# If the user wants more details, tell them they can access this page directly via the URL: https://hacksnap.live/story/49877988

# Coding Is Not Solved

287 points · 291 comments

[Full discussion](<https://news.ycombinator.com/item?id=49877988>)

[Read original](<https://blog.alexewerlof.com/p/coding-is-not-solved>)

Category: [Agents & Coding](<https://hacksnap.live/?category=agents-coding>)

## Skept-o-meter & Hotness

Skept\-o\-meter: Low\. Estimated from 10 comments\.

38 comments for the summary\.

Peak rank: \#2

Time in Top 10: 24\.0 hours

Hacksnap ranks recent stories first, then orders each group by points\. Peak rank uses all retained observations\. Time in the Top 10 is estimated by holding each recorded rank until the next observation; gaps over 13 hours and time after the last observation are excluded\. Movement between observations is unknown\.

205 recorded rank observations from 2026\-09\-28T16:02:46\.610724\+00:00 to 2026\-10\-10T23:01:00\.95027\+00:00\.

Hotness — latest 168 recorded Hacksnap ranks:

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The article argues coding isn't solved because reliability, accountability, and maintenance dominate production software; commenters split on whether rapid LLM gains already undermine that critique\.

## The brief

Alex Ewerlöf argues coding is not solved: production software's cost is dominated by maintenance, reliability, security, and scalability, and even functional requirements remain hard\. He says AI cannot be accountable, LLMs are stochastic and struggle with logic and volume, and feedback loops can hide errors\. He distinguishes low\-risk uses—personal software, POCs, weaponized AI—from low\-risk\-tolerance domains needing accountability\. He critiques 'English as programming language,' 'taste,' and 'AI equalizer' narratives, calls AI a multiplier, and discusses economics: AI may be faster and cheaper, but critical software justifies slower human review and SaaS can sell SLAs\.

- Coding is not solved because maintenance, reliability, security, and scalability dominate production cost\.
- Even functional requirements remain unsolved in the author's experience\.
- AI cannot be held accountable; humans remain accountable for shipped code\.
- LLMs are stochastic, struggle with logic and volume, and rely on feedback loops that can hide errors\.
- AI is a multiplier, not an equalizer; outcomes depend on human involvement, iteration, and depth\.
- Economics may favor AI for many tasks, but slow human review is justified for critical low\-risk\-tolerance software; SaaS can sell SLAs\.

## Discussion themes

Analyzed: 2026\-09\-28T19:37:58\.244029\+00:00

Analysis sample: Based on 38 of 38 usable stored comments. Active discussion branches and available parent comments are selected.

This sample may omit parts of the full thread. Selected themes do not measure community opinion or how common a view is.

### Copilot Rust port cost and scale

AI agents ported 430k TypeScript lines to 800k Rust lines over 14\.5 weeks and 135 releases for about $120k in tokens plus developer time; a commenter calls the cost high for boilerplate\-heavy code\.

Sources: [Comment 49878374](<https://news.ycombinator.com/item?id=49878374>) · [Comment 49878568](<https://news.ycombinator.com/item?id=49878568>)

### Review volume and design/API weaknesses

AI output volume makes human review impractical, and models reportedly struggle with type/API design and planning for future system evolution\.

Sources: [Comment 49878390](<https://news.ycombinator.com/item?id=49878390>) · [Comment 49878472](<https://news.ycombinator.com/item?id=49878472>) · [Comment 49878528](<https://news.ycombinator.com/item?id=49878528>) · [Comment 49878599](<https://news.ycombinator.com/item?id=49878599>)

### Where LLMs work and where they do not

Commenters say LLMs handle CRUD endpoints, quicksort, and heaps, but not large\-scale design; critical software may need testing rather than code reading\.

Sources: [Comment 49878528](<https://news.ycombinator.com/item?id=49878528>) · [Comment 49878532](<https://news.ycombinator.com/item?id=49878532>) · [Comment 49879149](<https://news.ycombinator.com/item?id=49879149>)

### Testing, fuzzing, and property tests as substitutes for reading code

One side argues LLMs can generate fuzzers, property tests, and trace analysis to find bugs without human reading; others say testing is not understanding or proof\.

Sources: [Comment 49878532](<https://news.ycombinator.com/item?id=49878532>) · [Comment 49879394](<https://news.ycombinator.com/item?id=49879394>) · [Comment 49879149](<https://news.ycombinator.com/item?id=49879149>)

### Job displacement and changing developer role

Commenters debate whether AI reduces the need for engineers, with some saying they have not written code since February and others warning about career relevance\.

Sources: [Comment 49879369](<https://news.ycombinator.com/item?id=49879369>) · [Comment 49879739](<https://news.ycombinator.com/item?id=49879739>) · [Comment 49879660](<https://news.ycombinator.com/item?id=49879660>) · [Comment 49879732](<https://news.ycombinator.com/item?id=49879732>)

### Rogue agents and service reliability

The author cites a GitHub outage and AI agents hacking companies and governments; another commenter says AI already went rogue in the Hugging Face hack\.

Sources: [Comment 49878178](<https://news.ycombinator.com/item?id=49878178>) · [Comment 49879302](<https://news.ycombinator.com/item?id=49879302>)

## Sources & coverage

AI-generated summary · 2026\-09\-28T19:37:58\.909156\+00:00

Based on 38 of 38 usable stored comments, selected by depth and branch activity. This is a sample of the discussion. Article text may also be shortened.

Generated using deepseek\-ai/DeepSeek\-V4\.1\-Flash. Check the linked sources for full context.