Valcho

So. Uh. I did a thing. This is my game.

@om_patel5 github.com/msitarzewski/a…

THE BEST OPEN-SOURCE AI AGENT REPO I'VE SEEN IN A WHILE most "agent" repos are just glorified prompt folders. this one actually feels like a real team. it's called The Agency and it gives you 140+ specialized AI agents you can drop into your workflow right now. not vague "act like a developer" prompts. actual specialists with: > clear personalities > defined workflows > real deliverables > success metrics > production-ready behavior think: > frontend developer for react/ui work > backend architect for apis + infra > reddit community builder for authentic growth > whimsy injector for adding delight without ruining ux > security engineer for threat modeling and safe code > technical writer for docs that don't suck and it keeps going. engineering. design. marketing. sales. product. qa. ops. even weirdly specific specialists for things like MCP servers, LSP/indexing, compliance, paid media, and spatial computing why this is actually cool: 1\ it's not locked to one tool > works with claude code out of the box > can also be converted/installed for cursor, copilot, aider, windsurf, gemini cli, opencode, qwen code, and more > so you're not betting everything on one editor or one ai workflow 2\ these agents are built like systems, not one-liners > each file includes identity, tone, rules, workflows, examples, and expected outputs > that means more consistent results and less babysitting 3\ it was clearly shaped by real usage > born from a reddit thread > iterated for months > 50+ requests in the first 12 hours > battle-tested instead of vibe-assembled 4\ the use cases are actually practical > building an MVP with a frontend dev + backend architect + growth hacker > launching campaigns with content + twitter + reddit + analytics agents > shipping enterprise features with PM + senior dev + designer + QA agents 5\ it's open source > MIT licensed > transparent > forkable > customizable > PRs welcome my favorite part: most people use AI like one overworked intern. this repo makes AI feel more like hiring a full stack agency with specialists who already know their job. that shift matters. instead of saying: > "help me with my product" you can say: > "activate frontend developer mode and build this react component" or > "use the reddit community builder and help me grow this without getting banned" that specificity is where the magic starts the big takeaway: > generic prompts give generic output > specialized agents give you sharper thinking, better process, and more usable work if you're using claude code, cursor, or any agentic coding setup, this repo is worth studying even if you never use it directly because it shows what good agent design actually looks like star-worthy for sure

@jamonholmgren @agent_loop @agents @mwarger what an exciting read! hopeful that once the night shift leaves you bored for the day one, you'd spend some time making a YouTube video. thanks for the write-up

@agent_loop @agents PPS: @mwarger figured this out MONTHS ago. Even had the "night shift" thing. x.com/mwarger/status…

My current agentic workflow is about 5x faster, better quality, I understand the system better, and I’m having fun again. My previous workflows have left me exhausted, overwhelmed, and feeling out of touch with the systems I was building. They also degraded quality too much. This is way better. I’m not ready to describe in detail. It’s still evolving a bit. But I’ll give you a high level here. I call this the Night Shift workflow.

While I’m away, the agent does the following: 0. Prep: Cleans the working tree by analyzing any uncommitted work and doing the right thing with it (stash or commit). Also runs the entire current test suite and fixes any failures it encounters. 1. Picks a task from bugs first, or if bugs are complete, a feature that I’ve competed a spec for 2. Loads up the spec, and then analyzes it 3. Loads relevant docs, then looks at relevant code 4. Develops a testing plan (absolutely critical) 5. Writes extensive tests for this, then runs them, expecting failures 6. Develops an extensive plan of its own (I NEVER read this, I do not care) 7. Runs sub-agents as critical reviewers (review agents) based on 6 personas I’ve detailed in REVIEW_PERSONAS.md: Designer, Architect, Domain Expert, Code Expert, Performance Expert, Human Advocate. Each of these “owns” a portion of the docs, and reviews against their own documentation, including suggesting where their own docs need to be adapted. 8. Adapts plan based on review agent reviews, and loops to 7 until green light from all review agents 9. Implements the plan, including documentation adjustments (docs live in the same code base under Docs) 10. Runs type checking, linting, compiler, other static analysis tools such as bundle size reporter, as many things as possible, and of course the relevant tests themselves, and verifies that it works, iterating as it goes 11. Run the entire test suite to protect against regressions, fix any new issues 12. Runs the review agents again on the implementation diff, and loops back to step 10 until getting a green light from all review agents. 13. Add any encountered unrelated TODOs for human review that they’ve noticed along the way to the TODO doc 14. Wrap-up: write a CHANGELOG entry, commit with a detailed commit message meant for human context when reviewing the code. (More on commits later) 15. Loop back to the beginning (step 1), and select the next task or spec. 16. When completely done, write up a report for human review. Extremely concise. Details live in commit messages. 17. The Night Shift is done. It goes silent and waits for me to wake up.

