Ratandeep Bansal

Building AI products

[AI Simplify @AISimplifyX]

Andrej Karpathy’s 1-hour Stanford lecture on AI engineering is one of the best explanations I’ve seen of how AI systems actually work.

The progression is simple:

10% → LLM
30% → Prompt
50% → Agent
70% → Loop
100% → Graph

The key takeaway:

AI engineering isn’t just about writing better prompts.

It’s about building systems around models — giving them context, memory, tools, feedback loops, and data flows.

“Delete everything, keep Graph.”

Definitely worth watching if you’re building with AI agents.

Watch → Bookmark it

[Codez @0xCodez]

Anthropic senior engineer just released a 1-hour course on building a team of agents with loops & graphs:

• 00:27 - introduction to CLAUDE.md & Plan mode
• 11:24 - building "skills" & "hooks" for Claude agents
• 37:02 - building agents & subagents with Claude
• 52:47 - self-improving loops & graphs for Claude agents

this 1-hour watch will replace a $500 agentic engineering course

watch today, then read how to build a team of self-improving agents that work together

[Claude @claudeai]

We’re introducing Claude Fable 5.1 and Claude Mythos 5.1.

They're the world’s most advanced models for coding and knowledge work.

[BookNote @BookNoteApp]

20 books to master 20 timeless mental models:

1) Thinking in Systems by Donella Meadows

( feedback loops )

[rari @0xwhrrari]

Andrew Ng just released a 2-hour course

On building agentic skills from scratch with Anthropic:

00:00 - How to build agent skills with Claude
22:32 - Claude pre-built skills for AI agents
41:07 - Agentic skills vs tools, MCP, and subagents
01:06:06 - Skills for long-running agents

This 2-hour watch can replace 10 paid courses on building agents

Taught with Anthropic themselves

Bookmark and watch it tonight

Then read the article below

[codila @0xCodila]

Anthropic and Andrew Ng built an agent that uses 90% fewer tokens from scratch:

they dropped the entire book of Frankenstein into a prompt - 108,000 tokens asked one question

the input dropped from 108,000 tokens to 11

here's how:

step 1 → put everything that never changes at the top - tools, then system, then docs

step 2 → mark where the static part ends. everything above it gets cached

step 3 → one stray space breaks it - and you pay full price again

step 4 → the cache dies in 5 min - every read resets the clock

step 5 → cached tokens don't count against your rate limits. free headroom

most people never touch this - it pays for itself on day one

watch & bookmark - this 1-hour brilliant course ↓

[Sam Blond @samdblond]

We just launched Monaco. Here’s the exact playbook we used. I hope it's helpful to other founders and startups:

1. The launch video: most launch videos I see orient around some stressed out person at their desk or some philosophical approach to company building. Do not do this.

[Ratandeep Bansal @ratandeep]

@solofounders Two reasons. Solo means zero coordination tax — you ship at the speed of your own decisions. And going solo is self-selecting — it screens for conviction before any investor does. The category didn't change; the toolset did — AI helps doing the work that used to need a team.

[Ratandeep Bansal @ratandeep]

4/ Call in and he'll dedicate the next record to you, by name.

Built for the @huggingface Build Small Hackathon 🌲

🎙️ Tune in: https://t.co/ttLtUuUDgY
▶ Demo: https://t.co/WgMJmVcpS1
📝 Field Notes: https://t.co/4vEciPeYbO

#BuildSmallHackathon

[Ratandeep Bansal @ratandeep]

1/ 📻 I built a 1970s all-night radio station run entirely by ONE ~1B-parameter model on a single GPU.

You tune in. Sam Dusk spins records that never existed, reads YOUR weather tonight, and answers you live when you call. 🧵

[Ratandeep Bansal @ratandeep]

3/ Stack: MiniCPM5-1B (GGUF via llama.cpp) on one Modal T4 + Kokoro TTS + faster-whisper.

