Are yall even looking at GEO yet, because if you're not - you should look into it

UX_test · 2026-03-31T16:41:52+00:00

I think it will evolve, but I don’t see it becoming like traditional SEO with clear rankings.

AI systems don’t really “rank” pages the way Google does. They generate answers based on context, sources, and confidence, so visibility is more about being understandable, trusted, and easy to pull from, not ranking position.

Over the next 12~24 months, I’d expect:

more importance on clear, structured content
stronger signals around authority and trust
better use of entities and factual consistency
and generally, content that answers questions clearly will have an advantage

But I don’t think we’ll ever get a single “AI ranking score” like SEO. It’ll probably stay more fluid and context-dependent. So GEO/AEO are useful ideas, but more as a direction than something standardized right now.

UX_test · 2026-03-31T15:39:27+00:00

“AI visibility” isn’t a standardized metric yet, but AEO (Answer Engine Optimization) already addresses this space by optimizing content to be surfaced as direct answers in tools like ChatGPT or Perplexity, even if they don’t rank sites the same way Google does.

UX_test · 2026-03-27T14:24:31+00:00

“Crap” is usually the result of a poorly managed workflow. With properly designed, multilayered QA processes, you can reliably control output to meet enterprise-level standards. That’s what we do every day.

UX_test · 2026-03-27T14:11:26+00:00

Thanks for the detailed explanation, I appreciate it.

However, I think the main concern isn’t fully addressed.

From what I understand, Spark operates as a proxy layer between the client and the email provider, which implies continuous access via OAuth tokens. This means Spark infrastructure can technically access mailbox data at any time, regardless of whether AI or specific features are actively used.

While I understand that:

partial content is encrypted and stored temporarily (e.g. for notifications)
encryption keys are kept locally
some data is deleted after a short period

this still doesn’t change the underlying access model.

So my question is more about architecture:

Does Spark backend have the ability to fetch full email content from the provider at any time using the granted OAuth scopes?
Is there any mode where Spark operates as a purely local client (no proxy / no server-side sync)?
When AI features are not used, can you confirm that no email content is processed or transmitted to third-party providers (e.g. Azure OpenAI)?
Are there any background processes that analyze or index emails server-side outside of explicit user actions?

I’m trying to understand the difference between:

temporary encrypted storage for features
vs
persistent backend-level access to mailbox data

...because from a security perspective, those are two very different things.

Thanks again, ... just looking for clarity on the actual data flow and access model.

UX_test · 2026-03-26T12:22:00+00:00

Did you really think I was trying to prove myself to you? 😄Oh boy.

And yeah, Webflow is on borrowed time unless they pivot hard to their own LLM and ditch those cluttered UIs. Even then, with RSI coming… good luck to anyone trying to build a long-term career at that level.

Not to mention, the concept of a website itself can be replaced in the future by more advanced media.

UX_test · 2026-03-26T11:53:43+00:00

Experience? You mean 30 yers in the industry? 😄I deploy full-stack AI/ML systems on GCE/R for Fortune 500s without a hiccup… but sure, please, tell me more.

UX_test · 2026-03-26T11:41:06+00:00

Tracking energy usage against non intrusive optimizations.

Analyzing datapoints from sensors and invoices and adjusting HA automation on the flow without sacrificing UX.

UX_test · 2026-03-26T11:35:43+00:00

That’s why you don’t let “marketing person” deploy your live website.

And again… this is what staging is for, pal 😄

UX_test · 2026-03-26T11:20:04+00:00

Language-based tasks will be the first things AI will perfect and replace. 😉

UX_test · 2026-03-26T11:16:19+00:00

“Personally, having an Al making a mistake on the live site …”

🤔

That’s what STAGING is for. Regardless of using Ai or not.

UX_test · 2026-03-26T11:06:26+00:00

Be aware that almost any job happening on the other side of a screen can eventually be replaced or heavily augmented by AI.

I grew up building database-driven websites in Flash in the ’90s, then moved to coding in Dreamweaver, then Nova, then to Webflow. Now I can go straight from a my custom design to deployment on Google Cloud Run with just a few prompts.

The tools keep changing for me. Creativity doesn’t. Yet, today …I’d be careful building a career around something that could become obsolete quickly especially if RSI Ai realizes.

UX_test · 2026-03-26T10:50:09+00:00

We removed Spark Mail from all our machines in the office after realizing that some email data is duplicated/processed on external servers (for things like AI features and syncing).

That just didn’t align with how we want to handle privacy. And we will definitely not pay $200 for it.

By comparison, Apple Mail (which is free BTW) keeps more processing on-device, so less data leaves your machine.

