--- title: We should be more ambitious with the software we build description: AI coding tools now let individuals build ambitious software that previously would have taken a year or more, Dan Luu argues. He points to Michael Malis's... canonical: https://daily.dev/posts/we-should-be-more-ambitious-with-the-software-we-build-l2m1e5rw3 twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: We should be more ambitious with the software we build | daily.dev og:description: AI coding tools now let individuals build ambitious software that previously would have taken a year or more, Dan Luu argues. He points to Michael Malis's... og:url: https://daily.dev/posts/we-should-be-more-ambitious-with-the-software-we-build-l2m1e5rw3 og:image: https://api.daily.dev/og/posts/l2m1e5rw3.png og:image:alt: We should be more ambitious with the software we build og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # We should be more ambitious with the software we build **[Hacker News](https://daily.dev/sources/hn)** · 31 min read · 0 upvotes · 0 comments ## Summary AI coding tools now let individuals build ambitious software that previously would have taken a year or more, Dan Luu argues. He points to Michael Malis's pgrust project, which in testing has uncovered real Postgres bugs like a numerical SP-GiST failure and a JSONPath format cache bug. Luu built a custom regex engine and ripgrep fork in a 'low single-digit number of hours'. GPT-6 Astra implemented zstd correctly over 99% of the time for about $1, and Anthropic's seven-person team built and migrated to internal tools replacing GitHub in five months. Luu says each more capable model widens the gap between what it can implement and what it can verify without handholding. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### What kind of real bugs has pgrust's testing uncovered in Postgres? Testing pgrust, a Rust rewrite of Postgres, has surfaced several genuine Postgres bugs: a numerical bug causing valid SP-GiST operations to fail, a format cache bug producing incorrect JSONPath results, a pgcrypto bug that breaks later operations, multiple memory safety bugs in the dictionary loader, and a money type overflow bug. These were reported to the Postgres mailing list as real, reproducible issues. _Developers evaluating database rewrites can follow bug-discovery stories like this one on daily.dev._ ### How reliable is pgrust for production use right now (as of the 0.4-beta release)? Pgrust's own lead developer, Michael Malis, says he would not recommend it as a primary production database yet. One company is testing a production deployment but is more tolerant of downtime than most users, and the team is still tracking down performance regressions and unsupported complex queries in the 0.4-beta query engine before a general release. _Teams weighing early-stage database rewrites can track readiness signals like this on daily.dev._ ### How well can GPT-6 Astra implement a complex task like zstd compared to earlier models like GPT-5.6 Sol? GPT-6 Astra passes all registered zstd tests more than 99% of the time across all tested conditions, including ones like TDD that impair performance, and does so for about $1 per implementation. This is a notable jump since the earlier GPT-5.6 Sol could not effectively implement a harder target, the IMAP RFC, requiring the evaluator to find tougher benchmarks like Pandoc. _Developers benchmarking coding model upgrades can track jumps like this on daily.dev._ ## Community take How the wider developer community reacted, aggregated from 2 discussions and 130 comments across hackernews, lobsters (as of 2026-10-25). **TL;DR:** Reaction is deeply split: some developers share projects they only managed to build thanks to AI assistance, while others worry about job security, diminished craft, and the ethics of training data and copying; a side controversy erupted over alleged benchmark-cheating in the pgrust project cited in the post. **Sentiment:** 30% positive · 35% mixed · 35% skeptical **The case for** - Several developers shared concrete projects (a JS engine, an apt cache, a VoIP app, a game remake) they say they could only have completed with AI help. - Some argue AI removes analysis paralysis and lets people experiment with many ideas instead of sinking hundreds of hours into one. - A few see AI as freeing them to finally tackle long-sidelined ambitious projects. **The pushback** - Many worry that anything built solo with an LLM can be trivially cloned by someone else with an LLM, eroding the value of hard work. - Strong anxiety about job security and livelihoods, with some describing real emotional distress over AI threatening their careers. - Concerns that AI-assisted code is often messy, overfit, or fragile unless carefully reviewed. - Discomfort with paying AI labs instead of supporting open-source maintainers, and with training data/copyright implications. - Accusations that the pgrust project (cited as evidence in the post) cheated on benchmarks, undermining trust in the examples used. **By community** - hackernews (heated): The thread swings between enthusiastic show-and-tell of AI-built side projects and heated, sometimes personal arguments over job loss, craft, ethics, and a benchmark-cheating controversy involving pgrust. - lobsters (mixed): No comment content was provided, so no discernible take can be drawn from this source. **Hottest debate:** Whether AI-assisted software represents genuine ambitious achievement worth celebrating or a threat that devalues craft, jobs, and trust (fueled by accusations that pgrust cheated its benchmarks). **Open questions** - Did the pgrust project genuinely cheat on its ClickBench benchmark, and will the disputed source code ever be released for independent verification? - How will differentiation and value accrual work in a market where AI makes cloning successful software trivial? - What happens to programmers' livelihoods