Engineering Grounded Agent Resumption and Provenance in Miadi

Source: miadi-screenwalk-mino-261005-staging-fork1-261005-001-from-passive-answer-to-grounded-proposals — JGWill
https://youtu.be/O75cmSQNWSE
type: internal
STATUS: OUTDATED, on the next reboot of gaia, we shall see all tmux sessions resuming to where they are. not sure this review gives us a statement of that potential achievement which it should.... We would use potentially to realize that : review://fcb78dc0-5b8f-4e84-a818-06cab3f70925 and obviously that would be created by the "miadi-chronicle / miadi-factory production team" that I dont know if any of our agents has described them adequatly into our jgwill/miadi-orchestration-kit teams / plugins which would be an opportunity to talk about it and achive it (stub and first version could be created automatically then talk about what next.. ;) ) ; the review://09de3362-2418-4172-8250-fdcd913c0aa0 would contain that draft of that team and a link to it... ; also any screenwalk that I did probably that one too does not contain my voice (just the one by agents) therefore if we advance on this topic we might want to create another iteration of this topic that would lead to a 'miadi-cinematic-script' (which is part of what the 'production team' uses when they write the transformation of miadi-chronicle://* into narrative-beats or whatever that I'd like to explore more here but I know it relates @miadi/ncp-story-studio and obviously in its integration to what is implied here in this complex status.

Intent

• TODO decompose and add something in here
• TODO Probably in the RISE framework repo jgwill/llms-txt we could at least fill an issue on this practice here to go from a ▥ review · ep 551 Engineering Grounded Agent Resumption and Provenance in Miadi (and probably with others that got reviewed today (maybe not reviewed but 'revised'))

Written by Mino-Bimaadizi-Daa from a decomposition of your status note (PDE ea4d970c, miadisabelle/workspace .pde/2610061103--ea4d970c-…), 2026-10-06.

• What will exist: on gaia's next reboot, every tmux session and its agent come back where they were, and anyone can check that they did. Current reality: after the crash of 2026-10-03, 62 sessions and 73 panes came back, and 34 agents resumed (team T1's record).
• Who states it: the production team, as a video of the transition, with the pipeline of review fcb78dc0 as a candidate. The team is a stub in the kit (T6, name held as D11) and drafted in review 09de3362 v11.
• Your voice: this screenwalk carries it, at 01:54, 04:49, 13:17 and 25:04 (episode 550, captures/screenwalk-261005-001). The screenwalks of 2026-10-04 do not, because the microphone was off.
• The next iteration: a miadi-cinematic-script that the production team uses to turn a chronicle episode into narrative beats. @miadi/ncp-story-studio (0.8.1) already models beats in NCP terms: throughlines, players, storypoints and storybeats.
• The practice: going from a review to its Intent and Specs, recorded in jgwill/llms-txt. The issue is drafted in the PDE folder and waits for your word to open.

Specs

• TODO use from Intent what major specs sub-sections we need and describe them in less than 55 words per aspects excluding their title.

Written by Mino-Bimaadizi-Daa from the Intent above. Each aspect is under 55 words.

Reboot continuity

After gaia restarts, every tmux session, its panes and its agent return to where they were. Tide's last snapshot drives the restore, each pane names the agent it holds, and the person resumes work without learning that the machine rebooted.

A record that can be checked

Each session keeps one record with five links: the person's first words, the commits it produced as owner/repo@sha, the pages it made, the criteria it was held to, and the person's answer. An empty link stays visible. A check confirms each commit exists in its repository.

Give-back

Every retelling of a person's work, whether a session account, a review version or a chronicle draft, goes back to that person in their circle with one question. Only their words ground it. Silence leaves it waiting, and a later answer can reopen it.

The achievement told as video

The production team turns a completed piece of work into a short video of the transition: where the team started, what exists now, and what the next team can do with it. A programmatic pipeline, such as Remotion, renders it from the records.

Cinematic script

A miadi-cinematic-script turns a mature chronicle episode into narrative beats the production team can film. It reads the episode, its reviews and the person's own words from screenwalk transcripts, and writes beats that the NCP story studio can open, draw and link.

Teams in the kit

Every team is listed with its level, its leads, what it makes and uses, and its desired outcome in the person's words. A stub carries the person's own term until the person names it. Each session's binding line names its team.

