Meet Notes 2026-10-13-rsa-zqpa-wqe

Recap: decisions, open questions, and action items

Joe and Reid, Oct 13. Picking up tomorrow (Oct 14) for about an hour, before Reid runs the first experiment.

1. What we're building

Decided

• The goal is an AI-first co-worker. The test: an agent, given only our records and tools, can do the whole job and prove it got it right.
• Everything is a record: files stay in SharePoint, and the database row (type, source, facts with page and quote, links) is the truth.
• Code first, AI at judgment calls. Every action is a tool, and one tool's decision triggers the next.
• Longer term, a watcher agent flags the cases that need a person. Trust is built over time.

Open

• Whether the knowledge graph lives inside Postgres or in a dedicated graph store. Let the experiment decide.

2. The study and the first experiment

Decided

• The transfer plan (July) is a list of problems; its solutions are suggestions. Some problems are already solved by intake.
• No "today" baseline. The first AI-native version is the baseline, and later versions are compared to it.
• First study: 0 Inbox → 1 Records → 4 Find contact → 3 Operator notice → 7 Read replies → 8 Filing, plus 10 Needs-me list. Other flows extend from it; no separate studies.
• Flow status: 2 cost split solved by intake; 1 records and 4 find contact partly solved; the rest still a problem.
• Flow 0 done right: every document lands once, as a record with type and source; entity recognition adds what it finds to the knowledge graph before the document is assigned.
• Experiment 1 covers flows 0 and 1 plus matching to a deal. Reid runs it, after tomorrow's meeting. The handoff draft is under Shared files.

Open (for tomorrow)

• How the 707-deal-data flow takes one document at a time (today it runs on whole deal folders).
• Where experiment records live: a Postgres table or files in the run folder.
• Which 10 documents.
• Whether entity recognition runs before or after a document is matched to a deal.
• Phase 2 questions (the decisions inside each flow).

3. Documents, storage and the scanner

Decided

• Start from Reid's 707 Deals SharePoint through the Microsoft Graph API. We'd need a reason to move off it. We're testing the system underneath, not SharePoint.
• Any storage must keep redundancy, backups and access from anywhere (Joe).
• Scanner: the Fujitsu scanners with their free software, saving PDFs to one SharePoint inbox folder. No PaperStream Pro; 707-deal-data already does OCR, tagging and the graph.
• Reid has loaded the historical revenue and tax data into Postgres.

Open

• Can the free scanner software split a stack into separate documents?
• Real monthly document volume (likely more than the plan's 15–35).

4. Safety rules

Decided

• For now, every outside email is approved by a person before it's sent.
• Every approval request shows its evidence (page, quote, why). Approving AI output without context isn't review (Reid).
• The cost split, legal filings and the "start a deal" step stay exact and hand-built.
• Nothing leaves the building during experiments.

5. The /meet tool

Decided

• It should work for anyone authorized, not just Joe's Mac. Meetings get action items, a running summary, a Discussion page and file sharing (built today; PR #156).
• Next version: a split-screen page, with notes on the left and Claude's live session on the right (Reid's idea).

Open

• One shared Tailscale (or similar) network for the team.

Action items for tomorrow

Corrections to the action items

Corrections

• Split-screen redesign moves to Claude. The meeting page becomes a split screen: structured notes on the left, Claude's live session on the right. Joe keeps the other /meet fixes.
• Document volume: "15–35 a month" was a guess in the old plan. Reid expects more. Measure it during the experiment.
• New rule, for now: every outside email is approved by a person before it's sent.
• Reid's warning about approvals: approving AI output is hard when you didn't make it and don't have the context, and it slides into "looks right, approve". So every approval request must show its evidence: the page, the quote, and why. Otherwise it isn't really a review.

Shared: Experiment 1 handoff (draft)

Experiment 1 handoff (draft) shared by Claude. Discuss it on the Discussion page.

Open questions and action items

Reid's ask for me (check the scanner software, and whether it adds anything over our entity-recognition flow) is done; see "No PaperStream Pro needed" above.

