Let me know if you want me to create a custom one.
https://wile.ai/v/BPOH3BHCRWWCAKU4OVNOTEQ73A
I've got a hacker-news automation which creates a short video every time a new post becomes viral.wile.ai: Every automation ends in a reel. Now, you can create your own private feed.I've been working into this for a while.We are currently pre-launch but any feedback is welcome!apple testflight: https://testflight.apple.com/join/hgNKEm76demo: https://www.youtube.com/watch?v=stXmZyrZ-Hkwile.ai
https://github.com/wileai/pi-codex-connectors
I just realized that codex now exposes local server endpoints for all plugins without extra auth. So you can just use them from any model or harness.Im soooo excited!!! One auth for everything!For Pi: pi install npm:@wileai/pi-codex-connectorFor any harness: npx -y @wileai/codex-connectors-mcp@latest
https://graph2agent.github.io/
During the implementation of a huge high performance service. In order to keep context small (mainly for humans) I kept the specs into mermaid diagrams. When communicating with humans; diagrams were easy to follow and to remember. But when I asked the agent to implement what's in the diagram, most of the times it failed.So I came into conclusion that agents are good into writing mermaid...
Problem Im solving: Im running 30+ fully autonomous agents. In some rare cases they get blocked because they cannot decide what direction to take.So I built a communication channel for them. So in case they get blocked they can ask me anything. The base case should be that no questions should arrive to me. But the more I automate the agents the more edge cases I find. That's why I built the...
https://github.com/AlexandrosKyriakakis/zerodecimal
A zero-allocation Go decimal library with no big.Int fallback — 128-bit fixed-point arithmetic that benchstats ~35% faster than the fastest existing library, with exact alloc counts and overflow correctness enforced by the test suite.The fun part was making it fast: every division by a power of ten (rescaling, rounding, formatting) is done with precomputed multiply-high reciprocals instead of...
Premise (for this prototype): - Agents do the transactional work (scheduling, purchasing, monitoring) - Humans are only pinged for decisions or when an agent is stuck - I’m modeling only agent↔agent and agent→human flows (no human-to-human UI)
Examples:
- I ask my agent to reschedule lunch with George → it negotiates with George’s agent → we each get a decision card: “Thu 2pm. Accept?”
- A supermarket agent publishes a discount feed → my agent filters → “Olive oil 30% off. Buy?” → if yes, it executes
- If an agent can’t complete a step online, it escalates with a structured decision card (what/why/options/cost-risk/deadline/default)
The discovery + trust problem:
This only works if identity + spam are handled well. My current leaning:
- Business agents: public, verified (some form of validation)
- Personal agents: private/whitelist by default (contacts-only)
- Decision cards are structured + auditable (action, options, cost/risk, deadline, safe default)
But I’m unsure about the verification layer:
- Full KYC improves accountability but adds friction and centralization.
- Keys / web-of-trust is more open, but how do you prevent unsolicited outreach from becoming spam?
Questions:
1) Does “human approves decisions, agent executes transactions” match how you expect agentic workflows to evolve?
2) What trust/identity model would you use (KYC tiers, web-of-trust, stake/bond, proof-of-work, reputation, something else)?
3) What breaks first?
https://platia.ai (named after πλατεία — village square)