Every song is synthesized live in your browser from a key/scale/tempo/timbre — no audio files, nothing copyrighted. Tune off-station and AI "ghosts" bleed through the static.

[Ratandeep Bansal @ratandeep]

📻 I built a 1970s all-night radio station run by ONE ~1B-parameter model on a single GPU.

Tune in: Sam Dusk spins records that never existed, reads YOUR weather tonight, and talks back when you call.

🎙️ https://t.co/ttLtUuUDgY
▶ https://t.co/WgMJmVcpS1

[Ratandeep Bansal @ratandeep]

Meet Professor Pip 🔭 a 3D avatar that teaches kids by VOICE! runs in browser, zero GPU animated.

Brain: MiniCPM5-1B finetuned on @modal_labs. Open weights + dataset on @huggingface. Thanks @OpenBMB!

▶ https://t.co/FzUExhZ3W0
✦ https://t.co/R0LsHxi6jO

#BuildSmall #BackyardAI

[Ratandeep Bansal @ratandeep]

@Ayussheth count me in

[Y Combinator @ycombinator]

Memoir (@trymemoir_ai) is an autonomous marketing system for software companies, letting builders focus on building.

It turns your code into demo videos and makes social posts in your own voice, automatically.

Congrats on the launch, @MaanavA51108 & @ZhanJason179!

https://t.co/cH2N0NaOP6

[Y Combinator @ycombinator]

Last week we hosted the first ever YC Paper Club in Mountain View.

We brought together great AI researchers and founders to discuss both the state of the art and what it actually takes to get it into production.

Thanks to the following presenters:

0:12 - Intro from YC Visiting Partner @FrancoisChauba1
3:49 - Tanishq Kumar (@tanishqkumar07) — Speculative Speculative Decoding (https://t.co/tFtsdZp1JC)
18:33 - Guangyao (Stannis) Zhou (@zhouguangyao) — Diffusion-MPC (https://t.co/9aIXKGgt4s)
30:26 - Isaac Ward — LeWorldModeling (https://t.co/hgXjHKsg2H)
43:54 - Akshay Vegesna (@akshayvegesna) — Deep Learning is Not So Mysterious or Different (https://t.co/o5EAC5QtV7)
51:24 - Konwoo Kim (@konwookim) — Pretraining Under Infinite Compute (https://t.co/4rArPbaZ6K)

[🍓🍓🍓 @iruletheworldmo]

how is this even legal. opus is performing significantly worse on hallucinations.

imagine relying on this model for anything mission critical and they can just swap out the model without telling for something so much worse.

genuinely don’t understand how it’s legal.

[Nakul Kelkar @MaruPelkar]

Few observations from YC W26 Alumni day

1. Founders are optimizing for speed rather than amount -
Everyone wants to close fast snd get back to building and selling.

2. Rounds are either 4 on 40 mill, 3 on 30 mill, 2.5 on 20 mill caps

3. Outliers are getting oversubscribed before the demo day. Good luck getting on their cap tables

4. Hardware and deep tech companies dominate - In the AI world, momentum has moved towards doing harder things passionately rather than building something that looks like an easy win.

5. gstack vs superpowers claud plugin - equal weightage. Superpowers for daily task. gstack for ceo mode.

6. Build energy is ⚡⚡⚡⚡⚡⚡

[Jahir Sheikh @jahirsheikh8]

Best YouTube Channels To Learn AI in 2026 (No BS)

1. Fundamentals – 3Blue1Brown
2. Deep Learning – Andrej Karpathy
3. AI Research – Yannic Kilcher
4. Practical AI – AssemblyAI
5. LLMs – AI Explained
6. ML Theory – StatQuest
7. Papers Simplified – Two Minute Papers
8. GenAI – Matthew Berman
9. AI Agents – Nicholas Renotte
10. Applied ML – Krish Naik
11. PyTorch – Aladdin Persson
12. Math for ML – Serrano Academy
13. Industry Insights – Lex Fridman
14. Real-world AI – DeepLearningAI