emilbob

@yashmp2004 Rust

Which backend language wins long-term?

@thepanta82 Exactly

What was once available only to enterprise team leads, now is available to every app maker with a claude account.

One of the most important jobs of a modern software engineering lead is to say NO to needless security hardening. Even more important now, that LLM reviewers are constantly whispering in your ear that you're gonna get pwned.

@tol_is @grok cool

Lychnos. You carry a lamp, the moths follow. Logarithmic spirals into the flame. tol.is/lychnos Made with @grok

@coryalthoff No, wait for UBI.

If you had a 15-year-old right now. would you tell them to prepare for a job or build a product?

@KirkDBorne x.com/emilbob_/statu…

[Download 585-page PDF eBook] Game Theory: arxiv.org/abs/1512.06808 ————— #GameTheory #Gamification #Mathematics #Statistics #Probability

@CodeEdison Rust

Which language would you learn if you started over today?

@alohaproxy Zig

developer challenge: name a programming language without using the letter ‘a’ or ‘c’ or ‘p’

@SaraDiscovers WSL

Finally bought a brand new Windows laptop What should I uninstall first?

@Taniyatweets_ Rust

Which backend language will still dominate in 2030?

@Surendar__05 Already did.

Be honest: As a developer, based on your current skills, can AI replace your job or not?

@jiya_3063 Rust

Which language do you think will grow the fastest

@dev_gen88926 Boo.

I'm a vibe coder, scare me with one word.

@CodeWithAmann Rust powers OpenAi.

C++ powers Google. C++ powers Microsoft. C++ powers Apple. C++ powers Meta. C++ powers Amazon. C++ powers NVIDIA. C++ powers Intel. C++ powers Adobe. C++ powers Netflix. C++ powers Cloudflare. C++ powers Spotify. C++ powers Uber. Still wondering if C++ is worth learning?

@Saanvi_dhillon Rust

Google uses Go. Microsoft uses Go. Uber uses Go. Cloudflare uses Go. Meta uses Go. Shopify uses Go. Amazon uses Go. Docker uses Go. PayPal uses Go. Dropbox uses Go. Kubernetes uses Go. Twitch uses Go. What's stopping you from learning Go?

@shannholmberg Like a sharded blockchain.

what's the difference between a loop and a graph? (marketing edition) both are ways to run an agent, the difference is who decides the path, the agent or you. a loop still starts with you. you set the goal, the brief, and the bar it has to clear. what the agent owns is the path. take writing an SEO article: hand it the brief and it drafts, reads the draft back against that brief, rewrites the weak parts, checks again, and keeps circling until it clears the bar. the one thing you did not write is the step-by-step it took to get there. a graph is you drawing the steps and the routes between them ahead of time. same article, but now you set the map: research the keyword and the competitors ranking for it. draft from what you find. score that draft against your rubric. if it clears, add the internal links and publish. if it misses, back to the draft. the agent still decides how to handle each step, it just travels the routes you laid down. the shape of this has a name, a state machine. every node is a state the work can be in, and a check at each one decides where it goes next, forward when it clears or back to an earlier node when it misses. if you have built a workflow in n8n, you have already drawn one. nodes wired together, branches that fire on a condition, a step that loops until it clears, that picture is a graph. an agent graph is the same shape, the nodes hold agents doing the work instead of single api calls. the way I think about it, a graph is a map of loops and checkpoints. some nodes run once, others are their own loop where the agent works something out, and the checkpoints between them read the result and route the work. you keep laying down nodes and checkpoints until the map reliably gives you the output you want. the vault accelerator I run at my agency is one of these maps, 3 sessions that hand off in a fixed order: > research session: reads our company brain and past campaign results, pulls in competitor and market context, and builds the cohort we go after > landing page session: takes that research and builds the page from it > content session: uses the research and the page to write the copy, illustrations, and slides for the live sessions we run inside the content session runs a loop, a critic scores each draft against a rubric and sends it back until it clears the bar. that is one node on the map, the checkpoints between the sessions carry the work from one to the next a graph earns its extra setup on anything you run every week: > validation gates the work cannot skip > a fixed set of routes the job can take > a clear failure point, you see the exact step something broke on a loop on its own is enough for the work you only do once, where you don't know the path yet, let the agent find it. graphs earn their place on the jobs you repeat, the content pipeline, the SEO and AEO funnel step by step, the vault accelerator once the map works you reuse it, feed it the next cohort and the whole pipeline runs again past the loop, the next thing you design is the map it runs inside.

@dexhorthy Intuitively, already did it.

Absolute banger

@omarsar0 Cool.

Sharing my new skill! It keeps track of high-signal X accounts for top AI news, papers, projects, etc. Total gamechanger for me. Built with X MCP tools. Give your agent the skill and tell it to generate the artifact with top stories. Works for Codex, Claude, Hermes, OpenClaw, or whatever you use. 3 steps: 1. Set up X MCP - X API: #x-mcp-%E2%80%94-x-api" target="_blank" rel="nofollow noopener">docs.x.com/tools/mcp#x-mc… 2. Install skill here: github.com/dair-ai/dair-a… 3. Run prompt: "Use the x-agent-intelligence skill to build a self-contained local feed from my X MCP connection; ask for my source handles if needed, save feed.html, and validate it." It should generate a nice, beautiful HTML artifact like the one shown in the clip. You can tune it however you want. You can then set a schedule/automation to do this daily or whatever cadence you prefer. I have it every 4 hours. You will need to curate the X accounts yourself, but I have shared a few good ones under the assets. You can ask your agent to tune it to however you like. I have also shared my personal feed with our community here: academy.dair.ai/dashboard/reso… I understand if it gets tricky to set up. Please reach out to me in the community forum. I plan to do a little tutorial or live session soon to help others reproduce the process. You can also store the feed as a wiki, as I have in my own implementation, but that's optional. If you encounter any issues or have ideas on how to improve it, please open a PR.

@zarazhangrui Exactly, you can set up your own system that suits your needs and workflow just by discussing it with AI, and without reading someone else's tutorials and the way they did it.

Everyone should develop their "personal eval set" for AI models: a few tasks that are actually relevant to your day-to-day work/life The industry benchmarks help but they might not reflect what will make it actually useful to you You find the model's capability boundary by poking at it & bumping into it for fun

Built almost exactly this yesterday without having read this yet — agents propose, mechanical checks resist, my merge is the only approval, Obsidian/git as the memory layer underneath. x.com/emilbob_/statu… Then I read this, and it caught the one thing I hadn't built: nothing governed the setpoints. Added a monthly calibration loop the same evening. The essay works as a diagnostic, not just a description.

Cheatsheet for ... x.com/IntuitMachine/…

6/ The whole thing cost one Saturday. Now my job is: read the email, merge what's good, close what isn't. An empty action queue means I'm free.

5/ Day-one results: a repo that sat empty since March became solrail — Solana payment rails — with a core SDK and a React checkout built, tested and merged the same day. My abandoned experiments are getting revival roadmaps as PRs this week.

1/ Spent one day wiring Claude Code, GitHub Actions and Obsidian into a system that develops my projects while I mostly just read email and merge PRs. At the bottom of it all: an Obsidian vault as the memory layer everything reads and writes.