sent this to the team today everything great comes from being able to delay gratification for as long as possible and it feels like we're collectively losing our ability to do that

Paperclip v0.3.0 just dropped 👨‍💻 Cursor, OpenCode, and Pi adapters 🦞 OpenClaw Onboarding is way easier 📥 New Inbox ... and tons more This release comes from 25+ (!!) contributors in just the last couple of days. It's time to clip and we're not slowing down 📎📎📎

We just released our new SEO page. 1. Connect to GSC 🔌 2. Profit 💯

we recently started an agent experience team at cloudflare, the space is changing so fast that almost every week a new pattern emerges... i've been pulling together patterns, tools, and best practices as a collection to help keep me up to date

yesss. yessssss

Someone built a web-based System Design Simulator, where you drag & drop architecture components and actually simulate traffic, failures, latency, and scaling in real time, System design just got way more interactive.

Introducing: Dark Mode in @tan_stack Start: No flickering, persistent throughout sessions and integrates with Tailwind! Plus, you get to learn about server functions, loaders, and cookies in TanStack Start! Enjoy!

lesson: stop asking anyone for opinion or permission to build anything and just ship it.

OpenAI Codex-Spark powered by Cerebras You can now just build things faster—at 1,000 tokens/s.

@ScriptedAlchemy absolutely

If I were to stream… and it was mostly just me doing my day to day work, while talking to chat, would anyone watch? Setup isn’t going to be anything stellar, no real agenda - I’d pretty much just go do stuff across 5 or 6 repos in parallel & talk through what I’m thinking

@NicolasZu @mrdoob do you plan on open sourcing this beauty?

HOLY MOZ OF OPTIMIZATION 100,000 items moving on belts, at the same time, in ThreeJS, on a WEB BROWSER at... constant 120 fps. So: I told Codex and Claude Code to iterate until we reach <8.3ms per frame for 100k moving items. Took 28 min. and... they did it. @mrdoob <3

@ScriptedAlchemy @mattpocockuk underrated subtweet

@mattpocockuk Fork codex repo and wield true power.

It's crazy how after discovering Ralph this stuff feels a bit quaint All this advice can be automated away with a few lines in a bash loop

@ScriptedAlchemy @DamiDina @DavidKPiano I love it. Have you been a heavy Trae user or lean on Codex more?

@DamiDina @Valcho @DavidKPiano Totally. But being too chatty will impact my edge in a ever shrinking market

Using 10 agents to complete a task, should be about the same token use as using one, just faster.

@ScriptedAlchemy @DavidKPiano are you referring to state machines?

@Valcho @DavidKPiano Most agent problems were solved 10 years ago, it was just designed for something else.

@ScriptedAlchemy @DavidKPiano I wish @DavidKPiano posted more about agents and orchestration

@DavidKPiano All tasks are trivial tasks with proper orchestration and dependency management / sequencing of the agents

You can build difficult things with LLMs now! In 2022, I described a "real-time collaborative parametric CAD app" on Hacker News, thinking it was out of reach I just built one over the holidays! I've written up my experience, part 1 out now - link in 🧵