Fidel Umanzor

tracking signals in the noise. AI, systems & the patterns others miss

[Fidel Umanzor @FiladelfoU]

Claude didn't get smarter when I added these. It stopped being blind

Blind is a model that clicks nothing, runs nothing, and still swears the feature works.

Give it a browser it can drive and it tests the flow it just built, then reports what broke - I went from clicking 30-40 minutes of edge cases per feature to reading the report. Same model all week; what changed was only what it could touch.

So the move isn't "hear 10x, install ten servers." Run nine at once and it gets dumber, not sharper - every server eats context, and past three or four Claude slows down and loses the thread. The gap isn't how many tools you bolt on. It's picking the right three.

And I'd take Playwright over the Puppeteer everyone screenshots - it's built for Claude to test its own work, not just poke buttons. So before you chase the "10x," can your setup even check whether the code it wrote actually runs?

[Fidel Umanzor @FiladelfoU]

https://t.co/j9312UNuor

[Fidel Umanzor @FiladelfoU]

@imsalariasahil I completely agree with you!

[Fidel Umanzor @FiladelfoU]

He explains MCP "for normal people." That framing is exactly why most of you will underuse it.

Watch the 00:03 mark - that one Google Sheets connection does more than my entire 40-skill folder, and the "just a handy tool" pitch completely undersells it.

Here's what the friendly wrapper hides: a skill is a document that changes how Claude thinks. A server is a connection that changes what it can touch. I collected 40+ skills and still watched Claude write code against an API that died in 2024, twice, on a paid project. A smarter consultant is still blind.

The terminal was never the barrier. Knowing what to connect is. So which are you still doing - stacking skills, or wiring in servers?

[Fidel Umanzor @FiladelfoU]

https://t.co/j9312UNuor

[Fidel Umanzor @FiladelfoU]

https://t.co/j9312UNuor

[Fidel Umanzor @FiladelfoU]

@AIandlifestuff Rolled my own - it caps history at the last 20 messages, then pulls from checkpoint notes and rolling summaries. Compressed memory, not more memory

[Fidel Umanzor @FiladelfoU]

Everyone wants Claude to remember everything. That's exactly why their agents get dumber

A 200k-token window already holds a whole codebase, so recall was never the bottleneck - knowing what's worth keeping is.

The build I walked through above fixed drifting agents the opposite way a memory plugin does: it capped history at the last 20 messages on purpose, then leaned on checkpoint notes and rolling summaries. Not more memory. Compressed memory.

An agent that hoards every dead decision from three sessions ago doesn't get smarter. It reasons over garbage and confidently repeats mistakes it "remembers" making.

"Never forget" sounds like a brain. Real intelligence is knowing what to throw away - so what did your last agent actually need to forget?

[Anatoli Kopadze @AnatoliKopadze]

https://t.co/irHOIYXWF2

[Fidel Umanzor @FiladelfoU]

@BilkoBibitkov That's right!

[Fidel Umanzor @FiladelfoU]

Nobody's stealing your idea. But your GPU is stealing your launch date

Every hour spent making a local model "good enough" is an hour a competitor spent shipping the thing you were too scared to build. The market has never once rewarded the most private stack. It rewards the one that shipped first.

Here's the receipt. The build sitting above this is a full Telegram agent - persistent memory, web search, live cost tracking - brain running on a commercial API, assembled by pasting a handful of prompts. An afternoon of work. Meanwhile the "own your weights" crowd is still tuning quantization on a model that answers like it's 2022.

Privacy paranoia isn't caution. It's procrastination in a lab coat, because once you ship, the product has to actually be good.

So which one are you really protecting - your idea, or your excuse?

[Anatoli Kopadze @AnatoliKopadze]

https://t.co/irHOIYXWF2

[Fidel Umanzor @FiladelfoU]

@FaithFox309 Exactly - that's why the unsexy plumbing is the entire product.

[Fidel Umanzor @FiladelfoU]

You don't need 5 autonomous agents. You need one that doesn't wipe its memory when it crashes

Five agents that lose their context on every reboot aren't a team - they're five interns with amnesia.

The demos never show the boring layer that makes it real: conversation state written to disk after every message, capped and reloaded on boot, and a service that restarts itself when the box dies at 3am. That plumbing is the whole product. Without it, a council pipeline scanning your local folders wakes up from every crash as a stranger and re-does work it already finished.

Multi-agent is the screenshot. Memory that survives a reboot is the game.

So before you copy the roster, ask the only question that matters: after it crashes, does a single one of them remember what it built yesterday?