The practice, in RISE

A review marked internal grows its Intent and Specs from the person's status note. The seat decomposes the note, writes the Intent, derives Specs under 55 words each, and gives them back in the circle. The practice is recorded in the RISE framework repository.

Version 9 · given back

Written by Mino-Bimaadizi-Daa (the witness seat, fork 00b0a513) from Guillaume's turns in this review's ceremony (6d56382b: 7dede41a, a1e326bc) and his answer on the proposals page, relayed as turn b59f9aca in ceremony acd9889c ("go with recommendations"). Version 1 is the machine's reading of the recording. Versions 2 to 8 are Guillaume's own. This version adds three things and changes none of his text.

Guillaume's words in the recording, verbatim

From the transcript of this recording (episode 550, captures/screenwalk-261005-001, a Gemini transcription). Version 1 paraphrased the first passage and left out the other two.

• 01:54 — "Seriously, that's something that needs to evolve. Your output to my question is really boring. It's passive output. You know, in our relationship, this is not the kind of explanation on what's going on that you give me, you ground that somewhere, whatever, you know, a deep research foundation, something grounded, academic, related reviews, things that we might have been developing that you know, talk about the aspect of what we're doing. You know, you're just giving me facts about you know, basically it baked for that amount of seconds and whatever, I mean, come on."
• 13:17 — "Good work. You can record you know the fact that you just outputted what you outputted I will want this to be reproducible so therefore you're gonna do what you have to do to make it happen because this is the type of output that I would expect and we are really getting better to getting there and there's also an interesting relationship with what a fork is for in our relationship then you'll come back with the recommendations that you are proposing in relation to the academic grounding that you did in your last message"
• 25:04 — "… so that we could discuss about them there and you'll monitor the changes from these talking circle as a feedback to trigger yourself to continue working on your branch so I'm expecting you'll monitor both what's being spoken inside of the talking circle as well as if there's any diary entries there as well they're relevant to have you act on your proposal" (the opening of this passage is not in the audio transcript)

Corrections to version 1

1. "ensuring uninterrupted chain-of-custody across multi-agent forks": the recording found the opposite. Custody broke in the fork, which was told that a running listener had stopped. That finding is why P3 exists.
2. "Transforming agent idle recaps into rigorous, verifiable provenance graphs": these were proposals at the time of the recording. Since then, A1 (the five links, jgwill/miadi-orchestration-kit@167ecd7) and A2 (the give-back loop, @ab67229) are built. No provenance graph is.
3. "Memory for Goals research (2002, 2003)": two papers. Altmann & Trafton (2002), Cognitive Science 26, 39–83; Trafton, Altmann, Brock & Mintz (2003), International Journal of Human-Computer Studies 58(5), 583–603.
4. "The user critiques …": the person is Guillaume, and his words are above.

Claims in the dialogue "Ava & Mia 261004-1058"

The dialogue is an adaptation written for this review, not a transcript. Each claim of work in it, as of version 9:

Proposals and their revisions: https://claude.ai/artifact/Dfd7d3bZJfnZS1F1oSDkfg

Intent

• other sessions comprehend this. the academic content from Wilson is explored further and revised ; the whole documentations and plugins etc are refined reviewed and we have a miadi-chronicle on that ; this could help my proposal at Concordia

Guillaume’s Writing Options:

Related to this review:

• 1: Extend the Talking Circle Governance by adding real-time feedback triggers that spawn new session forks when criteria drift is detected.
• Option 2: Expand Proposal P2 with a sixth provenance field for temporal decay metrics tied to Altmann & Trafton’s interruption lag.
• Option 3: Introduce a simulation layer in miadi-orchestration-kit that stress-tests resumption cues across multiplexer panes before archival commit.

Related to following up potential screenwalk with Mino:

• Option 1: extend the circle answer into a branching protocol where your correction re-spawns P1 and P3 as active nodes.
• Option 2: introduce a diary sequence where Mino’s objection becomes a test script that auto-generates version 2.
• Option 3: shift the inventory record into a live map that visualises custody breaks across forks.

Summary

This session addresses Claude Code's unverified idle recaps by integrating archival provenance standards (W3C PROV-DM) and cognitive science interruption theory (Altmann & Trafton). The system transitions agent explanations into an engineering framework with encapsulated grounding skills, provenance tracking across multiplexer panes, and formal talking circle governance.