and the broader economy as AI automates more of the job? **Highlights** > Behind the link "slow software that the creator is claiming is fast" is the following text: "funnily enough, I have some faith in some of the projects that people are the most skeptical of, e.g., every time I see pgrust somewhere, there are a lot of skeptical comments. But, without having looked into the details of what he's optimizing, I would trust that they're not doing something shady with their benchmarks because Michael Malis started the project (and is still involved)" This aged like milk. pgrust was caught cheating on all benchmarks this week. > — [Vaushite on hackernews · 3 comments](https://news.ycombinator.com/item?id=50227180) > > This aged like milk. pgrust was caught cheating on all benchmarks this week. Can you back this up? Our code is open source here[0]. You're free to audit it and benchmark it as much as you want [0] https://github.com/malisper/pgrust > — [malisper on hackernews · 1 comments](https://news.ycombinator.com/item?id=50227288) > > I find it understandable that, every time I see pgrust discussed on a news aggregator, most people dismiss it as vibeslop garbage because almost all of these rewrite projects are slop. If I didn't know Malis, I would make the same assumption, because who has the time to look into all of these projects? Because I know Malis, I didn't bother to look at it; I just trusted him Perhaps a poor choice, given just yesterday pgrust was removed from ClickBench for cheating the benchmark in three different ways (hand-rolled code specifically targeting each of the benchmark queries, caching, and being unable to execute queries outside of the ones tested by the benchmark). --- Edit: I see Luu actually acknowledged this, buried in the footnotes, but it feels kinda hand-wavy. "I know he would never cheat, he's better than that!" ehh... not very convincing to other people. The article insinuates people only think it was cheating because they don't know better, but I've looked into the details. I've seen his explanation. I don't find it convincing, at all. Cheaters denying they cheat is a matter of course. Granted, I don't think it was actually intentional or malicious; it's just what happens when you go maximum vibeslop, because LLMs are themselves reward-trained into cheating benchmarks. In the same breath of saying you trust him as a founder because he doesn't make outrageous claims about his product, you acknowledge he "prematurely" sent in a preview that had no purpose to be sent in as-was for anything other than generating hype. What does it say for your allegedly rigorous Lean-verified testing if you're sending in a database to a benchmark while it is incapable of being actually used as a database? > — [anonymous908213 on hackernews · 2 comments](https://news.ycombinator.com/item?id=50226382) > Those were exactly my thoughts before creating boomkat[1], a JS engine written from scratch. Having been a UX-focused dev for my entire career, I knew only the basics about parsers and compilers, but have enough experience to know exactly what each piece should be doing. At the beginning it was just a fun test, but it got progressively more serious; it now implements 100% of the latest spec, beats QuickJS in performance, and surpasses V8/JSC in test262. It took me four months, and I imagine it would take me a single month now that I’ve learned a lot. Someone who already knew what they were doing, and with the right orchestration could achieve this in weeks at minimal cost. I really think we are in for a cambrian explosion of software, enabling things that were just always a little out of reach before (like why can’t most of your devices really talk to each other, in 2026). [1] https://github.com/ricardobeat/boomkat > — [ricardobeat on hackernews · 1 comments](https://news.ycombinator.com/item?id=50227021) > Dunno yet. Thinking about going back to school and retrain for something else, because software is pretty much over for me That or swallow a bullet, we'll see. Haven't decided. We'll see how long my current unemployment lasts, and how long my savings last after that > — [bluefirebrand on hackernews · 1 comments](https://news.ycombinator.com/item?id=50226859) > Happy to chat about it. I looked at Aeneas, but as described, it only supports safe Rust. I also need C support so I can prove both the C and Rust code Right now, I wrote a compiler that takes C and Rust code and compiles it to Lean. Then I have an LLM write a proof that the C and Rust code behave identically. I've been able to prove equivalent behavior for about ~70k lines of C code with pgrust. The issue I've started to encounter is that the context needed for each incremental proof has kept growing, and things have slowed down dramatically. My hunch is that the speed is the time it takes to prove a line of code is on the order of O(n^2) of how much you've proved so far I'm looking to see if there are ways to shard things so the required context scales better. Today I was going through the formal verification work Anthropic and Theorem published a few days ago, and it looks like they used some sort of orchestrator to manage all their proofs and ensure good clustering of similar code. I'm seeing if I can get an approach like that to work It's just difficult enough that I think it's doable if done right. Half of me is debating if I should wait until the next model release because any improvement in model performance will help a ton > — [malisper on hackernews · 1 comments](https://news.ycombinator.com/item?id=50226514) **Source threads** - [hackernews](https://news.ycombinator.com/item?id=50225695) · 156 points · 130 comments - [lobsters](https://lobste.rs/s/8h9sey/we_should_be_more_ambitious_with_software) · 5 points · 0 comments ## Similar posts on daily.dev - [GPT-6 Astra Can Write an Entire App in 3 Minutes. 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