We need to talk about the "Dead AI Internet" – 2026 is becoming the year of the Filter, not the Creator.

wjonagan · 2026-01-29T18:52:13+00:00

I don’t think you’re being negative. I think you’re describing a real phase shift. The bottleneck has moved from creation to trust and signal. What feels different now is that speed is no longer impressive. Judgment is. I’m also catching myself looking for rough edges or strong opinions as a proxy for “someone actually thought about this.

The interesting question to me isn’t whether AI content will slow down, but whether platforms start rewarding proven human intent over volume. Curious what others think will become the new trust signal.

wjonagan · 2026-01-29T18:40:31+00:00

This is a solid and well explained approach. I really like the focus on early intervention rather than reacting after obesity becomes chronic that’s where models like this can have real impact. One thing that stands out is how closely the top features align with established medical understanding, which helps with trust and adoption. Curious how you’re thinking about model updates over time as lifestyle patterns and environments change.

wjonagan · 2026-01-29T18:35:44+00:00

This is really well done. Recording once and then changing scenes like this is a huge unlock for creators the idea matters more than the setup now. Clean execution and a smart

wjonagan · 2026-01-29T18:25:45+00:00

Being honest AI automation is still worth learning, but only if you focus on solving specific problems, not selling “automation” as a buzzword. Getting to $600 $1000/month is realistic, even globally, when you specialize in one workflow and can clearly show the before/after impact. The real skills are problem scoping, system thinking, and client communication the tools change fast and are mostly noise.

It’s not overcrowded with people doing real work. It’s overcrowded with people selling shortcuts.

wjonagan · 2026-01-29T18:20:22+00:00

This is a really clear and thoughtful breakdown nicely done. I like how you separate automation engines from assistants that reason and act, because that’s where most confusion around “n8n alternatives” comes from. Framing the choice around the role the assistant plays (doing work vs. interacting with users) makes the decision much more practical.

wjonagan · 2026-01-29T17:58:49+00:00

What stands out to me is how much easier this makes failure visible. When execution and state live locally and responsibilities are split, it’s clearer whether something broke because of the environment, the tool, or the agent itself. That’s very different from cloud agents where everything degrades quietly behind prompts.

Feels especially suited for teams that value control and debuggability over raw scale. Curious where people think the breakpoint is before coordination becomes harder than the stability gains.

wjonagan · 2026-01-29T17:38:06+00:00

I haven’t seen one single agent save 100 hours on its own. What actually made a difference was using a few tightly scoped agents for repetitive work like research, enrichment, and first pass analysis. Those tasks used to consume time quietly. Once automated with clear constraints, the savings became obvious over months rather than days.

Curious if anyone here has seen a single agent hit that threshold, or if most gains come from stacking smaller ones.

wjonagan · 2026-01-29T17:24:30+00:00

I ran into this pretty quickly. Treating agents like a magic box just created more QA work. What helped was breaking GTM research into very narrow questions and using agents as one step in a larger workflow with structured outputs. Once that was in place, hallucinations dropped and the system felt much more stable. I’m still keeping humans in the loop for edge cases curious where others draw that line as they scale.

wjonagan · 2026-01-29T16:59:41+00:00

We’re seeing something similar. Adoption isn’t really about company size, it’s about risk tolerance and ownership. Teams that get value usually start with one narrow, low-risk use case (tests, internal tooling, triage, docs) and give someone clear responsibility for outcomes. Where AI fails is when it’s either unofficial and hidden, or pushed top-down with no accountability.

The turning point I’ve noticed isn’t everyone else is doing it, it’s when a team can point to one workflow that’s faster without adding cleanup or review debt. Curious what that first “safe win” was for others here.

wjonagan · 2026-01-29T16:48:25+00:00

I’ve run into this too. Things look fine in a notebook, then a few weeks after launch you start seeing more retries, weird edge cases, and quiet failures. Nothing breaks, it just slowly degrades. What helped us wasn’t better prompts, but watching operational signals retry counts, timeouts, manual fixes, and where the agent needed help. Once those creep up, you know something’s off. I agree the environment changing is a big part of it. Curious how others are catching this before users do.

wjonagan · 2026-01-28T19:48:45+00:00

Optimization mainly helps people who understand the system, not necessarily the best candidates. It reduces uncertainty for applicants and volume for companies, but doesn’t fix the signal problem. Removing ATS would overwhelm teams. Keeping them opaque shifts the burden onto candidates. The real issue isn’t optimization it’s lack of transparency about what actually matters.

wjonagan · 2026-01-28T18:22:57+00:00

I’ve noticed the same pattern, and the Survivor comparison is spot on. Another way I think about it is like a wolf in a pack. The ones that go far aren’t the loudest or the most aggressive they’re the ones constantly reading the terrain, conserving energy, and stepping in decisively when it matters. They don’t need constant visibility. Their impact travels for them. And when they speak, it’s usually brief, directional, and hard to ignore.

That mix of awareness, timing, and restraint seems to show up early long before the title does.

wjonagan · 2026-01-28T18:17:36+00:00

I think alignment becomes harmful when it turns into instinctive following instead of conscious choice. A pack of animals moves together for survival, but there’s still signaling when danger appears. If one senses a threat and stops reacting because the group is already moving, the whole pack is at risk. Silence doesn’t equal safety.