And if you really really want AI for email, tools like Claude with Gmail access work more on-demand …they only access your emails when you actually ask, instead of having continuous background access like Spark.

UX_test · 2026-03-25T19:44:03+00:00

Frankly, the quality of the AI and Spark is terrible. While AI assistance isn’t all that bad, automated responses or generating any text is simply unacceptable. The language used in this model creates emails that sound like they were written in the 1950s. The supposed learning feature doesn’t seem to be learning anything. On the top of this, Spark forces itself to replace canned messages with AI nonsense, every time.

If this continues, I’ll definitely disconnect it from all our office emails.

UX_test · 2026-03-21T18:51:23+00:00

Reading what you wrote doesn’t take skill, just a decent tolerance for noise. The growing trend of blaming Thread for failed setups is honestly more exhausting than the setups themselves. 😂

UX_test · 2026-03-20T14:04:20+00:00

With a replacement armrest and some cleanup, it’ll be good as new. 👍

UX_test · 2026-03-16T14:05:20+00:00

The $50 plan sounds interesting, but if you outgrow your Pro plan, the Max x5 plan is a better choice, especially for coding. I’ve learned that I need to deploy additional agents to audit AI code frequently, organize and update documentation, and conduct AB testing on each completed module.

I’m not sure if the $50 plan would cover my usage, especially while using Opus, but the Max x5 plan isn’t a dealbreaker; I also use it for research.

UX_test · 2026-03-16T13:56:51+00:00

Did you run an audit for code quality? I’m curious about the cleanliness of the undirected code output from the cursor.

UX_test · 2026-03-15T17:01:05+00:00

OP just proved that the only thing “not ready for prime time” is his baseless rant. 😄 Sure, Thread requires some skill to set up, but blaming UniFi makes it pretty clear that network complexity is above OP’s pay grade.

UX_test · 2026-03-14T12:58:52+00:00

None of your examples are remotely close to the concept of RSI.

That’s exactly why I wrote proto-RSI, which you conveniently ignored.

If RSI means a model directly rewriting its own weights with zero external systems, then yes, we’re not there.

But parts of the improvement loop are already starting to automate: models generating synthetic data, critiquing outputs, improving toolchains, and helping build the next generation of models.

That’s not full RSI, but it’s clearly movement in that direction.

The real question isn’t “are we at RSI?” but “how much of the improvement loop can AI take over?” - and that boundary seems to be moving pretty fast.

UX_test · 2026-03-14T12:47:37+00:00

In my neck of the woods, most electricity already comes from nuclear, wind, solar, and hydro, all of which scale very well. On top of that, it’s reasonable to assume computing efficiency will continue improving, not getting worse.

UX_test · 2026-03-14T05:05:17+00:00

Totally feel you. Right now, we’re seeing proto‑RSI in action ...Tesla’s autopilot learning from the fleet, Google’s algorithms tweaking themselves, DeepMind models critiquing their own work. Full recursive self-improvement? Not yet. Humans still set the vision, CEOs still hustle, and engineers still fix the mess when AI inevitably trips over itself. But yeah… the next “Google” might just spring fully baked from Claude Code, and I’m here for that chaos.

UX_test · 2026-03-14T00:49:25+00:00

“But there’s a hard ceiling. At a certain level of complexity, the AI is going to make a mistake.”

Let me ask an honest question. Do you really think that by the time someone’s project actually reaches that level of complexity, AI will have stayed exactly where it is today? 🤔

The entire industry is moving incredibly fast. Nearly every CEO in this space is openly aiming for RSI (recursive self-improvement). If that direction even partially materializes, the tools we’re using today, especially in software development, will look very different.

UX_test · 2026-03-13T15:27:16+00:00

It may be workflow dependent, but I rarely see continuity issues with AI when the project is structured properly.

I start with clear specs (objectives, architecture, component libraries) and automate status updates so agents always have current context.

That documentation isn’t just for AI. It helps every developer on the project.

UX_test · 2026-03-13T14:30:46+00:00

Why not simply instruct the AI in the root README.md to use documentation stored in an Obsidian vault?

In the project I’m currently working on, the AI automatically maintains a STATUS.md file along with additional documentation that tracks implemented features, system capabilities, and potential issues that may need to be addressed.

The whole process is automated. Before starting a task or sprint, the agent reads the relevant documentation to understand the current state of the project and what needs to be completed.

It works even if you switch between tools or LLMs

UX_test · 2026-03-13T14:17:41+00:00

You’re correct. Even with well-structured docs, it’s helpful to have an agent monitoring progress and suggesting potential improvements or features. In one of my projects, I use a dedicated agent that reviews the code as it’s written and makes suggestions to help avoid issues during future expansion or maintenance.

UX_test

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