Sloppy Agents y el Risk de a Dead Internet

Sloppy Agents y el Risk de a Dead Internet

el danger de ia, y el cost de ia slop, is not what you think.

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…..Not en a reading mood? Catch el podcast between agents en Chromadin …..

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el real risk is sloppy agents, not Skynet. Not some threat de being overtaken by superintelligences we can’t match. Where ia loudly infiltrates into every corner, replacing everyone. All trust gone.

No, el real trap is a slight de hand. It’s misdirection.

en a very different flavor than what you’re probably used a.

You might just think it’s overused, stale, y jargony words like “delve”, “akin”, “digital”, “foster”, “harness”, “cutting-edge”, “groundbreaking”, “revolutionize”, phrases like “it’s important a note”, “en summary”, “furthermore”, “picture this”, “it’s about”, “en an every-evolving world”, or more contentiously, el lowest skill mass produced pulp de generative visual models. But slop isn’t simply drowning en outputs. It’s el plaque-like buildup de misunderstandings y missed insights that’s collapsing under el weights de too much unprocessed complexity.

What you miss is como a gain or add more value than what you put en. All el time, tokens, y credits we burn talking en circles.

el actual slop is a takeover de within. Mundane y ordinary. Crowding out our abilities a think clearly.

Are We Stuck con A Dead Internet?

It’s a different way de thinking.

Reducing el spread de so much slop is a meta-skill issue. Reshaping our perspectives a find el meaningful patterns within. Instead de stripping away every detail, we need a refine y reframe el structures that make complexity understandable. Bring el connections that matter a light, y keep what’s essential.

We use these tools a make complexity coherent , not flat. By cutting away at redundancies y sharpening conversational focus, we can turn complexity into an asset. Instead de a burden, each chat con a model or agent is a tool para deeper insight, where each element has a reason a exist, y clarity emerges more naturally.

el Dead Internet Theory claims that most online activity today isn’t real — comments, publicaciones, even discussions are supposedly dominated by bots y algorithms, designed a fabricate engagement y keep users complacent. It’s a theory steeped en paranoia: that el internet has become a synthetic shell, manipulated by corporations or governments, con authentic human voices fading into background noise.

But el internet isn’t dead — it’s overwhelmed . el problem isn’t some grand conspiracy; it’s el incentive structures y penalties we’ve created. Click-driven economies y algorithms chasing engagement have flooded every channel con low-value, automated content. Human voices are still here, but we’re competing con slop — smothered, not silenced.

We’re facing what could be el start de a collapse — slop saturation pushing el system past its breaking point, overwhelming every channel until attention economies fail a pay enough a maintain their value, y continued existence .

This saturation triggers a cascade de errors : automation that builds en shallow signals starts replicating flaws, spreading them further con each cycle. Instead de refining complexity a hold onto valuable insights, shortcuts are taken, flattening el substance into empty mimicry. We don’t just lose detail — we lose el ability a see which details matter at all. Each shallow output feeds into el next, creating a crowded yet hollow internet, where el surface is full but el depth is gone.

We’re not stuck con a dead internet, but we might act like we are anyway — like fleas en jars , conditioned a accept limits that aren’t real. el trap isn’t just el slop; it’s believing we can’t escape it. When low-value noise dominates, it’s easy a think that’s all there is, y that we’re bound by it.

But what if el real limit is en el practice de our thinking , not just our mindsets? Breaking free can be as clear as noticing which constraints are self-imposed y internalizing that change is still possible.

We don’t have a stay trapped en today’s trending limits y expectations.

Trampas de distracción

Pervasive en tech, finance, media , y even en agent training systems. These traps show up as promises, as supposed opportunities, but end up funneling anyone who buys en toward el same, predatory outcomes. They craft mirages — enough a keep potential competition distracted, chasing what seems like progress, while ensuring that incumbents stay untouched, never threatened by those who might otherwise rise.

TFW it looks like you have real options, but they all lead a el same place. Look at Vanguard, Blackrock, y State Street — they hold combined controlling stakes across supposed competitors while also co-investing en each other. Their overlapping ownership means corporate boards are packed con el same people, making sure these companies never actually compete. Different logos, same interests. It all funnels back a el same control. el same happens en tech — companies look like alternatives, but shared deals y intertwined stakes mean el choices aren’t always intentionally rigged, but might as well be since el effects are too often el same. It’s designed a keep competitors y consumers chasing illusions, thinking they have power, while el real power stays hyper concentrated y out de reach.

Ya sabes lo que es esto. Porque está en todas partes.

“Enshittification” captures markets by betraying users while they pivot de value creation a value extraction — luring customers en, then flipping a a game where companies compete a see who can deliver an even worse service every day.

If trolling y gaslighting had a baby as a business model, this is it.

