we're opening up more roles, hiring remote or in person in London 🇬🇧, building some very cool open source stuff and working on hard/medium/easy problems (we have them all). DM me and please share 🙏

We spent the last 6 months building our take on a chat agent SDK. It’s open source and uses the stateful compute that powers our existing tasks and workflows.

Applications for the latest Standard Capital Series A funding cycle are now open! Apply by July 21, hear back by July 31.

On 22-23 June our us-east-1 and eu-central-1 regions had periods of downtime and the overall incident lasted 18 hours. This falls way short of the reliability we aim for. I’m really sorry to all our customers, who will be receiving credits for that period and more. What happened, why it took so long to recover, and what we’re changing (starting from yesterday): trigger.dev/blog/incident-re…

Verbal ticks that give away Claude code: - Blast radius - Phase 1/2/x - Smoking gun - Let me actually check - Honestly, no - Honest answer

Trigger.dev lets developers add AI agents to their products with a simple SDK, handling execution, long-running workflows, and reliability so they don't have to. Over 90% of their usage now comes from agent workflows, and they recently announced their $16M Series A led by Standard Capital. In this episode of Founder Firesides, co-founders @mattaitken and @maverickdotdev sat down with YC's @koomen to talk about three versions of the product before finding product market fit, how building async infrastructure for two years accidentally put them in the perfect position for the agent era, and why they think the future of computing is programmatic checkpoint and restore — freezing and resuming compute on demand.

Bolto is a single platform that provides AI-native recruiting, HR and payroll in the same product, from YC S23. I just posted an interview with @mrinalsingh02 and @jakeatbolto, the founders of @boltohq, about their recent $ 12M Series A from @Standard_Cap. Link below

. @mattaitken from @triggerdotdev talking durable agents - @aiDotEngineer Europe

📝Detailed write up of how we ditched git worktrees in favor of @gitbutler and how we use it with agents here: trigger.dev/blog/parallel-ag…

We've decided to get into the 👟 business

We led the Series A for Insight Health. Insight Health builds AI agents for specialty care. The founders include a YC alum, the former head of cloud infrastructure at Twilio, and two practicing physicians. Welcome to @Standard_Cap, Insight Health!

Been running AI automation on GitHub PRs - generating them, reviewing them. Was doing it in GitHub Actions. Debugging GitHub Actions is a slog. Rerunning a failed job is a hassle. Observability beyond pass and fail requires parsing logs. Switched to @triggerdotdev. Night and day. Easier to set up, integrate locally, rerun, and actually see what's happening. The DX is much better.

Switching from Node to @bunjavascript gave us a 5x speed boost (28x better max latency) but there was a gotcha… Pending response promises don't resolve on client disconnect. @nodejs handles this automatically. Fix: resolve disconnects with 499. trigger.dev/blog/firebun

Just launched: our Vercel integration for Trigger. Push code. @vercel deploys your app. @triggerdotdev deploys your tasks. Env vars sync both ways. Your app never goes live with mismatched task versions. ↓

Do you think Claude gives us ratings on how well we are doing this session?

SF is for coding agents, London is for enterprise agents

Query and Dashboards are now live. You have full SQL-powered observability over your Trigger data. You can ask: "Why did failures spike after my last deploy?" "What's the p95 duration for my chat task?" "What are my most expensive runs?" ↓

I built a @techmeme killer on crack, with ai / @firecrawl / @iframely / @vercel / @supabase / @triggerdotdev. It's wild, messy, and fun. I'm not going to launch it, but if you want to see it and understanding my building process, check it out here: piped.video/watch?v=QPAy9R9V…

Spent the last 48 hours tracking down a massive memory leak in one of our production services. Node.js processes using up to 12-14GB within 5 hours. Went down 6 or 7 rabbit holes trying to recreate the leak locally, disabling various instrumentation, metrics, logging, prepared the service to be safely heapsnapshotted. Of course we created a script to slowly recycle the service every 4 hours before they would crash to buy us some time. Finally decided to look again at our logs and thats when I spotted the dreaded "Failed to convert rust `String` into napi `string`" error coming from a Prisma query. It turned out to be a two stuck processes polling the service every 5 seconds, performing a query that returned too much data to be serialized between the rust and the js layer in Prisma, starting about 2 weeks ago. The first arrow below is when we killed the stuck processes, as you can see memory flatlining. Then a few hours later we re-deployed the service with new tasks and now they are flat and using about 1GB of memory each at max. Few things in life come close to the satisfaction of finally finding and fixing this stupid memory leak

We've just shipped 5 Trigger Skills. Install them and your AI coding assistant will automatically gain in-depth @triggerdotdev knowledge. ✦ 𝚝𝚛𝚒𝚐𝚐𝚎𝚛-𝚜𝚎𝚝𝚞𝚙 ✦ 𝚝𝚛𝚒𝚐𝚐𝚎𝚛-𝚊𝚐𝚎𝚗𝚝𝚜 ✦ 𝚝𝚛𝚒𝚐𝚐𝚎𝚛-𝚝𝚊𝚜𝚔𝚜 ✦ 𝚝𝚛𝚒𝚐𝚐𝚎𝚛-𝚛𝚎𝚊𝚕𝚝𝚒𝚖𝚎 ✦ 𝚝𝚛𝚒𝚐𝚐𝚎𝚛-𝚌𝚘𝚗𝚏𝚒𝚐 🧵 But what are skills?