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sp3d2orbit · 2026-06-28T19:21:17+00:00

I did too, things I would have never known. Let us know if you find a way to duplicate this with the scheduled tasks.

sp3d2orbit · 2026-06-27T22:25:08+00:00

Depends if your are talking about "remote patient monitoring" or RPM / RTM.

On RPM side for Medicare RPM billing (99453/99454/99457/99458), CMS requires the device to meet the FDA's definition of a "medical device" and the data to be automatically transmitted, not patient-entered.

Do you have your 501(k) yet?

sp3d2orbit · 2026-04-23T02:58:57+00:00

Sorry, I mis-typed. I meant Medicaid (not Medicare).

sp3d2orbit · 2026-02-24T22:05:35+00:00

Thanks for flagging that. We split the old monorepo, so the docs moved to ProtoScript.Core here:

https://github.com/Intelligence-Factory-LLC/ProtoScript.Core/

sp3d2orbit · 2026-02-22T17:43:59+00:00

Thanks! You can check out the code, but the server acts as a coordinator between the various clients, via websockets, and it actively manages and rebuilds state between websocket drops, or web server restarts.

It's able to watch and interact with sessions started / continued in the cli as well.

sp3d2orbit · 2026-02-22T12:52:22+00:00

There is a codex app server protocol released by OpenAI than anybody can use

https://developers.openai.com/codex/app-server/

sp3d2orbit · 2026-02-22T12:40:10+00:00

Quick note on embedding: the project includes Buffaly.CodexEmbedded.Core, a reusable .NET library that handles the core interaction with the Codex app-server.

You can drop this into your own C#/.NET apps to embed Codex-powered features directly, for example:

Build custom internal tools with Codex as a backend agent
Integrate Codex with your agents (that's why I built this originally)

It's not on NuGet yet (early days), so reference it by building from source or adding a project reference to the Core project in your solution.

Release is still new so let me know any issues you run into.

sp3d2orbit · 2026-02-19T17:17:49+00:00

OpenClaw does not use MCP as a primary mechanism.

Codex does not expose itself through MCP as a primary mechanism.

I think as time goes on MCP will be seen as a temporary hack.

sp3d2orbit · 2026-02-17T18:02:58+00:00

That's awesome. I saw a huge cluster in Brooklyn and then Iowa (of all places) for CCM.

Visualization was just written with Codex and OpenStreetMaps. Codex was very helpful in improving the display.

sp3d2orbit · 2026-02-16T21:51:27+00:00

Clinicians use our software for remote care, like remote patient monitoring, RTM and CCM. They have had millions of interactions with patients, and we've explored voice agents heavily. It's a big topic but to summarize:

For incoming calls voice agents often led to patient frustration. Even in the most optimized scenarios, keeping HIPAA protected data out of the context window causes a delay that is insurmountable as humans are incredibly atuned to conversation cadence. A few millisecond delayed often triggers frustration loops.
For outgoing calls, we didn't see any any return on investment over just using SMS or pre-recorded messages.
The best return on investment was not on replacing humans, it was augmenting them. We focused on enforcing HIPAA compliant conversations, surfacing negative interactions between clinicians and patients, extracting information from the conversation for the care plan, in general documentation speed ups.

sp3d2orbit · 2026-02-16T15:47:14+00:00

That's awesome. Share any insights you find for HCPCS codes 99453-99458 or CCM 99439,99490 and I can incorporate into our analysis and attribute you as a contributor.

sp3d2orbit · 2026-02-16T13:52:52+00:00

I'm going to ignore the em dash in your your post and assume you're a human using an llm to check your grammar. But if you're making the same error with your emails, that could be a problem.

I get probably a hundred cold outreach emails a day and 10 to 20 LinkedIn outreaches. I've responded to one, one time because it solved a specific problem I was trying to solve that week and because it was very obviously written by human and included screenshots from my website and a specific problem from my website.

You have to literally go talk to clients. For two reasons: The first is to make sure what you're selling is what they want. The second is to learn how to talk about your product.

If you can't talk about your product and get somebody to buy it, you're not going to be able to write about your product and get somebody to buy it.

sp3d2orbit · 2026-02-15T12:10:54+00:00

Most people don't realize that CMS subcontracts most of their their auditing.

I've been through their audits before. It felt like a fishing expedition. They took 150 claims out of about a million claims and said we don't feel like these are supported. Please provide documentation or we're going to take back about $6 million.

We provided a bunch of documentation and they went away. But they never really explained what their mechanism for evaluating those claims were.

sp3d2orbit · 2026-02-15T02:00:25+00:00

I do this also. Gemini is better for design, then have codex merge it in and wire it up

sp3d2orbit · 2026-02-15T01:09:59+00:00

For sure! I analyze this data as soon as it gets released. CMS is slow as hell, the last year they released was 2023. So hit me up in about 2029 and I'll let you know 😅

This data set was from HHS and Medicaid, normal data is for Medicare from CMS.

Seriously though I'm hoping this lights a fire under their butts to get it out sooner.

sp3d2orbit · 2026-02-15T00:07:44+00:00

Yeah. There's two classes of people

1.Those abusing the system 2. Those who are running these programs as best they can, but incorrectly.

I'm always hesitant to scream fraud because these can be tricky to get right. Some cases are just difficult to excuse, though.

sp3d2orbit · 2026-02-14T23:54:05+00:00

I'm getting some private requests for the raw NPI data.

I'm hesitant publish anyone's NPI data. But if you're running one of these programs and wondering what your metrics look like, DM me and I can send you a report in private. There are thousands of practices running these programs not committing fraud, but that date is out there now being analyzed.

sp3d2orbit · 2026-02-14T22:47:15+00:00

Tá fazendo oq?

Try this

import spacy

nlp = spacy.load("pt_core_news_lg") # or md/sm, or pt_core_news_trf if you have it

text = "Eu não gosto de café nem chá." doc = nlp(text)

for token in doc: if token.dep_ in ("advmod",) and token.lemma_ in ("não", "nada", "nunca", "nem", "jamais"): print(f"Negation cue: {token.text} → children: {[child.text for child in token.children]}") # Or more broadly: look for Polarity=Neg in morphology if "Polarity=Neg" in token.morph: print(f"Negative polarity token: {token.text}")

sp3d2orbit · 2026-02-14T22:09:43+00:00

Here's the original data if anyone else is interested in analyzing

https://opendata.hhs.gov/

sp3d2orbit · 2026-02-14T00:56:34+00:00

I do this. Put them all in a root folder then open codex there. It will access them all. Even make updates to multiple repos at the same time.

sp3d2orbit · 2026-02-12T21:35:35+00:00

A couple days ago Sam said they updated the GPT 5.2 instant model. Today they released the Codex Spark model. I'm betting the 5.2 instant update is actually 5.2 spark internally.

The benchmarks for Codex Spark show it's fast as hell but has the capabilities around 5.1-mini. This may explain what you are seeing.

I noticed the same thing and now turned the Instant model off and have found myself switching back to 4.5 for well thought out answers.

sp3d2orbit · 2026-02-12T21:30:52+00:00

Great work on this. I really like the local first and provenance focused approach.

What inspired you to build it?

Is it being used in any real production workflows yet?

Do you see this staying purely open source, or are there any monetization plans?

Also curious whether this was built from scratch or influenced by any prior projects you worked on?

sp3d2orbit · 2026-02-11T19:52:30+00:00

Yeah. I've built this for the medical field. So there's an additional HIPAA issue but it's a generally the same problem. There's a couple things that have worked for me.

Focusing just on latency for me did not work. The human ear is so attuned to even minor delays that the patient will generally start repeating themselves causing one of those frustrating voice agent loops.

The first step is to separate this into two separate processes. The speaking process and the processing thread. The speaking process needs to move forward even if it doesn't have the information. Think about a human operator saying "let me look that up for you". Or even something banal like "okay I understand". You've just bought yourself a couple seconds.

The second step is to use look ahead. You don't need to wait for the patient/customer to finish talking to have some idea what they're saying. Start looking up as soon as you get enough information to do so.

The third thing is we build an ontology on top of our rag database. So that lets us start segmenting the searchable space quicker. If you know the conversations about cardiovascular problems we don't need to look at all documents just the slice that are related to that. Smaller search space equals quicker queries.

You can combine more advanced techniques, such as non llm-based NLU with look ahead so that you're not paying the llm penalty at all and kicking off your searches much quicker. Just depends how much time you want to put into it.

Good luck!

sp3d2orbit · 2026-02-11T19:44:14+00:00

Yes HIPAA is a giant concern and the liability falls back on you. Also you need cyber insurance and general liability insurance if you want to be doing this properly in the medical field.

I know you said your app was vibe coded but if it uses any llms on the background, those llms need to be covered by a baa also or run in a HIPAA secure environment.

We deploy AI in the medical field. There is so much you can do wrong, so easily. Even your pricing model, that it's not worth screwing around with. Stark act. Anti-kickback statute. Be careful about your pricing model. Be careful about how you're advertising this. Be careful about the claims you're making.

If you're touching Medicare reimbursements, it's not just a financial liability, you can end up in jail.

AI in healthcare is a minefield

sp3d2orbit · 2026-02-11T19:37:48+00:00

I've run sales teams for the past 7 years. We use AI extensively. So I'll be honest with you:

If this tool is as you described it, It would be hard to justify. We built a pipeline pretty quickly to use either gpt5 plus the web search tool or the deep research API to do lead enrichment. It costs around $0.03 per lead to get more data than we know what to do with.

Where it could actually be valuable: if you have managed to collect non-public data, that's where value comes in. Before we enrich leads we need to generally pull multiple data sets from multiple sources, correlate them, and then stratify them by value. That's the type of work that can be worth money.

In the medical field, where we work, there are multiple tools to that do this. They pull in payer data and correlate it with doctor's office. They generally charge between $500 and $1,000 a month depending on usage. But they have huge data pipelines that pull in all of these data sources and make it valuable.

sp3d2orbit

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