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bnchrch

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https://ben.church

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by.ben.church 1mo ago

Atoms and Knowledge

bnchrch
2pts0
output.ai 3mo ago

Show HN: Output.ai - OSS framework we extracted from 500+ production AI agents

bnchrch
40pts11
by.ben.church 5mo ago

Imperfect advice on how to be happy

bnchrch
2pts0
by.ben.church 5mo ago

On Luck, My Daughter

bnchrch
2pts0
github.com 5mo ago

Elixir, Kotlin, C# Outperform Python, TypeScript and Go on AutoCode Benchmark

bnchrch
3pts0
github.com 9mo ago

Vibesdk: Cloudflare's open source AI-coding app toolkit

bnchrch
1pts0
news.ycombinator.com 10mo ago

Show HN: wt a tool to help quickly manage git worktrees

bnchrch
2pts0
airbyte.com 1y ago

Airbyte 1.0 – Marketplace, AI Assist, Gen AI Support and Enterprise GA

bnchrch
50pts28
github.com 1y ago

Two Million Checkboxes: A OMC clone using only Elixir

bnchrch
2pts0
news.ycombinator.com 2y ago

Ask HN: Whats State of the art for Code Sandboxing? (2024)

bnchrch
7pts7
mainmatter.com 2y ago

Making Elixir even faster using Rust

bnchrch
1pts0
supersimple.org 2y ago

Using Embedded Elixir to power an automated sprinkler system

bnchrch
1pts0
airbyte.com 3y ago

Using Adapt and Beam for Effective Data Modeling

bnchrch
33pts2
news.ycombinator.com 5y ago

Ask HN: How can we improve Public Developer Documentation?

bnchrch
1pts1
hiring.ben.church 7y ago

Show HN: Hacker Hiring Hunt

bnchrch
1pts1
news.ycombinator.com 7y ago

Ask HN: Who invests with a Robo-advisor and what is your experience?

bnchrch
1pts1
medium.freecodecamp.org 7y ago

Show HN: Bitly is expensive so I made a tutorial on shortening links with Mnesia

bnchrch
3pts1
medium.freecodecamp.org 7y ago

Show HN: A tutorial on how to read and write from iOS's HealthKit

bnchrch
2pts0
medium.com 8y ago

Writing a Reverse Proxy with One Line of Go

bnchrch
2pts0
hackernoon.com 8y ago

Using GraphQL to manage local state with Apollo

bnchrch
1pts0
medium.com 8y ago

What I keep in my bag as a Remote Developer

bnchrch
2pts0
hackernoon.com 8y ago

Using apollo-link-state instead of redux in your next application

bnchrch
1pts0
hackernoon.com 8y ago

A simple notification system with pg_notify and Elixir

bnchrch
1pts0
medium.com 8y ago

Using pg_notify and Elixir to make a simple notification system

bnchrch
8pts0
news.ycombinator.com 9y ago

Ask HN: What are some good tools for keeping a software project on track?

bnchrch
99pts74
news.ycombinator.com 9y ago

Ask HN: Is React Native worth learning?

bnchrch
2pts1
benchurch.me 9y ago

Show HN: Hacker Hiring Hunt, a small React app to search who's hiring

bnchrch
57pts13
github.com 10y ago

Show HN: A Slack bot to find your team drink recipies

bnchrch
2pts0
news.ycombinator.com 10y ago

Ask HN: Need help deciding between a small django shop vs. large .net company

bnchrch
10pts12
news.ycombinator.com 12y ago

Show HN: Idea Sunday App

bnchrch
16pts4
Claude Fable 5 1 month ago

Automobiles are not interesting or useful because they're justing using trails the horses already built.

Claude Fable 5 1 month ago

An 11% jump over opus 4.8 and a 22% jump over gpt 5.5 on Agentic Coding Benchmarks is certainly impressive.

Obviously still need to verify it for myself to see if it's truely a leap.

But am I the only one wondering, "What can I do today that I couldnt do yesterday?"

Previously I would think "Oh I wonder if I can finally get it to do X now?"

However now I feel like yesterdays models were more that capable to handle nearly any engineering task I paired with it on.

Maybe this is the final leap where I can comfortable set up an autonomous coding loop? Maybe.

Oh man a few things

1. A dashboard that tracks my personal metrics (github, strava, todo completion, flossing)

2. A eink display for that dashboard

3. A realtime node graph that shows a codebase (and/or its diffs) in a way that I can visualize what functions call which, and under what conditions

4. A agent that automatically fills out government forms and creates invoices for my friends brewery based on the delivery notes in their google calendar.

