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making ai, tech content

open to collabs, hit up my dms

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My content team is six agents (Grok Bots) and none of them sleep.

One mission control. Six agents on orbit. Each one has a single job and a fixed slot in the countdown.

> Mission control routes every request.
> Scout scans the sector and locks the sources.
> Comms writes the post and sets the hook.
> Cartographer maps the visuals.
> Telemetry reads what performed last orbit and tells the crew what to change.
> Navigator computes the launch window.
> Launchpad ships it and confirms orbit.

Scan. Encode. Map. Read. Window. Launch.

Here's what nobody tells you about content: it was never one job. It's six.

Doing all six alone gets you one post a week and burnout by month four.

The idea was never the bottleneck. Throughput was.

This removes exactly that part.

One thing I kept manual on purpose: nothing lifts off without my go. The ignition button stays mine.

Save this before you build your own crew 👇

[unicode @unicodef1wn]

https://t.co/fFsyvBHpX6

[spect @spectnfa]

A SpaceX engineer just dropped a 1-hour workshop

"I woke up today and there were 20 PRs landed. And they were good.

I don't really look at the code anymore"

0% → 09:55 - why verification is the only skill that matters
20% → 14:10 - build a feature map so agents can navigate your app
40% → 21:15 - run evals as unit tests for your skills
60% → 28:35 - let cloud agents reproduce bug reports on their own
80% → 41:10 - ban useEffect and comments at the CI level
100% → 57:00 - watch PMs ship features they can't read

Most people are still reviewing every line their agents write

Cursor engineers already moved those rules into CI

Code review is the old guardrail

The compiler is the next one

This 1-hour workshop is worth more than most $500 agent courses

Bookmark it and watch before everyone starts catching on

Then check out the complete Grok Bot roadmap below 👇

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@spectnfa @unicodef1wn @mattyp @poteto @roshan_s among all the different content about grok bot, it really stands out

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@u7niversal there's a lot of junk on GitHub, but these 10 repositories are actually useful

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@tonyprediction what a crazy article... i saved it for myself

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@gippp69 188 ai models integrated into a single system, that's smart move

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three xAI engineers built a company from an empty repo in 72 hours, live on stream.

i mapped what actually happened: 9 roles, 9 playbooks, one org chart nobody had drawn until now

watch the handoff: founders → product → eng → marketing → sdr → sales → sales eng → support → post-sales

each one bleeds into the next in real time, then the roles fold into one system running by itself

full breakdown, ready to steal:

01 - AGENTS.md: drop it in your repo root, agent reads it, stops guessing
02 - 40 antipatterns: everything that broke on stream, why, and the rule it produced
03 - 69 bot roles: job descriptions ready to paste, one file each
04 - 9 playbooks: eng, PM, founders, sales, sdr, support, post-sales, marketing
05 - economics: every cost they quoted, where the tokens actually go
06 - 24-page PDF: the whole three days as one story

nothing theoretical here. every rule came from something that broke live in front of an audience

▸ https://t.co/YvukCdjKxF

save this and run it the way the people who built it run it 👇

[unicode @unicodef1wn]

Three xAI engineers built a company from an empty repo in 72 hours, live on stream. I turned all three streams into one GitHub repo.

→ AGENTS.md - drop it in your repo root, your agent reads it and stops guessing
→ 40 antipatterns - everything that broke on air, why, and the rule it produced
→ 69 bot roles - ready job descriptions to paste, one file each
→ 9 playbooks - eng, PM, founders, sales, SDR, support, post-sales, marketing
→ Economics - every cost they quoted and where the tokens actually go
→ 24-page PDF guide - the whole three days as one story

Nothing theoretical. Every rule came from something that failed live in front of an audience.

https://t.co/HfAwBw6D5P

Save this and run Grok Bot the way the people who built it run it 👇

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@unicodef1wn i wonder what @poteto @roshan_s @mattyp will say about this

[unicode @unicodef1wn]

Three xAI engineers built a company from an empty repo in 72 hours, live on stream. I turned all three streams into one GitHub repo.

