Yaowei Zheng

In the AI era, once a task can be measured and automated, it is not far from being maxed out. #randomthinking

What I learned from Kimi Code's system prompt: No matter how complex a system prompt file looks, it eventually comes down to two things: one clear sentence defining the task goal, and a lot of relevant background context. github.com/MoonshotAI/kim…

@aibekjumabek Let's connect

AI Engineers, let's connect!

@isha_singh06 Let's connect

@code_hiyouga let's connect

New week of #buildinpublic 💪 What are you building this week? 📷 Looking to #connect with founders, builders, entrepreneurs, and people working on: SaaS, AI/ML, Vibe coding, AI agents & workflows Drop your project below. I'd love to check it out and connect.

@ScatterLabz Hi

@code_hiyouga Hey, lets connect.

@i_am_jeganraj Lets go

@code_hiyouga Let’s connect

@Vahan_Drnoyan I like it

@code_hiyouga Hey I am building AI powered knowledge organizer app, lets connect.

@ArislanbekInc I'm currently building an optimization platform for agents now

@code_hiyouga we are building ai-powered call center. How about you?

@_deep_star let's goo

@code_hiyouga Let's connect

@alexx_p977 Would love to connect

I want to connect with: > founders > builders > vibe coders > freelancers > motion designers > brand designers > AI startup employees If you’re someone that is BUILDING I want you know you

@praj_kesi let's go

I want to connect with more: founders developers vibe coders agency owners people with agency If you’re someone building with AI right now, drop it in the comments and let everyone take a look!

Without human input and constraints, AI-generated writing often lacks real insight. Maybe it's time to stop asking AI to "just write" and start giving it better prompts.

in @ycombinator they have a playbook on how to get customers ASAP for your startup. if you follow this, you’ll brute force your way to 100 customers, almost no matter what your product is. Here it is: 1/ launch-max. product hunt, hackerNews, devhunt, betalist, peerlist, indie hackers, etc. YC tells you to launch 3 times MINIMUM 2/ pull your competitor’s strongest backlinks and get yourself listed in the same places. whatever article they have listed, you make a better version and ask the site to replace it (or supplement) with yours. 3/ WARM OUTBOUND. Everyone knows about building in public. but you still need to capitalize on the 99% of leads who see your content but don’t come inbound scrape everyone who likes your posts on Linkedin each week, check if they fit your customer profile, and message them. you set this up to fire automatically with @origamichat (i dropped a prompt in the comments) 4/ find 20 to 30 ugc creators on tiktok / instagram in your niche. ask them to create content about your product, ideally from a fresh account. pay them a fixed fee ($15–$30 per video) plus performance incentives ($1k for 1 million views, etc). you can use @sideshift_app (best creators imo) and line up 20+ of these creators in 1 day 5/ when building in public, a video is 10x better than an image/text - spam use cases of ur product on X/Linkedin 6/ figure out where your customers actually spend time. which slack/discord groups are they in? what newsletters do they open? which podcasts and accounts do they follow? pay those people for shoutouts 7/ there's a fresh trend on x basically every week. jump on the relevant ones and fold your product in (like i’m doing right now). To find trends i just use Origami & search “Lead Gen/GTM posts that are viral on X” to find the best posts every week in my niche Then, I will reply to those, quote tweet them, and use the formats that work myself (that’s the secret to why my account has high engagement BTW - you can do this too) --------- if you are doing all this every single week and DO NOT GIVE UP (launching, posting demos, contacting new customers) I guarantee you will hit your customer goals. Then the game becomes retention. will be posting 2-3 more growth hacks every single week

My spec-driven setup: Scenarios → initial requirements Roadmap → system requirements Architecture + Prototype → implementation Each item gets a global ID like PRN-001, SCN-001, or MVP-001, so decisions can be referenced across docs, issues, PRs, and code.

Trying spec-driven development for a large TypeScript project. Today I sketched this 7-layer spec structure to make specs the operating system for product, architecture, and implementation decisions. Curious how others structure specs. Would love to discuss.

Agent Observability has 4 layers: ①Token-level: CPU/GPU compute & comm. cost per decoded token ②Request-level: network + model latency per API call ③Task-level: LLM / sandbox / tool-call latency per task ④Evolution-level: memory update and dreaming latency across tasks

Code as Agent Harness: arxiv.org/abs/2605.18747

We should pay more attention to the DevAI benchmark, from a paper co-authored by Jürgen Schmidhuber, the father of LSTM. They were already exploring self-evolving agents back in 2024. huggingface.co/DEVAI-benchmark

Data Interpreter (Data): aclanthology.org/2025.findings-… MLE-Bench (Training): arxiv.org/abs/2410.07095 Agent-as-a-Judge (Evaluation): arxiv.org/abs/2410.10934

Today, we don't just need benchmarks for building software. We need benchmarks for building AI itself. Only then can AI move into the next paradigm: self-evolution. From data curation, to training, to evaluation (yes, benchmark for auto-eval), there is still a long way to go.