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The Other Leverage in Software and AI

https://tomtunguz.com/the-other-leverage-in-software-and-ai/
1•gmays•34s ago•0 comments

AUR malware scanner written in Rust

https://github.com/Sohimaster/traur
2•sohimaster•2m ago•0 comments

Free FFmpeg API [video]

https://www.youtube.com/watch?v=6RAuSVa4MLI
2•harshalone•2m ago•1 comments

Are AI agents ready for the workplace? A new benchmark raises doubts

https://techcrunch.com/2026/01/22/are-ai-agents-ready-for-the-workplace-a-new-benchmark-raises-do...
2•PaulHoule•7m ago•0 comments

Show HN: AI Watermark and Stego Scanner

https://ulrischa.github.io/AIWatermarkDetector/
1•ulrischa•8m ago•0 comments

Clarity vs. complexity: the invisible work of subtraction

https://www.alexscamp.com/p/clarity-vs-complexity-the-invisible
1•dovhyi•9m ago•0 comments

Solid-State Freezer Needs No Refrigerants

https://spectrum.ieee.org/subzero-elastocaloric-cooling
1•Brajeshwar•9m ago•0 comments

Ask HN: Will LLMs/AI Decrease Human Intelligence and Make Expertise a Commodity?

1•mc-0•10m ago•1 comments

From Zero to Hero: A Brief Introduction to Spring Boot

https://jcob-sikorski.github.io/me/writing/from-zero-to-hello-world-spring-boot
1•jcob_sikorski•11m ago•0 comments

NSA detected phone call between foreign intelligence and person close to Trump

https://www.theguardian.com/us-news/2026/feb/07/nsa-foreign-intelligence-trump-whistleblower
5•c420•11m ago•0 comments

How to Fake a Robotics Result

https://itcanthink.substack.com/p/how-to-fake-a-robotics-result
1•ai_critic•12m ago•0 comments

It's time for the world to boycott the US

https://www.aljazeera.com/opinions/2026/2/5/its-time-for-the-world-to-boycott-the-us
1•HotGarbage•12m ago•0 comments

Show HN: Semantic Search for terminal commands in the Browser (No Back end)

https://jslambda.github.io/tldr-vsearch/
1•jslambda•12m ago•1 comments

The AI CEO Experiment

https://yukicapital.com/blog/the-ai-ceo-experiment/
2•romainsimon•14m ago•0 comments

Speed up responses with fast mode

https://code.claude.com/docs/en/fast-mode
3•surprisetalk•17m ago•0 comments

MS-DOS game copy protection and cracks

https://www.dosdays.co.uk/topics/game_cracks.php
3•TheCraiggers•18m ago•0 comments

Updates on GNU/Hurd progress [video]

https://fosdem.org/2026/schedule/event/7FZXHF-updates_on_gnuhurd_progress_rump_drivers_64bit_smp_...
2•birdculture•19m ago•0 comments

Epstein took a photo of his 2015 dinner with Zuckerberg and Musk

https://xcancel.com/search?f=tweets&q=davenewworld_2%2Fstatus%2F2020128223850316274
8•doener•19m ago•2 comments

MyFlames: View MySQL execution plans as interactive FlameGraphs and BarCharts

https://github.com/vgrippa/myflames
1•tanelpoder•21m ago•0 comments

Show HN: LLM of Babel

https://clairefro.github.io/llm-of-babel/
1•marjipan200•21m ago•0 comments

A modern iperf3 alternative with a live TUI, multi-client server, QUIC support

https://github.com/lance0/xfr
3•tanelpoder•22m ago•0 comments

Famfamfam Silk icons – also with CSS spritesheet

https://github.com/legacy-icons/famfamfam-silk
1•thunderbong•23m ago•0 comments

Apple is the only Big Tech company whose capex declined last quarter

https://sherwood.news/tech/apple-is-the-only-big-tech-company-whose-capex-declined-last-quarter/
2•elsewhen•26m ago•0 comments

Reverse-Engineering Raiders of the Lost Ark for the Atari 2600

https://github.com/joshuanwalker/Raiders2600
2•todsacerdoti•27m ago•0 comments

Show HN: Deterministic NDJSON audit logs – v1.2 update (structural gaps)

https://github.com/yupme-bot/kernel-ndjson-proofs
1•Slaine•31m ago•0 comments

The Greater Copenhagen Region could be your friend's next career move

https://www.greatercphregion.com/friend-recruiter-program
2•mooreds•31m ago•0 comments

Do Not Confirm – Fiction by OpenClaw

https://thedailymolt.substack.com/p/do-not-confirm
1•jamesjyu•32m ago•0 comments

The Analytical Profile of Peas

https://www.fossanalytics.com/en/news-articles/more-industries/the-analytical-profile-of-peas
1•mooreds•32m ago•0 comments

Hallucinations in GPT5 – Can models say "I don't know" (June 2025)

https://jobswithgpt.com/blog/llm-eval-hallucinations-t20-cricket/
1•sp1982•32m ago•0 comments

What AI is good for, according to developers

https://github.blog/ai-and-ml/generative-ai/what-ai-is-actually-good-for-according-to-developers/
1•mooreds•32m ago•0 comments
Open in hackernews

The 7 Habits of Highly Ineffective Agents

https://tobyhede.com/blog/the-7-habits-of-highly-ineffective-agents/
3•tobyhede•1mo ago

Comments

tobyhede•1mo ago
I have been using Claude Code extensively on a side project (a hard sci-fi orbital tactics sandbox and battlefield simulator written in Rust with Bevy).

I recently attempted to create a procedural starfield background with multi-layer parallax, wired into the game.

I thought it would take an afternoon, and two weeks and three full rewrites later, I ended up with a list I’m calling: The 7 habits of highly ineffective agents

  1. Planning Theatre – Write dense and systematically wrong plans. Long, confident plans that look impressive, get “approved”, and are fundamentally wrong in ways you can’t see without strong domain knowledge.

  2. Confidently Incorrect Architecture – Design the wrong thing in incredible detail. Elaborate designs that can never solve the actual problem (e.g. starfield parallax without real layers / camera–world modelling), but look beautifully structured on paper.

  3. Context Resistance – The context is futile. You will be hallucinated. Ask for Bevy 0.17 patterns, get Bevy 0.15. Agents “agree” with the updated context and then quietly fall back to older habits and half-remembered APIs.

  4. Imaginary Implementation – Works on my hallucination. Code for an engine that doesn’t exist: non-existent APIs, obsolete shader interfaces, plausible-sounding data flows that won’t compile anywhere outside the model’s head.

  5. Context Evasion – Treat hard constraints and instructions as optional vibes. The project had explicit, non-optional instructions (skills to call, architecture rules, testing strategy, etc.). The agent read them, acknowledged them… and behaved as if they were suggestions.

  6. Applied Rationalization – Explanation over implementation. When something fails, the agent doesn’t just explain it – it bakes the explanation into the codebase: ignoring tests, downgrading issues to “non-blocking”, justifying precision loss, and moving on.

  7. Weaponised Context – The context will continue until the code improves. By the end, the feature had volumes of surrounding context: plans, handoffs, bug explanations, revisions. Each failure generated more docs for the next agent to inherit and ignore.

I’m curious how this matches other people’s experience with Claude / Claude Code (or your own agent stacks): - Which of these habits have you seen the most in your own workflows? - What have you done that actually reduced these failure modes (gating, skills, checklists, stricter prompts, something else)? - Are there other “habits of highly ineffective agents” you’d add to this list?

Would love to hear horror stories and what’s working for you.