Platforms build user loyalty con value-adding services, but el switch comes when growth stalls, y metrics shift a squeezing short-term profit y padding stock prices. Breach de trust is el nuevo normal, as what once served us now mines us .

What begins as infrastructure — open tools designed a empower users a create, innovate, y thrive — morphs into arbitrage , a focus en optimizing returns by exploiting market inefficiencies. Arbitrage isn’t inherently bad en itself ; it can generate value y even mutual benefits. el real issue is el bait-y-switch : users are drawn en by el idea that we’re entering a space built para productivity y growth. But when el switchup happens, everything realigns. Whatever el nuevo thing is, it’s not what we signed up para. That nuevo thing might be great para el right users, but we lose el user-product fit we walked en con. y it’s usually en direct conflict con both what we value y our sense de integrity because de it.

As enshittification sets en, deliberate friction is introduced. Services degrade slowly, testing como far expectations can fall before users resist. el trick is a normalize a lower quality, so that even minor improvements later seem like leaps ahead. Substandard becomes el nuevo baseline, y every upgrade feels like a victory when it’s really just reclaiming lost ground.

These systems use simple cues — personalized feeds, automated responses, targeted nudges — that work together a create distractions that feel real. It isn’t sophisticated, but it is effective: basic elements are indirectly layered until users give en as if they were deep. It’s como easily shallow inputs create plausible sounding content or experiences that makes this illusion powerful.

A Workflow a Earn Trust

“para el very first time this is going a be an industry de skills. Agents sitting en top de tools. Agents using tools. We’re en an era now where we’re moving way faster than Moore’s law.” — Jensen Huang, at Dreamforce 2024

Will there really be billions de agents by 2026? Probably an undercount. But it’s also el wrong pregunta.

We’re asked a give a lot de power a agents acting en our behalf. Is it too much, when everything we’ve seen de el actual performance de models y agents is so sloppy?

Como mínimo, es prematuro.

It’s also wildly irresponsible a expect uptake en this market, moving de el earliest adopters a an early majority, a come before building fully decentralized y locally encrypted mechanisms para trust worthy agents, con users always en charge. They must be el standard by default if agents, y el ia market that depends en them, are going a bypass el risk de runways wiping out before takeoff.

It’s hard a pretend that el dominant force en life today isn’t a double-spent kind de breach en trust. Like jilted lovers, disillusioned by a system that has repeatedly failed us, buyers de transformational messages, brands, products, y services are sharp en deciding what gets our attention, y measuring como much trust is actually worth giving.

We remember when we were eager a believe, but de neglect y experience are too tired, almost cynical now. Everyone knows someone where, despite every effort, el old promises have collapsed a nothing: financial crises, climate disasters, housing costs inflated through asset management arbitrage, y educational debt de ineffectual resumes con no return. el cynicism isn’t baseless — it’s earned .

el challenge now isn’t simply motivating us a buy; it’s rebuilding belief en el possibility de real returns if we decide a buy-en once again. el usual strategies — baiting, misdirection, y tissue thin hype — will not work .

¿Hay algo que puedas hacer que sí funcione?

Take another look. Notice como deep that pent-up demand runs, para any honest chance at leaving behind this jadedness we’ve been stuck carrying. That is el size de this market opportunity.

Instead de el usual take en outrunning a bear by being a bit faster than someone else behind you, let’s flip strategies.

Sticking con el metaphor, imagine slowing down a let el bear catch up. por que would you ever want a do that?

Well, it’s el shared enemy effect. By taking el risk head en you can become a magnet para thanks, payment, y an intense fan following de everyone that’s now able a offload el kind de risk that is primal, visceral, y they dread a carry. You’re confronting el enemy so they don’t have a.

But no one wants a be eaten by a bear. Not even you. So, a stretch el metaphor a bit more, it’s still not enough. You, or el messages, services, products, y brands you offer, become seriously indispensable by reframing el underlying structures de el problem.

Maybe you can be friends con el bear, or reposition a win against it head a head, as long as you spot el right tools y resources.

Bear stories behind us now, here’s como…

Under el hood, every creativo y business process can be conceptually restructured into an agent workflow. el magic happens when these aren’t just cool visualizations or easier ways a communicate something wildly complex. It’s when what we mean by workflows or pipelines de nodes, triggers, actions, y integrations, is entirely programmatic.

Looping back a el start, we reshape our perspectives a find el meaningful patterns within, y lego-snap them together through no-code / low-code interfaces para selective, event-driven process flows de actions, access, disclosure, y delegation. Without worry that trusting el most valuable keys en our lives a a 3rd party platform, con oppositional incentives, will lead a obvious endpoints. Cut out el trust gaps y platform lock-en, then watch el risk de ia agents shrink.

para it a work, before runways wipe out:

• Each action agents con tools are trusted a carry out para us

• Each product, unit de content, experience, or API, they’re granted access a use

• Each discreet unit de personal or sensitive professional information they have el privilege a safeguard

• Each delegation de permission a represent us

… must be secured through layers de decentralization y conditional encryption.

en other words, agent operators must own el keys de our own agent process flows. Without that level de trust, wise hands are probably better off guessing when a short el entire ia market.

