this is exactly why i’m spending the next 30 days building a self-governing ai system not another chatbot not a task automation a real operational brain that remembers, learns, and decides every company will eventually have one - a system that: - records every event across

our AI agents are now deployable to slack. and it WORKS as good as discord. key change: abstracted communication layer. discord and slack are now just simple adapters. switching between platforms is now as easy as changing a configurable deployment option. this is how the

our AI agents are now deployable to slack. and it WORKS as good as discord. key change: abstracted communication layer. discord and slack are now just simple adapters. switching between platforms is now as easy as changing a configurable deployment option. this is how the

i replaced a $5000/mo SEO service with a single AI agent in our infrastructure. it made a technical SEO audit on my website: - listed all of the website pages - found 404 pages - pointed out the content problems (e.g. duplicate/bad copy) - gave me actionable advice to improve

i replaced a $5000/mo SEO service with a single AI agent in our infrastructure. it made a technical SEO audit on my website: - listed all of the website pages - found 404 pages - pointed out the content problems (e.g. duplicate/bad copy) - gave me actionable advice to improve

people think fine-tuning is the answer to bad ai agents spent thousands on training datasets to customize your gpt the data science team built the perfect LoRA adapter and it still doesn't work consistently. you know why? because training assumes your agent will remember the

you know why your ai agents fail silently? they forget why they failed the first time. you ask your agent to analyze your Q3 metrics tuesday. it does great. you ask it thursday: "remember that analysis? go deeper." it doesn't remember. it hallucinates consistency because it

you know why your ai agents fail silently? they forget why they failed the first time. you ask your agent to analyze your Q3 metrics tuesday. it does great. you ask it thursday: "remember that analysis? go deeper." it doesn't remember. it hallucinates consistency because it

this is exactly true. i bet people in the comments hating on this are probably shit at everything they ever did can’t blame them though — they’re probably mad because AI replaced them.

everyone talks about larger context windows like it's the holy grail it's not. gpt 5.2? 400k tokens. opus 4.5? 200k tokens. but here's the thing: it doesn't matter how big your window is if your agent is still stateless. you're adding more cards to a poker hand that gets

everyone talks about larger context windows like it's the holy grail it's not. gpt 5.2? 400k tokens. opus 4.5? 200k tokens. but here's the thing: it doesn't matter how big your window is if your agent is still stateless. you're adding more cards to a poker hand that gets

the main problem with 99% of ai agents is data persistence like, imagine having an employee that forgets everything you said after is has completed 3-5 tasks? that's exactly how you're using ai. it's not persistent. it's a stateless function. yes, modern ai's do have memory.

the main problem with 99% of ai agents is data persistence like, imagine having an employee that forgets everything you said after is has completed 3-5 tasks? that's exactly how you're using ai. it's not persistent. it's a stateless function. yes, modern ai's do have memory.

just deployed an autonomous research analyst that runs 24/7 on prediction markets not a chatbot. not vibes. an actual research operation runs in Discord, monitors Polymarket, produces PDF reports with probability distributions, factor analysis charts, scenario breakdowns - 5-7

most ai agents are broken not in code - in conception. they're designed as stateless functions 1. you send a message 2. you get a response 3. everything resets 4. the next conversation starts from 0 this forces you into a loop: - re-explain context - re-upload files -

most ai agents are broken not in code - in conception. they're designed as stateless functions 1. you send a message 2. you get a response 3. everything resets 4. the next conversation starts from 0 this forces you into a loop: - re-explain context - re-upload files -

i don't understand people who work a corporate job and brag about 'i do most of my job with ai' you're useless to the company, friend you'll be replaced. i'd never hire someone whose job can be done with ai instead, become an ai master and start your own agency.

i don't understand people who work a corporate job and brag about 'i do most of my job with ai' you're useless to the company, friend you'll be replaced. i'd never hire someone whose job can be done with ai instead, become an ai master and start your own agency.

our agent reversed engineered a python library & implemented a new tool it can use to scrape yt channels and answer our questions using that knowledge base it did all of this at runtime, without restarting - without us having to touch one single line of code or configuration

we've been building our ai agent deployable workforce framework for the last month and have come to one fundamental conclusion... as of today, the only valid way to build ai agents is through what we call the "computer owning paradigm." let me put this in simple terms: > give

my ais are LITERALLY beefing with each other no teamwork, just constant hostility every output gets interrogated, every hallucination gets destroyed the backend agent writes code the devops agent audits for unsupported changes the frontend agent questions every function