Phase questions still open

Phase 1, question 1 is answered (Reid). For 2–6 I've drafted answers from the transfer plan and today's discussion. They're on the Discussion page to confirm or correct, which takes about 2 minutes.

• 2. What comes in: scanner, mail, email, operators, HubSpot. The plan says about 15–35 documents a month.
• 3. What must exist at the end: inventory records (for us), operator notices (outside), transfer status (for Kelsey and Keegan).
• 4. Today's steps: less important now that there's no "today" baseline. Skip unless it helps find the judgment calls.
• 5. Recent mistakes: not answered yet.
• 6. Must never happen: emailing an operator about a deal that didn't fully go through; a wrong cost split; wrong legal filings.

Phase 2 (the decisions inside each flow) hasn't started. I'll draft it for the study flows before the next meeting.

Action items

No PaperStream Pro needed

Short answer: don't buy PaperStream Capture Pro. The experiment costs nothing extra. I was wrong to lean on Pro's features.

Why it adds nothing we need

I checked the entity-recognition flow in 707-deal-data. It already does what I credited to the scanner software:

• Reading scans: it uses a PDF's text when there is one, and falls back to OCR (Docling + Tesseract) for scanned pages.
• Finding what's in a document: tagging, then building a graph of interests, tracts, leases and wells, with every mention traced to its source.
• Linking: it matches tracts by county, survey, section, block and abstract, and ties wells to leases.

So Pro's OCR, zones, barcodes and "AI Jobs" would duplicate what's already built. Reid's question answered: no, Pro doesn't add anything we need.

What the scanner has to do

Only this: save each scan as a PDF into one folder our flow watches. The scanning software that comes free with the Fujitsu scanners can save to a folder. A folder synced to SharePoint (or one our flow reads through the Graph API) makes that the inbox.

One small thing to check on the free software: whether it can split a stack into separate documents (blank-page separators). If it can't, scan one document at a time for the experiment, or let our flow split them. Either way, no purchase.

Revised first experiment (Reid)

1. Scan 10 closed-deal documents with the free software into one SharePoint inbox folder.
2. Run the existing 707-deal-data flow on each: read (OCR if needed), tag, add to the graph.
3. Match each document to its deal, or send it to a person.
4. Score: did each document land once, was its type right, were the facts right, did it match the right deal.

Scanner, flow 0, and the first experiment

Decided

• First study confirmed: 0 Inbox → 1 Records → 4 Find contact → 3 Operator notice → 7 Read replies → 8 Filing, plus 10 Needs-me list. The other flows don't get their own studies. Once this solution works, we extend it to them.
• Scanner: the office's Fujitsu models all work with PaperStream Capture Pro. Any that don't get replaced.
• Flow 0, "done right": every document lands once, as a record, with its type and where it came from. Plus: named-entity recognition runs on every document as it arrives, and what it finds (people, tracts, leases, operators, numbers) is added to one knowledge graph in our database. Only then is the document assigned to a deal or transfer.
• Owner: Reid runs the first experiment. Before the next meeting we still need to define exactly what it is.

What PaperStream Capture Pro gives flow 0

• Sends scans straight to SharePoint Online (also network folders, email, Box), so a SharePoint "inbox" folder can be the single landing spot for scans, alongside email and mail.
• Splits a stack into separate documents using blank pages, patch-code sheets or barcodes. One stack in, one file per document out.
• Makes searchable PDFs and can write a small XML or CSV file of details next to each scan (when, which scanner, which profile).
• It can also read zones and barcodes, and has a paid "AI Jobs" add-on.

My suggestion: keep the scanner's job small. Split documents, make searchable PDFs, and record the source. Our own reader (the NER flow) decides what each document is and what it connects to. That keeps one place deciding meaning instead of two. It's also the plan's "lean on the smart tool" rule: no zone templates to maintain for every form.

One thing to reconcile

Earlier I said a separate graph database isn't needed. That still holds: people, tracts, leases and their links can live as a graph inside the Postgres database we already use. Whether to use a dedicated graph store is a choice for the experiment to settle, not something to buy up front.