I'm sorry. But whats the point of this critique?

That a raw LLM hallucinates?

That we never see all the mistakes and dead ends a complex system using AI hits?

Does it even matter if its accuracy rate across all its experiments is < 100% if it can run trillions of experiments in the same time a human could run 1?

We don't see many of the failed attempts of Human Researchers. Why? Because it doesn't matter.

What amazing here is that it shows our society can make discoveries faster in the post LLM world. Thats incredible.

Your "critique" of how it happened. Not so much.

Our teams efforts have shifted toward reviewing plans as a team.

Before code hits a humans eyes it's went through a few independant review passes from our review agents.

If it's low complexity / blast radius it gets auto merged.

If it's high complexity / blast radius it gets flagged for human review.

And funny enough our team has agreed even our human review layer has the best results if we have an agent create supplementary descriptions of the code and potential issues that we read and apply human judgement.

Reason being is that it can be very pendantic. Both in a good and bad way. Either flagging things that are non-concerns, or catching things my lazy human eye wouldnt have caught. e.g. A docstring mis-describing the actual shape of an object.

I'm not sure it's fair to call the Apple Vision Pro a flop in the traditional sense.

While it may not have sold millions of units and been a household staple.

It certainly focused the entire org on manufacturing a suite of chips and hardware that are on a completely different level than their competitors. Apple's now has a clear advantage in all dimensions that matter: compute, power consumption, size, capabilities, etc.

Apple Vision helped created a moat that will be hard for anyone else to cross for at least a decade.

Oh I can answer that.

So we had a few goals here

1. Be opinionated on best practises, tools and libraries

2. Not get in the way of what the developer wants to do

To that end the core is built on top of Temporal, and our llm package is a thin wrapper around ai-sdk that provides QoL enhancements (Prompt files, tracing, cost tracking etc..)

So for failures in general, and tool calling specifically there are two levels of retries.

1. ai-sdk level tool retries: The library by default handles tool call failures and will retry if the LLM deems it a transient issue, and will never hard fail if one of its tool calls in unsuccessful (unless perhaps you instruct it to).

2. Temporal level activity failures: Our workflows and steps are all configured with a base line affordance to reattempt steps that have failed. You as the developer are able to change this, you can make it so a step is never retried, or retried say 100 times with exponential backoff.

Hope that helps!

Hey dangent! Glad you find it interesting!

So the API keys during setup are entirely optional. They're used in the example workflow that evaluates blog posts for clarity and provides feedback on how to improve.

Youre more than free to ignore/delete the example workflow and create your own that doesn't make use of an LLM 1. Fetching trending hn posts 2. Pulling reddit posts that match keywords 3. Transforming Daily calendar events into an html page etc..

And the claude code plugins (that are installed for you) all work with you Anthropic subscription no problem

Happy to see this launched, particularly today.

I own a stake in a small brewery in Canada, and this feature just saved me setting up some infrastructure to "productionize" an agent we created to assist with ordering, invoicing, and government document creation.

I get paid in beer and vibes for projects like these, so the more I can ship these projects in the same place I prototype them the better.

(Also don't worry all, still have SF income to buy food for my family with)

Hey! Ben here (one of the engineers who built this).

This is a reason why we made our http framework (@outputai/http) a first class citizen for the greater framework and our claude code plugins.

As you pointed out at this moment in time theres a Cambrian explosion both in new tools/libraries and the willingness to use them, which poses a systemic security threat when combined with how LLMs function.

So while you're free to use any third party tool or library you want with Output. We encourage you to roll your own as often as possible both for the security/control it gives you. But also for the vertical integration it provides (debugging, cost tracking, evals etc...)

There's an interesting side effect to the current state of the non-technical world.

We have some new tools that increase productivity, and these same tools both lower the barrier to entry to understanding software concepts and building software.

I think the result is more people who would've been traditionally considered non-technical are going to be onboarding to concepts that wouldve been traditionally ring fenced in the developer world.

Granular version control and diffs being one of them.

If this trend is real, and relatively large, I think it will be a good thing.

I can only assume Chuck has decided to relieve the grim reaper of his duties, leaving us all here to meet our own end not with a scythe but a roundhouse kick.

At the same time it feels like the python is overused.

If I could wave a magic wand to reset any programming language adoption at this point I would choose Python over Javascript.

