reading this: https://trinkle23897.github.io/learning-beyond-gradients/

i think the self-hosted version of “dreaming” maybe should not start as /analyze or nightly jobs. those are product surfaces. the deeper primitive is: can Flue produce clean experience records that another agent can learn from?

so maybe the stack is:

• Run: stable execution unit for prompt / skill / task / webhook / shell
• event log: what happened during the run
• artifacts: diffs, test output, screenshots, logs, files touched
• feedback/eval: success/failure, human rating, regression case, reward-ish signal
• replay/export: enough structure that another agent can inspect, summarize, or turn failures into tests/docs/code changes

then “dreaming” becomes one possible consumer of that substrate, not a special built-in mode.

i also think this lines up with #91: before Flue can analyze past runs, it needs runs to be first-class objects. and it lines up with #89 too: append-friendly persistence matters a lot if the thing you are storing is not just conversation state, but learning material.

maybe the first Flue-native slice is not “learning” yet, but “make runs observable and attachable.” once that exists, dreaming / eval / local heuristic improvement can be built as recipes or higher-level APIs.

[ketankhairnar]

The persist layer that just landed in PR #87 is enough substrate for a v1 of this if dreaming stays read-only and externally-scheduled. The Postgres recipe writes one row per session into flue_sessions(id, data, updated_at). A dreaming consumer is then just:

SELECT id, data FROM flue_sessions
WHERE updated_at >= NOW() - INTERVAL '24 hours'
ORDER BY updated_at DESC
LIMIT 50;

Same shape on D1. Fed into a Flue agent prompt told "review these conversations, look for trouble spots, write findings to dream/<date>.md." The SDK doesn't need a list() on SessionStore for this. Enumeration naturally lives in the persist adapter, which is where it should live anyway.

Two scope calls that I think keep this from sprawling:

1. Recipe, not built-in. Same shape as connectors/persist--*.md. User runs flue add dream, the installing agent writes a script under .flue/dream/ that reads from their existing SessionStore adapter, runs a review prompt, and writes findings to a file. Scheduling is whatever the user already has (Cloudflare cron triggers, OS cron, GitHub Actions). Framework doesn't own the scheduler or the destination.
2. Read-only, no fix loop. You called this out. Without code access we can't translate findings into a PR. So v1 deliverable is a markdown file the user reads. Anything more (auto-issue, auto-PR, prompt-edit suggestions) is a separate consumer they layer on top.

Echoing @stainlu's point: the richer version of this wants the Run primitive from #91. Today's SessionData.entries collapses every prompt/skill/task into one append-only stream, so dreaming sees the conversation, not the runs. Once #91 lands, a dream recipe v2 can filter "show me failed runs in the last 24h" instead of "show me last 50 sessions."

Happy to draft connectors/dream--persist-postgres.md against the schema PR #87 ships. Might be cleaner to wait until #91 has a shape though, since the consumer-side filter ("which runs are interesting") is what a dream recipe actually needs.

[tunnckoCore]

I kinda agree with @ketankhairnar. But also with @stainlu.

To me it sounds more like an observability type of citizen. You'd have a flue add adapter that pipe events to given thing user wants. Then they can have skill/role to tell the agent to "hey, always review the this and that thread/session before you start" kinda thing. It's the simplest "outside" thing, plus it's good for general observability not necessarily "dreaming".

But again, we need the Run as citizen first too.

[ketankhairnar]

note: not a plug ...but if you think - please delete this comment cc: @FredKSchott

Am running my own agent harness for tacit.sh and planning to do 2 things

1. add flue provider to see all the flue sessions in tacit
2. replace current underlying harness with flue

with that as context - it opens up "knowledge" / "memory" adapter requirement