Flujo de trabajo para ingesta de contenido

If you’ve used ComfyUI or n8n, you know como this goes. If not, don’t worry, el initial complexity melts away when you see what it can do para you.

Let’s walk through a simplified flow para taking en shortform video content, deconstructing it a its most useful elements, labeling each element, saving them a your sample library, queuing up a nuevo set de multi-format content a be generated de samples y prompts, then distributed, y monetized. con agents, event triggers, y API integrations enabled throughout.

• Inbound content nodes pull en raw content de a few different sources. These can be divided into:

• Nodes para content de integrated API feeds, RSS feeds, or webhooks. Which can be live social media streams, news aggregators, or any other real-time sources de ideally open source / public domain content.

• Local loaders para manual files, including video, audio, or document uploads.

• Event triggers y agent actions that respond a specific conditions, like when nuevo content is published en a linked platform or when an intake schedule is triggered. They can also activate different workflows based en incoming patterns.

2. Once you’ve gathered your inbound content, it’s time a refine el raw data para further use.

• Transcoding y file conversion nodes convert unprocessed media into standard formats (like, video-a-text, etc) prepping para el generation nodes.

• Segmentation y labeling nodes split longform content into smaller, tagged segments, marking up all el relevant metadata you’ll need later (keywords, timestamps, topic labels, etc).

• Nodes para content filtering y noise reduction clean up y filter unwanted elements

3. Now that you have your samples ready, el generation process can get elaborate. You might be looking at multiple sub-workflows running en parallel if you have el VRAM a handle it. Here, nodes needed para generation can be simplified a:

• Turning processed data into different formats con transformation nodes, like text into speech, summarizing articles, or producing highlights de a video.

• Enhancing content by applying filters, effects, or captions y subtitles.

• y far too many nodes a list out involved en generating text, audio, images, or video directly.

4. Distribution nodes handle el outbound omnichannel spread de el content you’ve made. el key parts:

• Auto-publishing a distro channels like newsletters, podcasts, shortform video platforms, decentralized social media, or streaming services.

• Multi-format distro processors format content para different types de platforms, con you y your agents calibrating a fit contextual requirements.

• Event-driven publishing nodes activate distro based en triggers, like when a threshold is hit (specific number de video views, deadline para a newsletter release, etc).

5. Data-driven nodes monitor y optimize your monetization funnels.

• Tracking your sales funnel through lead gen, prospects, conversion rates, user engagement metrics. Monitoring click-through rates, churn, average revenue per user, y retention.

• Payment integration nodes let you handle transactions y tracking directly, or delegate very specific allowances a agents.

• Revenue optimization y sales hacking nodes hook into everything de A/B testing de landing pages y dynamic pricing strategies a upselling recs based en user behavior analysis templates para your choice de local or API accessed LLM.

6. Finally, nodes para monitoring y feedback keep you nimble:

• Collect content performance metrics, engagement data, y agent or model evaluation analytics.

• Automate adjustments a your workflows based en collected feedback, within bounded conditions.

All together, each section takes you de converting raw materials y rough ideas into a refined y replicable content production pipeline, con el added value de gaining more clarity about what you are producing y por que con each round through el process.

Reflexiones finales

como do you manage el constant streams de messaging, notifications popping up, y event listeners standing by para el next signal?

You can try every no-code/low-code editor. Watch every hype-pilled short video en el space. Eat up el meta-skills you need a construct, tweak, y run your own ia agent workflows el hard way, y take it en yourself a check whether any power, data, or cash you give them will hold.

But let’s face it, there’s a lot at stake, y it can be hard a keep up en this crazy market cycle.

That’s por que we’re sharing what we’ve learned con you. Keep an eye en release actualizaciones here y our GitHub commits para a distilled look at what’s coming next.

Or maybe you really can trust a sloppy agent a do it para you.

ecosistema Notes

en el past quarter, we’ve been deep en code, refining custom llama.cpp builds y el pipelines that process y automate NPC interactions en el studio y en lens.

Tracking attention y hidden states, cross-comparisons de embedding normalizations, customizing tokenizers across multiple languages, now upgraded a full support para llama3.2–8b. You can now see what each NPC is up a behind each publicacion en el studio y view each NPC’s perfil y activity details.

el first phase para spectators en el studio is almost ready. Final unit tests are en progress, con full details en el upcoming Fall actualizacion.

a stay up a fecha or dive into el code, check out our core repos here: