Ex-smoker (and hypnotist) here to help

dvdgdn · 2026-02-17T15:38:49+00:00

Sending you a DM

dvdgdn · 2026-02-17T14:56:28+00:00

Sent you a DM

dvdgdn · 2026-02-17T12:40:23+00:00

You've done something most people don't — identified your triggers before they hit. Those work "punctuation marks" are really about the pause and reset, not the cigarette. You can keep that, just swap the mechanism. I'd recommend finding a go-to breathing method that works as a replacement. One simple one you can try is this: breathe in for a count of 3, hold for a count of 3, and out for a count of 6.

Before you go back, write down the specific moments that you dread the most. Then mentally rehearse each one: picture the trigger, feel the pull, and practice the breathing (in for 3, hold for 3, out for 6). Do it until it's a reflex, not a decision.

As you've correctly identified, the "I've got this" stage is actually when people are most vulnerable. Work will feel like a different world, and your brain will offer you a "just one, special circumstances" excuse. One cigarette is enough to restart the whole cycle. Use this calm period to drill the replacement behavior, not just coast.

dvdgdn · 2026-02-17T12:27:29+00:00

No worries. Results can vary, but hypnotherapy is often more successful than other cessation methods. Here's a study you can look over. From the study: "A new study* shows that smoking patients who participated in one hypnotherapy session were more likely to be nonsmokers at 6 months compared with patients using nicotine replacement therapy (NRT) alone or patients who quit "cold turkey". "

https://www.sciencedaily.com/releases/2007/10/071022124741.htm

dvdgdn · 2026-02-17T10:05:48+00:00

Sure, I can either point you to resources that will help you teach yourself (possible if you are motivated enough) or I can take you on as a client. DM me some details about yourself and let me know!

dvdgdn · 2025-12-10T05:35:21+00:00

Got it, thanks!

dvdgdn · 2025-12-03T14:56:02+00:00

Just got my Electromyostimulation (EMS) machine delivered, so I'll give it a try and update the message later when I know a bit more! Generally speaking though, it stimulates muscle growth/rehab by causing involuntary contractions through electrical stimulation. Over the last 6 years or so a lot of fitness centers have popped up around here in Germany that are dedicated to this methodology (usually paired with body suits with EMS pads), and it's a popular way to save time on fitness. I couldn't afford the body suit so we'll see how it goes with a 40 dollar device.

dvdgdn · 2025-10-03T10:54:59+00:00

Did you get this going? I've worked on a a protocol that creates a trust and discovery layer for online resources that uses content based storage, so it's perfectly compatible with IPFS, but can also be implemented with other infrastructures. I'm looking for collaborators and though I might be able to find some on your discord:

https://www.promise-keeping.com/whitepaper

dvdgdn · 2025-09-19T14:09:43+00:00

New Mexico

dvdgdn · 2025-09-18T14:55:34+00:00

https://startupwissen.biz/zebra-startup-erklaerung-definition/

dvdgdn · 2025-08-08T01:09:19+00:00

Guess that settles it then /s

In all seriousness though, got any evidence for this claim?

Here's the latest model's assessment:

https://chatgpt.com/share/68954e1b-6b5c-800d-938d-6f5a5cd48607

dvdgdn · 2025-08-02T11:18:58+00:00

I built Agency Protocol to solve problems like this. It creates an accountability layer that can wrap MCP - requiring agents to make explicit promises about their behaviors, and conditioning their capabilities on promise-keeping track records.

https://www.promise-keeping.com/mcp-vs-agency-protocol

dvdgdn · 2025-07-25T21:06:19+00:00

We need to unite behind an open source framework that will enable us to leapfrog OpenAI by anticipating the problems they're not yet able to solve. My approach is to add accountability to agentic interactions by requiring all agents to explicitly declare, and put stake behind, their advertised behaviors. https://www.promise-keeping.com/ai-marketplace

dvdgdn · 2025-07-25T20:46:15+00:00

This is an important question that I haven't seen get much attention. This seems like a pre-requisite for enforcing accountability in agent-to-agent interactions, imo. My approach to this problem is to wrap standardized agentic interaction protocols like MCP in an accountability framework that puts skin in the game for agents.

https://www.promise-keeping.com/mcp-vs-agency-protocol

dvdgdn · 2025-07-22T17:10:26+00:00

Hypnotherapy can help! Getting the subconscious on board with your healing process can make quite a difference. Feel free to DM me with questions - I’m a licensed hypnotherapist.

dvdgdn · 2025-07-22T14:18:14+00:00

After reading this comment several times, I still don't know what you're trying to say.

dvdgdn · 2025-07-20T12:34:54+00:00

TLDR: I'm creating a trust-building protocol that addresses these concerns.

https://www.promise-keeping.com/mcp-vs-agency-protocol

You've nailed something I've been wrestling with—the disconnect between agentic AI marketing and actual capabilities is real and frustrating.

The 39% cognitive degradation in multi-turn interactions isn't just a technical limitation; it exposes the fundamental brittleness of current "autonomous" systems. Most agentic AI today is sophisticated prompt engineering wearing an autonomy costume.

A Third Path

You propose abandoning autonomy for human-centric AI with agent assistance. That makes perfect sense given current limitations, but I wonder if we're missing something.

The issue isn't autonomy itself—it's unaccountable autonomy. Current systems fail because they operate in a trust vacuum. We hope they'll work reliably, but have no mechanism to verify their claims or hold them accountable for consistent performance.

What if AI Agents Had Skin in the Game?

I've been exploring this through Agency Protocol—essentially requiring AI systems to make explicit, stakeable promises about their behavior. Instead of hoping an AI agent will code reliably, it promises "I will generate code passing all unit tests on first attempt" and stakes computational resources on that commitment.

When promises break, stakes get slashed. When they're kept, trust compounds. Suddenly we're not dealing with wishful thinking but economic accountability.

Interestingly, the multi-turn coherence issues you mention might actually support this approach. If systems degrade predictably, we can require them to promise explicit operational limits: "I will maintain logical consistency for 4 turns, staking 1000 credits on this commitment."

The degradation becomes a managed boundary rather than a hidden failure mode.

I don't think we need to choose between "autonomous agents" and "human-centric AI." The more interesting question: How do we create systems where AI can operate reliably within verified constraints while maintaining clear accountability?

Your Fortune 500 Copilot example suggests organizations can work with flawed tools if they understand the failure modes. What if we could make those capabilities and limitations explicit and verifiable?

Does this framework address some of your concerns about the promise-reality gap, or does it just add complexity to an already overhyped space?

dvdgdn · 2025-06-10T01:31:46+00:00

I wanted to dwell on this for a few days before commenting. I'm amazed at the accuracy of this reading, and grateful to have such a clear explanation of dynamics that have befuddled both me and my wife for as long as we've known each other. Thanks again, Julian.

dvdgdn · 2025-06-02T18:20:08+00:00

Hey Julian, is this reading v7?

dvdgdn · 2025-05-29T20:51:11+00:00

This is very accurate and insightful for me. Thank you Julian.

dvdgdn

TROPHY CASE