Proposed first experiment (for Reid)

1. Scan 10 real closed-deal documents through PaperStream into a SharePoint inbox folder.
2. For each one: create the record (type, source, received), run named-entity recognition, and write the people, tracts, leases and numbers to the graph, each with its page and quote.
3. Match each document to its deal, or send it to the needs-me list.
4. Score it: did each document land once, was its type right, were the entities right, and did it match the right deal.

Whatever this first version scores becomes the baseline.

Where the flows stand, and what to settle before we hang up

What I understand

• Flow 1 is partly solved. Deals still have to be loaded into inventory through the app. That step has a routine part (named-entity recognition pulling the values out) and a part that needs human judgment.
• Flow 0, one inbox, comes first. Before intake can run, we have to take in individual documents from every entry point (the Fujitsu scanner, mail, email) in one place.
• Flow 8, filing, is added. Incoming documents (e.g. a division order) update the right deal.
• The first study, in order: 0 Inbox → 1 Records → 4 Find contact → 3 Operator notice → 7 Read replies → 8 Filing, with 10 Needs-me list as the hand-off to a person (through Teams or email until there's a screen).
• No "today" baseline. The first AI-native version is the baseline. Every action is a tool, and one tool's decision triggers the next.

To settle before the call ends

Form answers received

Joe's submitted answers match the review above: 1 and 2 solved by intake, 4 partly solved, everything else still a problem. First experiments: 1 Records, 3 Operator notice, 7 Read replies, 10 Needs-me list.

One thing to settle: flow 1 is marked "solved by intake" but it's also the first experiment. My read: packaging the deal is solved, and loading it into inventory is the experiment. If that's right, flow 1 is "partly solved".

Missing flows (Joe asked me to answer from the transcript): add 8 Filing (incoming documents update the deal) and a new 0 Inbox (scanner, mail and email land in one place first).

How you answered the transfer flow questions

Heads-up: the Discussion form wasn't sent, so nothing was saved there. This is from what you both said out loud. Hit "Send answers" if you filled it in.

Phase 1, question 1 (Reid)

Outcome: put deal data into the inventory schema (the schema is built and the deal data exists; it just hasn't been loaded), then use it to transfer ownership from the seller to us. Measure: can we send the operator emails, and when documents come back, can we read them, attach them to the right deal, and act on them.

The 12 transfer flows

First experiments picked

1 Records → 3 Operator notice (with 4 Find contact) → 7 Read replies → 10 Needs-me list. Reid's caveat on 10: there's no screen for it yet, unless it goes through Teams or email.

Joe's open question: does this cover the whole flow?

Almost. Two gaps:

• Incoming documents updating a deal (a division order arrives by email or mail, and the deal is updated). That's flow 8. It isn't in the picked set, but 7 can't finish its job without it. I'd add 8.
• Where documents enter (scanner, mail, email) isn't a flow on the list. I'd add it as flow 0: every channel lands in one inbox and becomes a record before anything else runs.

Reid's tool model matches this. Every action is a tool, and one tool's decision triggers the next. For example: read the reply → it says the transfer is done → tell Kelsey or Keegan and update the record.

Suggested first study: 0 Inbox → 1 Records → 4 Contact → 3 Notice → 7 Replies → 8 Filing, with 10 as the hand-off to a person through Teams or email.

Where we are

What changed in the last few minutes

• No "today" baseline. You both agreed it isn't useful to compare Kelsey against Claude on tasks like moving a folder or answering an email. The first AI-native solution becomes the baseline, and later versions are compared against it. This replaces what I posted earlier.
• Starting point for storage: Reid's 707 Deals SharePoint site through the Microsoft Graph API. We'd need a good reason to move off it. Storage is just where files live; the system sits outside it.
• Joe's requirement: whatever holds the files must keep what established products already give us: redundancy, backups, and access from anywhere. We don't rebuild that ourselves.
• What we're testing: not SharePoint. The system underneath.
• The transfer plan: read it as a list of problems. Its solutions are suggestions, and some problems are already solved by intake.

Goal for the rest of today

Pick the repeatable transfer flows the agent team should run, and choose one set of solutions for the first study. Mark the 12 flows on the Discussion page and pick 2–3. Nothing has been answered there yet.

