So awesome to see "𝚞𝚜𝚎 𝚠𝚘𝚛𝚔𝚏𝚕𝚘𝚠" in more production apps and agents by the day

Before / after “𝚞𝚜𝚎 𝚠𝚘𝚛𝚔𝚏𝚕𝚘𝚠”: > before: > - scheduling service > - queues > - workers > - cron jobs > now: > - 5 functions in one file Another customer told us they were able to delete 4000 lines of code.

kinda fun to just get an llm to guide you through some random deep part of some stack I spent the last hour implementing my own version of TCP from the ground up. Next up: building my own HTTP protocol on top of it.

The bug that took down 1/3 of the internet

“do things that don’t scale” used to mean “don’t start by writing software”, and that was good advice when software was hard to write - much easier to validate ideas manually, and then automate yourself away as human effort in writing software trends to zero, writing heaps of

two ways to build products: the first buyer is the user: you sell utility, build compelling UX - craft something beautiful and functional the first buyer is not the user: sell the value to the organisation, the end user must typically suffer the product, not enjoy it

opus 4.5 can one-shot beautiful, tasteful UI

day 1 learning to build voice agent infra from scratch: put together a VAD, twilio , Deepgram (SST), o4-mini, ElevenLabs (TTS) into an event-based loop that coordinates listening and speaking main issue right now is latency and quality of turn-taking/interruptions.

the trick to making voice agents fast is pipelining everything first pipeline: audio packets -> speech to text -> turn-taking model second: LLM -> text to speech -> encoding -> output here's a render of my current latency. bear in mind, I'm running this locally from a

this architecture gets you to a nearly SOTA voice agent (a la Vapi/ElevenLabs), but with much more control over the orchestration. Deepgram's Flux handles STT and turn taking + a pipeline for LLM and TTS managed based on Flux events

Mandarin learning progress update: I am 14% to B1 (conversational) - about 1 year away at the current pace. - I advance around 1.5% every week. - last month, I learned 97 core words (out of the 2k most common) - ~200 total phrases/sentences learned last month 2x tutor sessions

just beat Vapi E2E latency with my own voice agent orchestrator. had to host everything just right to get the numbers this low Vapi's reported: ~840ms mine: ~690ms + 100ms (twilio) = ~790ms that 50ms is a big deal in voice! write-up incoming

100% agree with this. I've gone far with: - cursor - claude 4.5 -> now 4.6 - no subagents - one prompts at a time - zero MCPs, zero skills, all rules in README

My voice agent's e2e latency is now down to ~300ms, all thanks to Groq Inc insanely low TTFT endpoints (~100ms?!). This is 2-3x better than what you get off-the-shelf with the major providers.

$350 in Opus 4.6 spend yesterday but I got ~2 SWE-weeks of work done in just a few hours

I’m speed-learning Chinese with AI goal: fluent by 2027 I built my own learning harness over the last month: - smart tracking of all vocab - feeds me high frequency words - spaced repetition modelling my memory - AI generated images + pronunciation I’m learning ~80 new