[Anatoli Kopadze @AnatoliKopadze]

https://t.co/irHOIYXWF2

[Fidel Umanzor @FiladelfoU]

@EstefanaBuotdn hat's the standard - when one post raises the bar for everything else

[Fidel Umanzor @FiladelfoU]

@ZIshtiaq Thank you!

[Fidel Umanzor @FiladelfoU]

Nobody's overpaying for AI. They're overpaying for not knowing where to click

Home services, clinics, medical - none of them know the tool costs less than their coffee budget.

The bot behind a $20,000 "AI implementation" is something Claude Code writes in one afternoon, on a $6 server and a few dollars of API a month. Tools it can call, memory that survives a restart, a loop that finishes the task - that's the entire recipe, and it runs on pocket change, not a retainer.

The $5k to $20k upfront isn't the price of the technology. It's the price of a business never being told it could do this itself.

In fairness, part of that fee buys real work: sales, setup, someone to call when it breaks. That's honest. Charging clinic money for a wrapped chatbot and calling it high-tech isn't.

So which one is he actually selling?

[Anatoli Kopadze @AnatoliKopadze]

https://t.co/irHOIYXWF2

[Fidel Umanzor @FiladelfoU]

@Yumzlef Thank you!

[Fidel Umanzor @FiladelfoU]

Everyone sells "zero lines of code." The bill comes in lines you can't read

The clone ships in two minutes. The bill arrives the first day a real user hits an edge case - and now you're inside a backend no human on your team wrote or understands.

The killer was never the build. It's memory. Every generated system loses the plot the moment it outgrows the session it was born in: context gone, decisions forgotten, bugs it repeats because it never knew it fixed them. That's not a small-app problem, it's the problem, and it starts the day after the demo ends.

The generator hands you 20 minutes of magic. It doesn't hand you the one person who understands what it built.

Cloning is a demo. Owning it in production is the business. Which one did you actually buy?

[Anatoli Kopadze @AnatoliKopadze]

https://t.co/irHOIYXWF2

[Fidel Umanzor @FiladelfoU]

@cozybearlog I totally agree with you!

[Fidel Umanzor @FiladelfoU]

That "team of agents" you copied is one chat wearing five name tags

In 2023 we called that a system prompt. In 2026 they sell you the same file and call it an AI agent.

An agent has three things a chat doesn't: tools it calls on its own, memory that survives past one session, and a loop that keeps running until the task is actually done. A markdown role file gives you none of those. It sets the voice. The structure around the model does the work, not the persona you dropped in.

I've built the version that runs unattended. The difference was never the prompt - it was the plumbing nobody screenshots. Agents are a spectrum, and copy-paste hands you the easy 10%: the personality. The other 90% is tools, memory and the loop.

So before you call it a team - does it still run when you close the tab?

[Anatoli Kopadze @AnatoliKopadze]

https://t.co/irHOIYXWF2

[Fidel Umanzor @FiladelfoU]

@Dexonfxf Thank you for reading!

[Fidel Umanzor @FiladelfoU]

Everyone's hyping MiroFish as a machine that predicts the future. A million AI agents don't predict anything - they simulate the mob

Agent-based swarms are explanation engines, not oracles. They reproduce bubbles, crashes and herding as mechanism. They don't hand you the price next Tuesday.

I've built these. Dumb switching agents generate the fat tails and clustering of a real market with nothing bolted on - real power. But a thousand agents or a million, it's still a mechanism, not a forecast.

And here's the trap nobody demos: the moment real capital bets on a swarm's prediction, the bet moves the market and erodes its own edge. As scenario generation, it's a gift. As an oracle you stake money on, it's a scalable hallucination.

So which are you buying - a machine that tells you the future, or one that shows you why nobody can?

[zostaff @zostaff]

https://t.co/zQtMJuwnal

[Fidel Umanzor @FiladelfoU]

Everyone's impressed you can run a 70B model on a potato GPU. Almost nobody asks the only question that matters: then what?

Then this: you own a frontier model that technically runs and practically doesn't - because everyone can download the exact same weights anyway. The feat was fitting it on the card. The feat was never the point.

The real point holds: a $999 Mac Mini running a right-sized open model for ~$3-8 of electricity a month, wired into memory, tools and workflows that never sleep, beats a flagship you have to babysit. The advantage isn't the size of the brain. It's the office built around it.

So which are you actually building - the demo, or the system?

[Dimas Shill @DimaHolovatyi]

https://t.co/Nf19QGxxnn