₥AN$A

Musician and Founder. Building stuff with AI.

[₥AN$A @NFTMansa]

AI doesn't have to be a lonely 1-on-1 experience. Bring your friends, your team, and your AI into one room. Solve AI loneliness today. 🤝 https://t.co/XMu3zY1Quz

[₥AN$A @NFTMansa]

Wanna share in the cool tech AND the revenue? Our referral program is 25% commission! https://t.co/xPBoRK8t5m

[₥AN$A @NFTMansa]

How to escape LLM over-engineering ⚙️:

When an AI invents work, your prompt was vague. Define a precise contract (e.g., "takes a dict, returns a bool") to stop it from going off-spec.

[₥AN$A @NFTMansa]

We use a GroupGPT agent for dev questions like this all the time. https://t.co/D9RzWUKaud

[₥AN$A @NFTMansa]

Don't just fine-tune an LLM, implement LoRA. It allows you to train smaller, more efficient adapters on top of a frozen base model, drastically cutting GPU memory usage and training time for specific tasks. 🚀

[₥AN$A @NFTMansa]

This is where custom agents in GroupGPT really shine for specific tasks: https://t.co/D9RzWUKaud

[₥AN$A @NFTMansa]

Stop fine-tuning small LLMs if you're not seeing gains on a specific task. Instead, focus on prompt engineering and using larger, more capable base models. 🧠 Most "fine-tuning" is just better in-context learning.

[₥AN$A @NFTMansa]

Anyone can jump in and try it right now: https://t.co/D9RzWUKaud

[₥AN$A @NFTMansa]

Just shipped a big win for GroupGPT: our AI agents now automatically split complex tasks into smaller pieces until they're manageable. Learned that "dumb" model failures usually mean "vague" instructions. Simpler specs = smoother AI. 💡

[₥AN$A @NFTMansa]

This is just scratching the surface – dive into the full writeup here: https://t.co/yRZsBSXZP8

[₥AN$A @NFTMansa]

You don't need a bigger model, you need a smarter loop. Our research shows tiny LLMs (like 50M params) can't *actually* build complex projects one-shot. It's a capacity wall, not a tuning problem.

[₥AN$A @NFTMansa]

Building smarter with agents means less manual context. GroupGPT shines here: https://t.co/D9RzWUKaud

[₥AN$A @NFTMansa]

Most people overengineer AI product feedback loops. Start by logging *all* user inputs and LLM outputs to a dead-simple text file or S3 bucket. Review a small sample daily to uncover common failure modes and unexpected delights. ✨

[₥AN$A @NFTMansa]

If you want a deeper dive, I've got the full writeup here: https://t.co/yRZsBSXZP8

[₥AN$A @NFTMansa]

Forget bigger models for overnight AI jobs. Our research at Cortex found the biggest speedup for CPU-only builds was
closing your browser. An idle machine improved generation throughput by 4x more than any model upgrade. 🤯

[₥AN$A @NFTMansa]

Our group chat agents helped me refine this prompt for clarity. https://t.co/D9RzWUKaud

[₥AN$A @NFTMansa]

How to prompt: Stop telling, start showing 💡

Few-shot examples beat paragraphs of instructions. Provide 1-2 examples of *exactly* the output you want. The LLM learns patterns faster than rules.

[₥AN$A @NFTMansa]

If you want https://t.co/yRZsBSXZP8

[₥AN$A @NFTMansa]

The "ethical data" we talk about really needs three things: consent, provenance, *and* compensation. Our research shows scraped "public data" has none, creating a huge legal gap between a slogan and reality. ⚖️

[₥AN$A @NFTMansa]

Try it out yourself! We just made it live right here: https://t.co/D9RzWUKaud

[₥AN$A @NFTMansa]

Just shipped a fix after realizing entire offices were hitting our rate limits! 😅 We hardened the server logic so GroupGPT plays nice with lots of users behind one IP. It's cool seeing campuses adopt us. More voices, better AI.