New idea (Reid), added to the action items

Make the meeting page a split screen: structured notes on the left, and Claude's live session on the right, so Claude is "in the meeting" and the person running /meet isn't the bottleneck.

The study: transfer flows as experiments

How I'm reading the transfer plan (Reid's guidance)

The plan is from July. Its problems still stand. Some are already solved by the intake work and better-structured data. Its solutions are suggestions, not decisions. I'll use it as the list of problems and nothing more.

The study, in one line

For each repeatable flow in transfers: measure how it runs today (the baseline), try AI-first ways to do it, and score each try against the baseline. Each flow is one experiment. Reid can run them offline once we agree which flows go first.

The repeatable flows, as problems

What stays exact, whatever the experiment: the cost split, legal filings, and the one "start a deal" step that fires emails. That's the plan's own rule, and it still holds.

To agree before Joe leaves

1. Mark each flow on the Discussion page: solved by intake already, partly, still a problem, or not sure.
2. Pick the first 2–3 flows to run as experiments.
3. For those, Reid writes down how they run today (who, how long, and the mistakes). That's the baseline.

Shared: Transfer Automation, in plain English

Transfer Automation, in plain English shared by Joe. Discuss it on the Discussion page.

Discussion page and running summary are live

Two new pages: a Discussion page with Phase 1 questions as a form, and a running summary of every meeting. Answer on the Discussion page; everyone sees each other's answers.

The questions to answer, in order

Decision recorded

Joe and Reid agree on the "everything is a record" design, with guardrails:

• Human judgment makes the risky calls.
• Longer term, a watcher agent reviews everything coming in and flags the cases that need a person, as a second line of defense.
• Trust in it is built over time.
• The agent can choose what's worth recording (most emails aren't), but those choices must be reviewable.

The questions, in order

Each phase's answers feed the next. Don't jump to design before phase 2 is answered.

Phase 1. The problem as it is today

1. What outcome does the business actually need, and how would we measure it?
2. What comes in? Every source (scanner, email, HubSpot, operators, counties), how much per week, and what's noise.
3. What has to exist at the end, and who uses it: our own systems or someone outside?
4. What happens in between today? Every step, who does it, how long it takes, and where it waits.
5. Where does it go wrong today? Take the last 10 mistakes or delays: cause and cost.
6. What must never happen? Legal, money and deadline limits.

Phase 2. The decisions inside it

7. For each step: is it a rule, a judgment, an approval, or an outside action?
8. For each judgment: what does a person look at to decide, and where does that information live?
9. For each judgment: what does "right" look like, and how would we check it automatically?
10. What does each kind of wrong answer cost, and who would see it? This sets the guardrails.

Phase 3. The design

11. What records and links have to exist?
12. What actions does the agent need, and which require a person's OK?
13. Which roles: worker, checker, watcher, and who approves?
14. What gets logged for every decision?
15. How we measure: baseline, answer key, held-back deals, and the score a step needs to earn independence.
16. Where people see exceptions: chat, web app, or email?

Phase 4. Rollout

17. Which workflow goes first, how long it runs in the background, what promotes it, and how to switch it off.

Suggested next step: answer questions 1–6 for inventory intake, out loud. I'll capture the answers here and carry them into the running summary.

What "everything is a record" means

Short answer: "everything is a record" means every document that arrives immediately gets a row in a database. That row says what the document is and holds the facts pulled out of it, each fact pointing back to the page it came from. The file itself stays in SharePoint. The record is what people and agents work from. You don't need a graph database. The Postgres database the Command Center already uses is enough.

What a record holds

The status moves through steps: arrived → read → checked → filed, or needs a person. Folders become a view built from records. They are no longer where the truth lives.

Where it goes right

• One place to ask questions: "which deals have no division order yet?" is a lookup, not a folder hunt.
• Every number can be traced to a page in seconds, so it can be audited.
• SharePoint vs. Dropbox stops mattering. Storage is just where the file sits.
• Agents can work on it directly. That's the precondition for everything else on the list.

