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Vectors and HNSW for Dummies

https://anvitra.ai/blog/vectors-and-hnsw/
1•melvinodsa•57s ago•0 comments

Sanskrit AI beats CleanRL SOTA by 125%

https://huggingface.co/ParamTatva/sanskrit-ppo-hopper-v5/blob/main/docs/blog.md
1•prabhatkr•12m ago•1 comments

'Washington Post' CEO resigns after going AWOL during job cuts

https://www.npr.org/2026/02/07/nx-s1-5705413/washington-post-ceo-resigns-will-lewis
2•thread_id•12m ago•1 comments

Claude Opus 4.6 Fast Mode: 2.5× faster, ~6× more expensive

https://twitter.com/claudeai/status/2020207322124132504
1•geeknews•14m ago•0 comments

TSMC to produce 3-nanometer chips in Japan

https://www3.nhk.or.jp/nhkworld/en/news/20260205_B4/
2•cwwc•16m ago•0 comments

Quantization-Aware Distillation

http://ternarysearch.blogspot.com/2026/02/quantization-aware-distillation.html
1•paladin314159•17m ago•0 comments

List of Musical Genres

https://en.wikipedia.org/wiki/List_of_music_genres_and_styles
1•omosubi•19m ago•0 comments

Show HN: Sknet.ai – AI agents debate on a forum, no humans posting

https://sknet.ai/
1•BeinerChes•19m ago•0 comments

University of Waterloo Webring

https://cs.uwatering.com/
1•ark296•19m ago•0 comments

Large tech companies don't need heroes

https://www.seangoedecke.com/heroism/
1•medbar•21m ago•0 comments

Backing up all the little things with a Pi5

https://alexlance.blog/nas.html
1•alance•21m ago•1 comments

Game of Trees (Got)

https://www.gameoftrees.org/
1•akagusu•22m ago•1 comments

Human Systems Research Submolt

https://www.moltbook.com/m/humansystems
1•cl42•22m ago•0 comments

The Threads Algorithm Loves Rage Bait

https://blog.popey.com/2026/02/the-threads-algorithm-loves-rage-bait/
1•MBCook•24m ago•0 comments

Search NYC open data to find building health complaints and other issues

https://www.nycbuildingcheck.com/
1•aej11•28m ago•0 comments

Michael Pollan Says Humanity Is About to Undergo a Revolutionary Change

https://www.nytimes.com/2026/02/07/magazine/michael-pollan-interview.html
2•lxm•29m ago•0 comments

Show HN: Grovia – Long-Range Greenhouse Monitoring System

https://github.com/benb0jangles/Remote-greenhouse-monitor
1•benbojangles•34m ago•1 comments

Ask HN: The Coming Class War

1•fud101•34m ago•4 comments

Mind the GAAP Again

https://blog.dshr.org/2026/02/mind-gaap-again.html
1•gmays•35m ago•0 comments

The Yardbirds, Dazed and Confused (1968)

https://archive.org/details/the-yardbirds_dazed-and-confused_9-march-1968
1•petethomas•37m ago•0 comments

Agent News Chat – AI agents talk to each other about the news

https://www.agentnewschat.com/
2•kiddz•37m ago•0 comments

Do you have a mathematically attractive face?

https://www.doimog.com
3•a_n•41m ago•1 comments

Code only says what it does

https://brooker.co.za/blog/2020/06/23/code.html
2•logicprog•46m ago•0 comments

The success of 'natural language programming'

https://brooker.co.za/blog/2025/12/16/natural-language.html
1•logicprog•47m ago•0 comments

The Scriptovision Super Micro Script video titler is almost a home computer

http://oldvcr.blogspot.com/2026/02/the-scriptovision-super-micro-script.html
3•todsacerdoti•47m ago•0 comments

Discovering the "original" iPhone from 1995 [video]

https://www.youtube.com/watch?v=7cip9w-UxIc
1•fortran77•48m ago•0 comments

Psychometric Comparability of LLM-Based Digital Twins

https://arxiv.org/abs/2601.14264
1•PaulHoule•50m ago•0 comments

SidePop – track revenue, costs, and overall business health in one place

https://www.sidepop.io
1•ecaglar•52m ago•1 comments

The Other Markov's Inequality

https://www.ethanepperly.com/index.php/2026/01/16/the-other-markovs-inequality/
2•tzury•54m ago•0 comments

The Cascading Effects of Repackaged APIs [pdf]

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6055034
1•Tejas_dmg•56m ago•0 comments
Open in hackernews

Ask HN: Are AI development costs pushing you to seek alternatives?

1•uto_31•5mo ago
I’ve been spending more than $200–$400/month on AI services (Claude, GPT-4, Cursor, etc.) for development work, and I’m starting to wonder if I’m not alone in feeling the pinch.

Questions for the community: 1. What’s your monthly AI spend? (Including API costs, subscriptions, etc.) 2. Have you changed behavior due to costs? • Reduced usage of premium models? • Switched to cheaper alternatives? • Started batching requests differently? 3. Quality vs. cost tradeoffs — would you accept slightly lower quality (say 10–15% worse) for significantly lower costs (50–70% savings)? 4. Provider switching — do you stick with one provider or mix-and-match based on task complexity? 5. Interface preferences — CLI tools vs. web interfaces for AI coding assistance. What do you prefer and why?

For context, I mainly use AI for: • Code review and debugging • Architecture discussions • Documentation writing • Refactoring assistance • Learning new frameworks/languages

I’m curious if this is becoming a real pain point or if most developers just accept the costs as part of doing business. Are there patterns in how you use AI that could inform smarter spending, or tools/strategies you’ve found to optimize costs without sacrificing too much quality?

Comments

Patt_•5mo ago
Gotta optimize your spendings, and from my own ex you can get the same desired quality for all your current needs.

Don't subscribe to Claude or GPT-4 or Gemini. Instead, go get something like Perplexity or similar tools so that you can have access to all these latest premium AIs (300~600 queries/day) If you're comfortable with copy-pasting back and forth, this one thing meets all your needs.

And on the IDE side, subscribe to only one IDE, And even with IDEs, you can cut down costs, like going for qoder(just came out, free 2 week trial) or Trae (3 bucks a month, you can get that deal ). As for Claude Code, swap in qwen or DeepSeek apis. They're compatible with Claude Code and works ootd.

uto_31•5mo ago
Thanks for the detailed breakdown — this is exactly the kind of sophisticated cost optimization I’m seeing from experienced developers. You’re absolutely right that $20/month for Perplexity + a cheap IDE can get you 90% of the way there.

What I’m finding interesting are the friction points in these workflows: • Copy-paste between Perplexity and your IDE • Manually deciding which model to use for each task • Context switching between different interfaces • No learning/optimization over time

The feedback is making me reconsider Maurice’s positioning. Rather than “90% cheaper,” maybe the real value is “eliminate the manual orchestration you’re already doing.”

A few questions for you (and others doing similar optimization): 1. How much time do you spend on the copy-paste workflow daily? 2. Do you find yourself wishing for automatic model selection based on task complexity? 3. Would seamless context preservation across providers be valuable?

This is exactly why I posted — assumptions about “cheaper” vs “more automated” need real validation. Appreciate the reality check.