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Ian Mackintosh

https://en.wikipedia.org/wiki/Ian_Mackintosh
1•petethomas•41s ago•0 comments

Show HN: CPU-only fact-check, summarize, explain, translate any text

https://github.com/kouhxp/fftext
1•mrkn1•2m ago•0 comments

Konversio: Open-source AI customer support for digital sovereignty

https://www.konversio.org/
1•rcoenen•2m ago•0 comments

A2 Is Released

https://www.neuralampmodeler.com/post/a2-is-released
1•vcxy•4m ago•0 comments

'Close to the Terminator narrative': the dawn of self-improving AI

https://www.ft.com/content/7cc7800f-18ed-47d8-9539-221ae3e16182
1•petethomas•11m ago•0 comments

Show HN: Browser-based, Blender-like hard-surface modeling

https://roughform.com/
1•benhmoore•11m ago•0 comments

Steve Ballmer blasts Aspiration co-founder's bid for leniency in sentencing

https://www.latimes.com/sports/story/2026-04-23/steve-ballmer-delivers-rebuke-to-aspiration-exec-...
1•1vuio0pswjnm7•13m ago•0 comments

Microsoft Scout

https://learn.microsoft.com/en-us/microsoft-scout/
1•doppp•19m ago•0 comments

Show HN: an AI that settles small couple arguments

https://thepiece.app/en
3•Byalpel•28m ago•0 comments

Teaching AI agents to ask better questions by playing "Battleship"

https://news.mit.edu/2026/teaching-ai-agents-ask-better-questions-playing-battleship-0603
1•droidjj•29m ago•0 comments

Digital Goods by ProxyStore

https://digitalgoods.proxysto.re/en
1•Cider9986•30m ago•0 comments

A Structure-Aware Fuzzing Experiment

https://fitzgen.com/2026/06/01/structure-aware-fuzzing-experiment.html
1•sfink•36m ago•0 comments

A Primer in Post-Training Reasoning Data: What We Know About How It Works

https://arxiv.org/abs/2606.02113
1•Anon84•36m ago•0 comments

JackHamr, cloud workspaces for orchestrating coding agents

https://www.jackhamr.ai
3•jrda•36m ago•1 comments

FUTO Swipe Relative error rate improvement vs. Gboard

https://swipe.futo.tech/
1•Cider9986•39m ago•0 comments

California Back and Pain Specialists Exposes 133GB of Patient Medical Records

https://write-ups.security-chu.com/2026/06/California-Back-Pain-Specialists-with-data-breach.html
1•news_rt•44m ago•0 comments

Pie: Yet another open-source coding agent in Rust

https://github.com/c4pt0r/pie
1•c4pt0r•44m ago•2 comments

I built a vulnerable app and spent $1,500 seeing if LLMs could hack it

https://kasra.blog/blog/i-spent-1500-seeing-if-llms-could-hack-my-app/
25•jc4p•48m ago•7 comments

Review of the MoErgo Go60 Keyboard

https://arslan.io/2026/06/02/review-of-the-moergo-go60-keyboard/
2•wapasta•48m ago•0 comments

Klaser Cards, a printable personal collection

https://klaser.cards/
2•Triphibian•49m ago•1 comments

Why Video Agent models are next

https://www.latent.space/p/video-agents
3•gmays•49m ago•0 comments

Dreambeans

https://labs.google/dreambeans
1•fallinditch•50m ago•0 comments

Aquifer – local flow control for bursty GPU-backed APIs

https://github.com/rjpruitt16/aquifer
1•rjpruitt16•50m ago•0 comments

Scholarly Futures: AI and the practical scientist

https://scholarlyfutures.substack.com/p/ai-and-the-practical-scientist
1•JohnHammersley•50m ago•0 comments

