Rene

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[Rene @refon1004]

@georgesttock CLAUDE

[Rene @refon1004]

@mpoilerfx free

[GREG ISENBERG @gregisenberg]

The takeaway from Fable 5 being BANNED by the government: GET GOOD AT LOCAL MODELS SO YOU HAVE 100% CONTROL.

My entire weekend was going to be building my craziest ideas with Fable 5. That's now cancelled.

So instead of building with Fable this weekend, I've decided I'll go deep on local models:

1. Start with the runtime. Download Ollama or LM Studio first. This is the thing that actually runs models on your machine.

2. Match the model to your hardware. A model's size is measured in billions of parameters (7B, 32B, 70B). Bigger is smarter but needs more memory. Rule of thumb: a 7B model runs on almost any laptop, a 32B needs a good Mac with 32GB+ RAM, a 70B needs serious hardware like a DGX Spark or a maxed-out Mac Studio.

3. Know which model for which job. Qwen 3 is the best all-around choice for most tasks. DeepSeek for reasoning and coding. Gemma 4 when you need something tiny that runs on a phone. Llama when you want the biggest community and the most fine-tunes.

4. Quantization. You can shrink a model to run on weaker hardware with barely any quality loss. Look for versions labeled Q4 or Q5. This is how a model that "needs" a server runs on your laptop. Learning this one concept changes everything.

5. Connect it to your agent. Point Hermes or your agent stack at a local model.

6. Context window is your real constraint locally. Cloud models give you huge context for free. Local models make you pay for it in memory. A bigger context window eats RAM fast. Keep your sessions tight and your prompts lean or your machine chokes.

7. Learn to give local models tools. A smaller local model with web search, file access, and code execution beats a giant model with none. The capability gap closes fast when you wire up the right tools. The model is the engine but the tools are the wheels.

8. Fine-tuning is more accessible than you think. You don't need this on day one, but know it exists. You can take an open model and train it on your own data so it gets good at your specific domain.

I'll probably do a breakdown at some point on this @startupideaspod if people are into it.

The lesson from this ban is basically don't build your entire workflow on something that can disappear with a single letter. Own part of your stack. Local models are insurance.

It reminds me when people realized they don't own social media accounts. And then you saw people build email lists etc.

I remember running a startup and my biggest traffic source was organic FB. All of a sudden, algo changed, and I lost 99% of my traffic.

Same sorta moment (but bigger) for AI.

This is a wake up call.

[Rene @refon1004]

@spwfeijen USG

[Rene @refon1004]

@johnvirality 100

[John @johnvirality]

claude fable 5 just made it possible to post 100 AI UGC videos per day across 4 platforms in JUST 30 minutes of production

everything else runs 100% autonomously

clippers might be cooked 😭

this mythos model watches raw video footage and finds viral moments transcripts would miss

it scrolls tiktok while you sleep and builds trend reports, generating 100 production packages and renders them through higgsfield MCP without you touching another tab.

so i documented the ENTIRE machine with every prompt, every setup instruction, and every workflow step

here's what's inside:

→ the overnight market research system that runs while you sleep

(cowork scrolls 5 platforms, analyzes 60-80 pieces of content each, returns a trend intelligence report with 10 specific content ideas by the time you wake up)

→ raw-pixel clip identification that finds moments human clippers miss

(facial expression shifts, product reveals, body language peaks, visual incongruities. all timestamped and ranked by predicted virality.)

→ batch script and asset generation: 20 complete production packages per prompt, run 5x for 100 total

(6-shot scripts, character prompts, product frame prompts, voice direction, platform captions. 15-25 minutes total.)

→ the higgsfield MCP pipeline that renders all 100 videos automatically

(fable 5 calls seedance 2.0 directly. character reference locked. lip sync aligned. zero human involvement.)

→ the virality predictor that filters your top 20 candidates before posting

(hook score, hold rate, brain region activation. bottom 5 get diagnosed and revised automatically.)

→ the CPM math: 400 platform-posts/day × 3,000 avg views = 36M views/mo = $180k/mo at $5 CPM

→ all 6 copy-paste prompts that run the entire machine

all from my personal experience in looking behind the scenes on how Rizz App + Looksmax AI + Memix scaled past 7-figures with this method

like + comment "100" and i'll send you the ENTIRE system

(must be following + RT for priority access)

will stop sending these out in 24h...

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[Rene @refon1004]

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[Rene @refon1004]

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[Rene @refon1004]

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Create 10x Beautiful UI With Hugeicons Pro Icon Library.

[Kerry Kennedy @KerryKennedyRFK]

I am sharing a personal statement that my family and I have made in response to my brother’s announcement.

[Rene @refon1004]

@shafin1coder Yes

[Rene @refon1004]

@thetripathi58 Send

[Chidanand Tripathi @thetripathi58]

Faceless YouTube channels are one of the best ways to make money

Here's how to make faceless YouTube videos with AI & start earning online.

I just made a FULL GUIDE on how you can make $5000

Usually, I'd charge $699 for this, but today I'm giving it away for FREE

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[Rene @refon1004]

Amazing watch this video entirely created by AI without lifting a finger
https://t.co/jtgJTavK9n

Tool...
https://t.co/HDEzLz2xtd

[Rene @refon1004]

@thetripathi58 send