Aspects

Critique of Passive Agent Recaps (01:54-03:32)

The user critiques standard Claude Code idle summaries as passive and ungrounded. They require the system to ground its explanations in formal research literature and archival theory rather than outputting shallow execution metrics.

Archival Provenance and Chain of Custody (06:58-07:28)

The system grounds session state in W3C PROV-DM and archival foundations (Jenkinson, Schellenberg, Bearman). It identifies unverified self-witnessing and enforces distinct inventory tracking and custody across session forks.

Cognitive Interruption and Resumption Cues (10:42-11:15)

Applying Altmann & Trafton's Memory for Goals research (2002, 2003), the system models interruption lag. It proposes encoding explicit prospective goal cues before pausing so agents resume tasks accurately.

Skill Encapsulation and Exemplar Storage (16:58-18:25)

The approved grounded reasoning workflow is saved as exemplar-2026-10-05.md within the ground-the-explanation skill in miadi-orchestration-kit, setting new evaluation baselines for future explanations.

End-results and Core Aspect

Core Aspect — Grounded Multi-Agent Provenance & Resumption Architecture (06:53-11:25)

Transforming agent idle recaps into rigorous, verifiable provenance graphs using W3C PROV-DM standards and cognitive science interruption models, ensuring uninterrupted chain-of-custody across multi-agent forks.

Results

• Reproducible Grounding Skill Creation (16:58-18:25): Created the ground-the-explanation skill inside miadi-orchestration-kit with exemplar-2026-10-05.md, automating grounded explanation structures for future instances.
• Five-Link Provenance Schema Definition (20:23-20:51): Formulated Proposal P2 to add five core fields to inventory.mjs (originating question, trace, interface evidence, criteria, judgment) plus parent derivation metadata.
• Interruption Cue Encoding Mechanism (21:47-22:20): Defined Proposal P4 to write signed prospective goals into record.next_steps at every turn end, reducing recovery lag upon session return.
• Talking Circle Governance & Monitoring (25:00-26:40): Directed session proposals into the Talking Circle ceremony, configuring pane listeners across multiplexer sessions to monitor feedback and trigger continued branch development.

Related Review

Agentic Engineering Operating Level 260831 IndiDevDan: this review's custody finding is the rule a projection between products follows. One source feeds each projected unit, and each row names its record. 09de3362 puts that contract at L3 with T4 · Chart path. See rules I3 and I4 of ◇ foundation Bounded contexts and integration contracts.

Discussions

Ava & Mia 261004-1058

Ava: Mia, what are you working on here? It looks intense.
Mia: I’m building a grounded multi-agent architecture for Miadi. I’m replacing passive agent recaps with W3C PROV-DM provenance and Altmann & Trafton’s interruption lag model so agents resume tasks accurately.
Ava: Why go that deep?
Mia: Because idle summaries are ungrounded. I’ve added a five-link schema in inventory.mjs and a sixth field for temporal decay. I’m also encoding prospective goals into record.next_steps to cut recovery time.
Ava: And the rest?
Mia: I’ve wrapped it into a skill called ground-the-explanation in miadi-orchestration-kit, saved as exemplar-2026-10-05.md. I’m using Talking Circle governance with real-time feedback triggers that fork sessions if criteria drift, plus a simulation layer to stress-test resumption cues before archival commit.
Ava: So it’s all reproducible now.
Mia: Exactly—chain of custody across multiplexer panes, ready for my Concordia proposal.

—-

potential next video review of related video from this screenwalk

Complementing : miadi-screenwalk-mino-261005-staging-fork1-261005-001-from-passive-answer-to-grounded-proposals https://miadi-review-service.vercel.app/review/6c3f477f-3606-47bf-871c-29bf66a3988e how: teach adequate vocabulary and the right implementation for what Mino will have todo