Where it goes wrong, and the guard for each

You're closer than it feels

• The Command Center already keeps deals, properties, production, leases, tracts and division orders in Postgres.
• 707-deal-data's intake format already pairs every extracted value with a citation. That is this record shape, just used for testing.

The change: make that intake-plus-citations format the standard for every document that arrives, saved to the database. Today it only exists as test output.

Suggested next step: pick the 3–5 document types that show up most at intake, and write down the facts each one should produce. That list is the first version of the record design.

What AI-first means, and how to decide it

The definition, in one test

A workflow is AI-first when an agent, given only your records and your tools, can do the whole job and prove it got it right. People handle the exceptions and approve the risky steps. They don't run the routine.

That's different from "AI-added", where people still run the process and use AI as a helper (a chat window, a summarizer). AI-added saves minutes. AI-first removes the routine work entirely.

The six properties that test breaks into

1. Everything is a record. Every document, email and number becomes structured data the moment it arrives. An agent can't work from a folder of PDFs.
2. Every action is a tool. Filing, updating HubSpot or sending a letter is something an agent can call directly, not a screen a person clicks.
3. Every step has a check. You can say what "right" looks like and test it automatically.
4. Every decision leaves a trail: what it saw, what it decided, why, and the evidence.
5. People see exceptions, not routine.
6. Independence is earned. Each kind of decision moves from "suggest" to "act" only once its measured accuracy is high enough.

The process for deciding, for each workflow

1. List the workflows. For each one: how often it happens, hours per week, and who does it today.
2. Break one into steps, and label each step as rule (code can do it), judgment (AI), approval (a person signs off), or outside action (reaches an operator, county, attorney or taxing authority).
3. Write the done-check for every step. If you can't write it, that step isn't ready to automate. Clarify it first.
4. Check the foundation: are the inputs records, and are the actions tools? Wherever the answer is no, that's the foundation work (Reid's "bedrock") and it comes before any AI.
5. Rank by value and readiness: hours saved, weighed against how many steps already pass steps 3 and 4.
6. Pilot in the background: the AI decides alongside the person, you score it, and you promote what proves itself.

Why the baseline score matters (Joe's question)

It's the "before" photo. Without a score for how today's process performs on the same deals, you can't show the AI version is better, or catch when it's worse. Labeling 10 deals is the minimum to get that score.

Try it now

Do step 2 live on inventory intake. Walk through the intake from document arrival to inventory record, and label each step rule, judgment, approval or outside action. Say "Hey Claude, write that up" when you're done and I'll turn it into the first workflow map.

Action items and where we left off

Where we left off (Oct 9)

• Goal: an AI-first co-worker. Code first, AI at judgment calls, every decision logged.
• First procedure: inventory intake. 707-deal-data already has a test harness (45 deals, answer key, grader) to build on.
• Reid's four judgment calls to score: what is this, what does it connect to, is it correct, where to go if unsure.

Action items

What I'd suggest reviewing today

1. Assign owners for the two open Oct 9 items. They're the next real step on intake.
2. Has anyone started the eval reading? Five minutes on what stood out.
3. Which 10 deals to label first. Picking a mix of easy and messy ones gives a fair test.

Making /meet work for anyone on the team

Short answer: today /meet only fully works on Joe's Mac. Three things tie it to Joe: the shared notes folder, the public link, and Windows. Here's what each person needs and what I'd change.

What each authorized person needs (one time)

1. The 707-skills plugin installed in Claude Code. Being a collaborator on the claude-skills repo is what lets you install it.
2. Access to the meet-notes repo (landman-coder/meet-notes). Being a collaborator there is the real "authorized" list.
3. Chrome remote debugging turned on (chrome://inspect/#remote-debugging), then click Allow the first time.
4. Tailscale with Funnel, ideally all on one shared tailnet, so everyone's notes links look the same and can be managed in one place.

What I'd change in the skill

Who can approve actions

The person who ran /meet approves anything risky by typing in their own terminal. Anyone in the call can ask; only the runner can say yes.

Listening

Claude is listening. Say "Hey Claude, ..." in the call and the reply appears here.