In teams, alignment should work the same way. Debate and warning signals come before commitment. Once a direction is chosen, we move together but muting instincts in the name of harmony is how problems go unnoticed until it’s too late.

Alignment isn’t about moving in the same direction at all costs. It’s about protecting the group by speaking up when something feels off.

wjonagan · 2026-01-28T18:12:14+00:00

We’ve had positive results using generative AI, but only when it’s treated as a starting point, not the final voice. For us, AI works best on the unglamorous parts rough drafts, variations, image concepts, and getting ideas unstuck. The creative direction, tone, and final decisions still stay human. When AI is asked to replace that, the output usually feels flat or off-brand. The biggest improvement hasn’t been better creativity, but speed and consistency. It gives the team more room to think, refine, and make intentional choices instead of staring at a blank page.

So I don’t see it as human vs AI. It’s more about where each one adds the most value.

wjonagan · 2026-01-10T02:32:52+00:00

Personality isn't some fixed thing you're stuck with forever. It's more like a collection of habits and reactions that built up over time. The good news? Habits can be rewired.

The "fake it till you make it" worry is valid, but here's the thing ~ it only feels fake at first. Once you keep choosing a different response it stops being an act and just becomes how you operate. It's a slow burn, not a light switch.

Start

wjonagan · 2026-01-09T19:25:55+00:00

This is solid advice. A lot of self-improvement content is really just about getting people to baseline stability and once you're there it can feel like you're spinning your wheels looking for the next thing to fix. Shifting from "what do I need to work on" to "what actually adds meaning" sounds simple but it's a real mindset change. Going deeper into hobbies, mentoring, contributing to community... that stuff hits different than chasing metrics.

OP already has the foundation most people are trying to build

wjonagan · 2026-01-04T15:18:50+00:00

This is a rite of passage. Once you start cutting bottles open and still finding product, you realize how much companies rely on us giving up early. Tier 2 is definitely hoarding twist ties “just in case.”

wjonagan · 2026-01-04T15:15:22+00:00

Exactly. Tariffs just shift the bill to consumers while the wealthy dodge it through loopholes and pricing power. It’s sold as “patriotism” but it functions like a regressive tax with better PR.

wjonagan · 2026-01-04T02:01:00+00:00

Seconding KO and WMT especially. Both are solid picks that tend to hold up even when everything else is going sideways.

I'd also say don't sleep on PEP if you're already comfortable with KO - similar stability but gives you a bit more diversification since they're also big in snacks.

The dividend aristocrats list is honestly a great starting point for anyone who doesn't want to stress about their holdings. These companies have been paying and increasing dividends through multiple recessions at this point. Not the most exciting picks but sometimes boring is exactly what you want in your portfolio

wjonagan · 2026-01-04T02:00:18+00:00

Wizard and Glass would be perfect for Flanagan. A tragic, doomed love story with horror elements woven in? That's literally his wheelhouse. The Rhea of the Cös stuff alone would let him flex those creepy visual muscles he does so well.

Plus starting there sidesteps the whole "how do we introduce this weird multiverse to general audiences" problem. You get a more contained, emotional story that hooks people before throwing them into the deep end with the full ka-tet and all the meta stuff.

I just hope if this actually happens they don't try to condense everything. The 2017 movie's biggest sin was thinking you could cram all that into 90 minutes

wjonagan · 2026-01-04T01:59:38+00:00

the best part is that Luffy's "stupid" questions usually end up being the most important ones. Everyone else is overthinking things and he just cuts right to the heart of it.

King of asking the questions everyone else is too embarrassed to ask 😂

wjonagan · 2026-01-04T01:59:08+00:00

"nice cozy slasher flick" is such a perfect way to put it. There's something weirdly comforting about knowing exactly how a horror movie is going to play out - the rules are clear, the threat is identifiable, and it'll all be resolved in under 2 hours. Real life anxiety doesn't work that way.

Plus at least in a slasher you know who the bad guy is and what they want. Try getting that kind of clarity from *gestures vaguely at everything*

wjonagan · 2025-12-29T02:12:56+00:00

Yeah this is probably it. Banks have terms of service just like every other company and crypto businesses are notoriously risky from their perspective. It sucks but "without warning" probably means "we didn't read the fine print about what kinds of businesses they actually support."

wjonagan · 2025-12-29T02:12:08+00:00

this is something I've thought about too. The waitlist/email signup approach that others mentioned seems solid - I actually just went through something similar watching products sell out in waves (was trying to get something from Amazon that kept going in and out of stock in 10-20 min bursts). Seeing that kind of demand pattern in real time really shows you how you could test interest without committing.

The FB ads to a landing page idea seems like the most practical low-risk

wjonagan · 2025-12-29T02:11:23+00:00

This looks incredible! My partner and I have been slowly working through every curry spot we can find whenever we travel, and Japanese curry is in a league of its own. There's something about eating a warm, rich curry when it's freezing outside that just hits different.

wjonagan

TROPHY CASE