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Article URL: https://gaia-fork-oz2l3yz60-gaia-2.vercel.app/blog/how-tool-calling-works

Comments URL: https://news.ycombinator.com/item?id=47133402

Points: 3

# Comments: 0

Article URL: https://cambridge-chem-lab.onrender.com/

Comments URL: https://news.ycombinator.com/item?id=47133395

Points: 2

# Comments: 1

I’ve noticed that mainstream design tools are getting incredibly powerful, but also super overwhelming. If you just want to make a quick poster, certificate, or social media graphic, you end up navigating through hundreds of menus, complex features, and premium upsells.

I just wanted something where I could: Pick a template -> Edit the text/images -> Download -> Done.

Since I couldn't find a minimalist tool that did just that, I built it. It’s called EPIC.

Here’s what it does: * *Ready-made templates:* Focused on the basics (flyers, certificates, presentations). * *Zero learning curve:* A completely stripped-down manual editor (with an optional AI mode if you want it). * *No friction:* It runs entirely in your browser. Get in, make your design, and get out.

I originally built this with students in mind, but I think anyone who gets frustrated by heavy design software might find it useful.

I’m currently getting a trickle of organic traffic, but before I try to scale this, I need to know if the core product is actually good. I’d genuinely appreciate your brutal, honest feedback on: 1. The UX/usability (Is it actually as simple as I think it is?) 2. The quality of the current templates. 3. What features are strictly missing for your basic workflows.

You can try it out here:

https://no-edit.lovable.app

Thanks in advance for the feedback!

Comments URL: https://news.ycombinator.com/item?id=47133387

Points: 2

# Comments: 0

I see lots of postings (not here but in the 'interwebs') about how to downsize (housing).

However, seems like all the 'info' is from the real-estate industry.

Looking for comment on the proposition:

'downsizing' works if and only if you are taking money off the table.

Comments URL: https://news.ycombinator.com/item?id=47133380

Points: 1

# Comments: 0

Article URL: https://github.com/zanderone1980/artificial-persistent-intelligence

Comments URL: https://news.ycombinator.com/item?id=47133376

Points: 2

# Comments: 1

Article URL: https://philippdubach.com/posts/the-absolute-insider-mess-of-prediction-markets/

Comments URL: https://news.ycombinator.com/item?id=47133363

Points: 1

# Comments: 0

Article URL: https://longnow.org/ideas/pace-layers/

Comments URL: https://news.ycombinator.com/item?id=47133349

Points: 1

# Comments: 0

Article URL: https://www.ft.com/content/ecead6b9-eb42-4a85-bd33-073c659e84bf

Comments URL: https://news.ycombinator.com/item?id=47133343

Points: 1

# Comments: 0

Article URL: https://predictabledialogs.com/learn/openclaw/future-of-software

Comments URL: https://news.ycombinator.com/item?id=47133184

Points: 1

# Comments: 1

Article URL: https://www.trendforce.com/news/2026/02/23/news-psmc-joins-intel-softbanks-zam-initiative-to-manufacture-ai-memory-eyeing-an-alternative-to-hbm/

Comments URL: https://news.ycombinator.com/item?id=47133183

Points: 1

# Comments: 0

Ran a hands-on workshop in Tokyo where ~50 engineers built a CLI coding agent from scratch in Python and now, I've converted it into a self-paced exercise.

GitHub Repo: https://github.com/primaprashant/alduin

This should help in getting a better understanding of what goes on inside the coding agents. You will iteratively implement the core agent loop present in all coding agents like Claude Code and Codex starting from a skeleton repo with a basic input loop and no LLM. Over 7 phases, you will add the Anthropic API and implement tools (read file, edit file, bash). Each phase has hints and a reference implementation if you get stuck.

Should take ~3-5 hours and in the end, you'll have your own coding agent which you can use on other project and codebases as well.

Feedback and PRs welcome. Happy to answer any questions.

Comments URL: https://news.ycombinator.com/item?id=47133182

Points: 1

# Comments: 0

Article URL: https://blog.rust-lang.org/2026/02/23/rust-debugging-survey-2026/

Comments URL: https://news.ycombinator.com/item?id=47133164

Points: 2

# Comments: 0

Article URL: https://arxiv.org/abs/2602.20082

Comments URL: https://news.ycombinator.com/item?id=47133157

Points: 1

# Comments: 0

Article URL: https://www.iranintl.com/en/202602234502

Comments URL: https://news.ycombinator.com/item?id=47133155

Points: 2

# Comments: 0

Article URL: https://www.phinite.ai/

Comments URL: https://news.ycombinator.com/item?id=47133140

Points: 2

# Comments: 3

Article URL: https://en.wikipedia.org/wiki/Cassandra_(metaphor)

Comments URL: https://news.ycombinator.com/item?id=47133135

Points: 2

# Comments: 0

Article URL: https://www.wired.com/story/how-to-organize-safely-in-the-age-of-surveillance/

Comments URL: https://news.ycombinator.com/item?id=47133126

Points: 1

# Comments: 0

COLT converts natural language instructions into browser automation. You say "Create a user with email admin@test.com and admin role" — it executes it on a live browser and exports a standalone Playwright script. How it works:

1.Discover — crawls your web app autonomously, maps every page, form, modal, and element 2.Index — LLM-summarizes each state into a vector search index (discover once, run unlimited tasks) 3.Execute — ReAct agent loop drives the browser in real time with self-healing on failures 4.Record — exports reusable Playwright scripts, pytest tests, and typed Python functions

It handles Shadow DOM, cross-origin iframes, infinite scroll, pagination traps, and modals — the stuff that breaks most automation tools. What it's not: Not a consumer AI browser. Not an RPA tool. It's for engineering teams who want to generate E2E tests or automate internal tool workflows without writing selectors by hand. The key difference from other AI browser agents: they start from scratch every execution. COLT builds a persistent knowledge base of your app, so task #100 is as fast as task #1. Built with Python, Playwright, and ChromaDB. Works with Groq, OpenAI, Anthropic, or local Ollama models. Currently in closed beta — launching soon. Would love feedback on the approach, especially from anyone doing browser automation at scale

Comments URL: https://news.ycombinator.com/item?id=47133121

Points: 1

# Comments: 0

Article URL: https://www.theregister.com/2026/02/24/anthropic_misanthropic_chinese_ai_labs/

Comments URL: https://news.ycombinator.com/item?id=47133103

Points: 1

# Comments: 1

Hey HN. I built memctl because every AI coding agent starts each session with zero context. No memory of past decisions, no shared knowledge across your team. memctl is a memory server that gives AI coding agents persistent context that carries over across sessions. Memory is shared across your team so every agent works with the same knowledge. It's branch-aware so context follows your git workflow, and everything is tracked with full history. It works with any AI coding agent. Open source and self-hostable.

GitHub: https://github.com/memctl Website: https://memctl.com

Launches on March 1st. Waitlist open. Would to hear any feedback!

Comments URL: https://news.ycombinator.com/item?id=47133074

Points: 1

# Comments: 0