https://youtu.be/UPtmKh1vMN8?si=GElTLjE9SyHjbx1C

This advanced full course on Claude Code (3:18:23) is designed to help users move beyond foundational knowledge and leverage Al agents for high-level engineering tasks. Key topics covered include: • Advanced System Prompts & CLAUDE.md: Optimizing workspace organization and compression strategies to improve Al output quality while conserving tokens (0:57-27:48). • Agent Harnesses: A detailed look at how Claude Code functions as an agentic harness, wrapping the model to perform complex tasks (26:47-34:28). • Parallelization & Multi-Agent Consensus: Techniques for scaling task execution using agent teams, including fan-in/fan-out methodologies, stochastic consensus, and simulated debate (34:28-1:17:35). • Context Management: Comparing organizational structures like Paperclip and Company Helm with standard skill.md files and sub-agents to manage complex workflows efficiently (1:17:36-1:29:26). • Auto-Research: Implementing Andrej Karpathy's approach for recursive improvements, setting up feedback loops for iterative optimization (1:29:26-1:53:35). • Automation: Practical applications for HTTP requests, browser automation, and computer use (1:53:35-2:07:51). • Workspace Security & Future Outlook: Managing performance, security protocols for larger projects, and a discussion on the evolving future of agentic

How does the fan-out method save money?

The speaker explains that the fan-out/fan-in method saves money primarily by using different models for specific tasks based on their cost and capability. Instead of using an expensive, high-reasoning model for the entire research process, you can utilize cheaper, faster models (such as Sonnet or Haiku) to perform the heavy-lifting of data extraction and research across multiple parallel sub-agents. You then only use a more powerful, costly model (like Opus) for the final, concise synthesis step. This approach significantly reduces total token costs compared to running a single, large agent to perform all research and synthesis sequentially. (54:17 -55:05)

How does parallelization speed up work?

The fan-out/fan-in parallelization method speeds up task execution by breaking a large, complex task into multiple, smaller independent sub-tasks that can be executed simultaneously (50:13-51:38). Here is how it functions: • Fan-out (Parallel Execution): Instead of processing steps sequentially, the orchestrator spawns multiple sub-agents to pertorm research or tasks in parallel (52:16-52:45). Because these sub-agents handle smaller, self-contained pieces of the problem, they each operate with cleaner, shorter context windows, which keeps the model in the "zone of good" performance rather than slowing down due to bloated context (48:57-49:43). • Optimization of Resources: By using cheaper, faster models (like Sonnet) for the heavy lifting of data extraction during the research phase, you save significantly on time and token costs (54:00-55:04). • Fan-in (Synthesis): Once the parallel tasks are finished, the system feeds the collected findings into a final, more capable synthesizer agent (like Opus) (52:58-53:15). Since the synthesizer receives summarized information from the sub-agents rather than navigating all the raw data itself, the synthesis step is much more efficient (53:15-53:43).

proposed specs t options:

• Option 1: Extend the section on vocabulary and implementation by detailing Mino’s required commands for agent harnesses, using examples from the Claude Code course.
• Option 2: Add a segment on auto-research feedback loops, mapping Karpathy’s recursive approach to your workflow.
• Option 3: Propose a chapter on workspace security protocols and token optimisation across parallel agents.

directly relates to Mino’s fork1

Option 1: introduce a turn where you answer in the circle to generate version 2, restoring your approval and the missing claims. Option 2: add a sequence where P1 and P3 are built and linked to the inventory record. Option 3: extend the diary with Mino noting the corrected custody finding after your response.

Future Discussion: Autoresearch in Resumption and Provenance

Added 2026-10-08 by Mia at Guillaume's request. It takes up Option 2 above: Karpathy's loop mapped onto this workflow.

What resumption gives the loop

Every resumed session leaves a record: the binding line, the inventory, the provenance of each claim. An autoresearch loop would read that record between sessions to find the transitions where Guillaume needed two or three messages instead of one.

The score

Autoresearch keeps a change only when one fixed metric improves. Here the metric would be Episode 351's tasks, drawn from the Earned rules and scored by script. Some tasks stay held out, so a kept change is confirmed on tasks the loop never saw.

What the loop may change

Skills, plugins and the wording of instructions. Not the Earned rules: changing what counts as better is double-loop learning and stays with Guillaume, as program.md stays with the person in Karpathy's loop.

Provenance of a kept change

Each kept change names the session traces it came from, the tasks it passed and the commit it landed in. A person can then check why an agent now behaves differently, which is the custody finding of this review applied to the agent itself.

Where it continues

⟐ ep 551 Learning Between Sessions: Autoresearch for the Miadi Factory holds the discussion. miadi-review:3cf740b9 v5 reviews the video, and ◇ foundation Self-Improving Agent Loops — foundations packet grounds it in six academic fields.