hackernews as a whole has the same issue software engineers have - overestimating one's wisdom and overapplying it with confidence to everything, resulting in horrible takes that might look like signals but are mostly noise
Honestly, HN has a lot of people getting infuriated by storms in teacups and spouting shit. Definitely an order of magnitude better than Reddit or Facebook but still not the same as IRL.
Google Search has gotten better unless you think AI mode is a downgrade, the alternative of having a wikipedia article, reddit post or random website as the first result is not better technically maybe morally for you but not matter of factually. The average user does less manual filtering.
I definitely think the AI mode is a downgrade. It has me seriously considering abandoning Google for different search engine. With a reddit post or a Wikipedia article, it's much easier to assess the credibility of the content.
The AI mode does at least attempt to list it's sources, but it's extra hoops to jump through.
For the average Google User, searching for things like who perform in the Superbowl it is not extra hoops and incredibly fast. It's going to power Siri soon, enjoy.
hasn't been my experience, I am able to search for information faster, speed to correct answer has increased on average, I feel, if we start providing examples your argument starts to fall fast. Think about the average Google Search, you really think it gets it wrong? Your search query is probably more obscure than mainstream web users.
I’d infinitely prefer a relevant wikipedia article to an AI “Answer” that is almost always wrong.
Google lens image search used to be amazing, I tried a repeat of a search I did before of a piece of art, it showed the same piece but confidently listed the artist and year wrong by about 300 years.
I’ve had relatives do “research” about things I mentioned I needed to do, and they’ve just sent screenshots of the incorrect AI answer.
It’s made google almost entirely useless, there is zero incentive for them to try to make search better (vs incentive to make it worse) and even if they did want to make it better the sheer volumes of slop have made that even harder.
We’ve completely sabotaged out ability to collate information at scale as a civilization, for the benefit of a few companies that were already the largest in the world to begin with. And it turns out, very few people notice or even care about this.
almost always wrong is just incorrect. Ask it who made Hackernews and it says Paul Graham with a informational paragraph it scraped from Wikipedia, without me clicking into Wikipedia. I can provide so many examples.
I primarily use Gemini 3 Flash with a GUI coding agent I made by myself and its been able to successfully one-shot mostly any task I throw at it. Why would I ever use a more expensive reasoning and slower reasoning model? I am impressed with the library knowledge Gemini knows, I don't use any skills or MCP and its able to implement functions to perfection. No one crawls more data than Google and their model reflects that in my experience.
My experience with Antigravity was that 3 Pro can reason itself out of Gemini’s typical loops, but won’t actually achieve it (it gets stuck).
3 Flash usually doesn't get into any loops, but then again, it’s also not really following prompts properly. I’ve tried all manner of harnesses around what it shouldn’t do, but it often ignores some instructions. It also doesn’t follow design specs at all, it will output React code that is 70% like what it was asked to do.
My experience with Stitch is the same. Gemini has nice free-use tiers, but it wastes a lot of my time with reprompting it.
I don't use Stitch it doesn't have the context of my codebase, I just tell Gemini to make the UI directly and its able to do it. The only time it failed is when my prompt and goal was bad. I told it to swap expo-audio with react-native-track-player and it was able to do it in one-shot. Implement Revenue Cat and it did it in one shot. I do task by task like all the other agent tools recommended. The harness I made doesn't install packages, it just provides code. I don't use Anitgravity or any Electron-based coding agent, mine has a Rust core and different prompt engineering, not sure why it works so well but it does.
I need to implement a better free trial plan, it's reached enough maturity where its my only and primary way I write code, I also use web chats to help me craft prompts. Reach out to test.
https://slidebits.com/support
you can run into payload too large errors, ingesting bunch of context, I use vercel's ai sdk so I can interchange between models but have 0 OpenAI and Claude credits or subscriptions. I use a combination of grepping files like a terminal tool and implemented a vector search database for fuzzy searches, Gemini chooses what tool it wants to use, I provide it create, read, update, delete, functions. There's a few tricks I do as well but if I tell you, you can probably prompt a clone . Sharing the full implementation is basically open sourcing the code.
You should really provide a comparison to existing agentic tools if you expect people to buy annual licenses to your tool. Right now pretty much all of your competition is free and a there are a lot of good open source agents as well.
The AI generated landing page is pretty lousy too, did you even review it? As an example, it says "40% off" of $199.99 = $99.99? Its also not clear if your pricing includes tokens. It says "unlimited generations" are included but also mentions using your own API key?
AI web agent that lives in a wasm sandbox with predefined skills, it creates websites, mobile apps, powerpoint slides (.pptx files), word documents (.docx files), visualize csv data, and creates remotion videos, no external sandbox servers, all in wasm.
talk is even cheaper, still show me the code, people claim 10x productivity that translates to 10x of work done in a month, even with Opus 4.5 out since November 2025 I haven't seen signs of this. AI makes the level of complexity with modern systems bearable, it was getting pretty bad before and AI kinda saved us. A non-trivial React app is still a pain to write. Also creating a harness for a non-deterministic api that AI provides is also pain. At least we don't have to fight through typing errors or search through relevant examples before copying and pasting. AI is good at automating typing, the lack of reasoning and the knowledge cutoff still makes coding very tedious though.
Best example of this is Claude's own terminal program. Apparently renders react at 60fps and then translates it into ANSI chars that then diff the content of the terminal and do an overwrite...
All to basically mimic what curses can do very easily.
This is the fun part of whole AI-built things that a lot of people don’t want to accept - it really, really, really does not matter if the code “nice, maintainable and etc.”. Does it work? Is it somewhat extendable with AI? Are users generally happy and adoption rate is high? That’s it.
If you have high time preference yes. Over longer time horizons I think the issues with vibe coded software will reveal themselves in the same way badly written software does.
Remember 8 years ago how vibe coding was awful? Like i never used it in prod apps. Now i'm a daily CC user, and every few months models are getting better, some problems are being solved, the other ones still being worked on and so on.
Opus was a non-deterministic probability machine in the past, present and the foreseeable future. The variance eventually shows up when you push it hard.
I don't get this sentiment, regressions still exist, you can't just prompt them away and a programmer will spend 10x more time fixing regressions, bug fixing and improvements than scaffolding in most projects that people pay for. If most of your time at work is not doing this, then you are already living a simple life.
I found out that Claude Code and OpenCode doesn't do vector search and embeddings but relies on grep to power their agents. Most people are satisfied with this even though I think vector search approach is way better and saves on tokens.
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