I think Pythons execution model, deep OO behaviour, and extremely weak guarantees have done a lot of damage to the soundness and performance of the technology world.

1. Proprietary Data (Youtube, docs, gmail, cloud logs, waymo, website analytics, ads, search, the list is huge)

2. Commercial Datacenters (theyre ahead at least)

3. Chip production (Google is manufactoring proprietary chips)

4. Consumer OS (Chrome, Andriod)

5. Consumer Hardware (Pixel)

Basically google has access to data that OpenAI will never have access to, can lower costs below what OpenAI can, and is already a leader in all the places OpenAI will need massive capex to catch up.

Thats a large reason for sure!

I'd layer in a few more

* Largely stable and unchanged language through out its whole existance

* Authorship is largely senior engineers so the code you train on is high quality

* Relatively low number of abstractions in comparisson to other languages. Meaning there's less ways to do one thing.

* Functional Programming style pushes down hidden state, which lowers the complexity when understanding how a slice of a system works, and the likelyhood you introduce a bug

This is an understate and often unsaid take. But its 100% right.

Its also why you'll hear many engineers opine over functional programming.

Most start by thinking about 1. What does a system do for me?

Then onto 1. What actions does a system do? 2. Where should files and folders live? 3. Where should services live?

and stop there.

But the true key is when you just think about how data moves through your system.

Then you learn to simplify.

No classes, no hidden state, just simple functions with an input and an output and nothing else.

Long story short: Think about your system in data, and learn how to keep your code super simple to help with that thinking

I may have something to teach you about indicators, averages, and population samples/biases.

We're not debating majority opinion here. Just that people exist who have that bias / perception and what it leads to.

People exist that judge and exclude based on if you have have an Android.

Im sure the reverse exits too.

Im also sure the former is more common than the later.

But I have no idea how large that population is.

Just like Im not in that population.

Maybe, but let me pose you mental model that a lot of NA iPhone users have.

For a long time, if you were on iOS and added a android user to your group chat. All threading was broken. It was no longer a group chat just a bunch of out of band messages.

So iOS users naturally started leaving the android user out of the chat. They would text their 5 friends on iOS in one group to make plans, then text their Android friend separately to update them when plans were made.

I believe this is relatively fixed in latest iOS, but that habit is still very much their in iOS users today.

Anecdotally I did just experience a group chat of 4 iOS users this year that was very active, then died when one person switched to Android.

Its a real issue in North America.

SMS and as a result iMessage is the dominant text based chat.

iPhones have become the default smartphone, and is a status symbol compared to Android.

Mac vs Windows is similar on the laptop front.

Which means if your an Android user in a relatively average social group:

* You will get left out of group messages

* You will be starting on a back foot in the dating scene

On top of you wont be able to answer messages from friends on your laptop, because again, sms is dominant, not whatsapp.

Now don't shoot the messenger here. I don't like it either, but this is the social/technical reality in NA at the moment.

(sigh: receiving downvotes)

Reacts added some poor abstractions over the last decade. Looking at you hooks and effects.

But its far from the worst.

It was the first framework to put together JSX, a functional way of defining components and simplifying state. This was a monumental improvement. As a result they earned mass adoption.

As a result its the framework that now has a community moat that is not going to crumble until someone else can break ground in the way they did.

Sure, some of these could be considered "better" but they're all better due to incremental improvements for Frontend Engineering.

None of which are substantial enough to unseat the king

We mourn our craft 6 months ago

Well said. This sums up my own feeling. I joined this craft and love this craft for the simple ability to build beautiful and useful things.

This new world makes me more effective at it.

And this new world doesn’t prevent me from crafting elegant architectures either.

Swift has all the things I want in a language

- Strong Typing

- Great Performance

- Actor Model Concurrency [0]

- Modern Ergonomics

- Corporate Backing

- Performance

- Functional Style

- LLMs perform well with it [1]

- Usable across iOS, Android, Web, and Browsers [2][3]

The only thing its missing is adoption outside of the iOS space.

I'm not sure it will be able to make that leap, but the ingredients are there.

If it does I'd be happy to make it my primary language.

----------------

[0] https://www.hackingwithswift.com/quick-start/concurrency/wha...

[1] https://github.com/Tencent-Hunyuan/AutoCodeBenchmark/blob/ma...

[2] https://www.swift.org/blog/nightly-swift-sdk-for-android/

[3] https://vapor.codes/