→ AGENTS.md - drop it in your repo root, your agent reads it and stops guessing
→ 40 antipatterns - everything that broke on air, why, and the rule it produced
→ 69 bot roles - ready job descriptions to paste, one file each
→ 9 playbooks - eng, PM, founders, sales, SDR, support, post-sales, marketing
→ Economics - every cost they quoted and where the tokens actually go
→ 24-page PDF guide - the whole three days as one story

Nothing theoretical. Every rule came from something that failed live in front of an audience.

https://t.co/HfAwBw6D5P

Save this and run Grok Bot the way the people who built it run it 👇

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@beamnxw build → retrieve → act → observe → ship

an absolutely correct sequence

[beamnxw ./ @beamnxw]

this AI engineering breakdown from IBM Technology is pure f*cking treasure

it explains the role as a connected system

01 Python and APIs give you the surface to build on: services, data, integrations, and the software around the model

02 RAG and embeddings solve the context layer: finding the right information before the model has to reason about it

03 agents turn that context into work: they choose tools, run steps, and move toward an outcome

04 observability closes the feedback loop: traces, metrics, failures, latency, and the evidence needed to improve the system

05 deployment is where the system becomes real: reliability, constraints, and the conditions that let people actually depend on it

the model sits inside this architecture
the AI engineer connects every layer into one operating loop:

build → retrieve → act → observe → ship

save this, then build your solo business with an AI employee ⭣

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@whemohere what a beautiful and helpful infographic. i saved it.

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@gippp69 Kimi's engineers demonstrated this very clearly

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@silentguyy66 thank you! sounds very interesting bro

[spect @spectnfa]

SpaceX engineers just dropped a free 1-hour course on building a team of AI agents

From chatbots to AI coworkers 👇

0% → 00:00 - stop using AI like a chatbot
20% → 11:15 - automate apps that have no API
40% → 22:05 - make agents split work without you
60% → 33:08 - fix a bot's mistake once, forever
80% → 44:34 - let bots work without constant approvals
100% → 53:13 - pick the first job to automate

Most people still treat AI as a chat box you hand tasks to

This shows bots with their own cloud computers, long-term memory and skills learned from a screen recording, all live

Worth more than most paid agent courses

Bookmark it and watch this weekend 👇

[unicode @unicodef1wn]

SpaceX engineers built a company live using nothing but Grok Bot.

Here's the exact setup so you can copy it ↓

They don't talk to 10 bots. They talk to one chief of staff, and it routes everything.

The team:
• You talk to one chief of staff bot
• It routes work to specialists
• One bot, one job

What they kept using:
• Routines set up in plain chat
• Bots that work overnight on their own computer
• Permissions scoped per bot

The habits that matter most:
• Read-only first, write access later
• Changing facts live in a skill, not a prompt
• "Watch the webinar, draft the email" instead of asking for links

The rest of the playbook is in the cheat sheet

Save this to build your company with Grok Bot 👇

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@unicodef1wn you saved me 9 hours, thank you so much for that

[unicode @unicodef1wn]

SpaceX engineers just spent 9 hours live showing how they actually run Grok Bot. I pulled the 30 best tricks.

Not the marketing. The setups they use every day.

One of them says she shipped 2,500 PRs last month.

Another has a bot that checks his coding agents every 5 minutes and kills the ones stuck waiting.

A founder runs a bot that signs up for competitors and tours their onboarding.

All 30 are in the image

Save this before you set up your first bot 👇

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@fluixoo if i understand you correctly, then i agree

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this is pure f*cking treasure

the biggest AI leaks all live on GitHub. free. none of this was supposed to go public

5 repos, mapped across 5 layers of how AI products actually work

full source. coding agents. frontier models. live tracker. claude code internals

01 FULL AGENT SOURCE

claw-code
▸ https://t.co/Msx8CkfnkT

clean rewrite of the leaked Claude Code CLI. 195k stars, 100k of them in a single day. nobody had done that on GitHub before

02 CODING AGENTS

system-prompts-and-models-of-ai-tools
▸ https://t.co/ncnsHHZa7j

28 coding tools with their JSON tool schemas. not just what the agent is told, but everything it's allowed to touch

03 FRONTIER MODELS

system_prompts_leaks
▸ https://t.co/fuaOYctYGg

the real prompts behind Claude Opus 5, GPT-5.6, Gemini 3.5, Grok and Cursor. Claude's alone runs 3,677 lines. The Washington Post built a story on this repo

04 LIVE TRACKER

CL4R1T4S
▸ https://t.co/PNujHQHZ1j

every big lab in one place, updated whenever a new model ships

05 CLAUDE CODE INTERNALS

claude-code-system-prompts
▸ https://t.co/epSBFi76IW

pulled straight from compiled source. 27 tool descriptions, subagent prompts, security review logic

the stack covers the full picture:

read the prompt ⮕ see the tools ⮕ study the subagents ⮕ copy the structure ⮕ ship your own agent

the best prompt engineering course ever made is 5 repos written by people who never meant to publish them

some of these can get taken down anytime, so grab what you need while it's up

save this before it's gone ⭣

[unicode @unicodef1wn]

https://t.co/mv5zEXSpPB

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@spectnfa you're welcome, sis!