A community-ranked feed of blog posts from curated sources

https://bubbles.town/
1•wwfn•54m ago•1 comments

Dystopic Future: The Set Design in Alien

https://kevinmccorrytv.ca/alien-2.html
2•exvi•54m ago•0 comments

The Star Blazers Page

https://kevinmccorrytv.ca/blazers.html
2•exvi•55m ago•0 comments

Monterey Park votes to permanently ban datacenters

https://www.theguardian.com/us-news/2026/jun/03/california-monterey-park-datacenters-ban
4•logickkk1•56m ago•0 comments

Limbic Capitalism

https://cwcp.ca/blog/limbic-capitalism/
2•the-mitr•56m ago•0 comments

The Lost Space Battleship Yamato LaserDisc Game (2013)

https://www.ourstarblazers.com/vault/363/
1•exvi•56m ago•0 comments
Open in hackernews

I Replaced My Devs with Agents – Part 2: What Happened to the Team

https://easylab.ai
2•buzzbyjool•1y ago

Comments

buzzbyjool•1y ago
Follow-up to Part 1, where I explained how we rebuilt our dev process around LLM agents at Easylab AI and stopped writing most code by hand.

The original post sparked a lot of questions — the most common being:

“Okay, but how did your developers react?”

Here’s a breakdown of what actually happened inside the team — who stayed, who didn’t, and what new skills emerged.

⸻

Some embraced it. Some left. That’s okay.

When we committed to building with agents — not just using LLMs for autocompletion, but making them first-class executors of logic — not everyone was thrilled.

Some engineers were fascinated. They saw the shift coming and wanted to be ahead of it. They became architects of multi-agent workflows, prompt designers, QA strategists, validators.

Others didn’t want to work that way. They liked writing every line, owning every detail, and were (understandably) uncomfortable giving up control to a system that feels less deterministic.

They moved on. We didn’t push them.

Like every evolution in software tooling, this one came with a natural selection effect. Not better or worse. Just different skillsets, different energy.

⸻

This isn’t no-code. It’s new-code.

Some assumed we were just automating CRUD. That’s not what happened.

The tools we use today — Claude 3.7, DeepSeek, bolt.new, role-based agents, memory stacks — aren’t trivial macros. They’re a new level of abstraction. They reason. They refactor. They test. They fail with style.

You don’t “ask the AI to do it.” You engineer constraints, context, fallbacks, tooling, and create robust systems through language.

At Easylab AI, we use context protocols, Redis-based memory layers, and model routing logic based on latency and task weight. It’s not less technical — it’s just built differently.

⸻

Did their skills atrophy?

Actually, the opposite.

Sure, they’re not practicing DSA interview puzzles every day. But they’re building systems that can write tests, simulate failure, and self-correct.

They’re learning new skills you can’t yet Google: • Prompt minimalism • Agent composability • Multi-agent state consistency • Prompt-based debugging

They think more like staff engineers than syntax solvers.

⸻

This is abstraction, not disappearance

The fear that “AI replaces engineering” misses the nuance.

This isn’t magic. It’s not cheating. It’s just abstraction — like every wave before: • Assembly to C • C to Python • Python to Terraform • Terraform to prompt-based execution

As Jensen Huang (NVIDIA CEO) said earlier this year:

“English is now the world’s most popular programming language.”

He’s not wrong. We’re just learning to write instructions that build systems — without the middle step of syntax.

⸻

One more thing

Some developers left. Most who stayed leveled up. And today, no one wants to go back.

That tells me something: It’s not easier work. It’s better work.

Happy to answer more if folks are curious.

falcor84•1y ago
I'm not clear - is this comment the actual post, while the link that you shared is irrelevant? If so, it would have probably been more appropriate to submit this as an "AMA:" without a url.
buzzbyjool•1y ago
Hi thanks for your comment, honestly I don't know how to do it. Thanks
falcor84•1y ago
Oh, it's just that you can make a submission without anything in the 'url' input. Here are a couple of examples:

https://news.ycombinator.com/item?id=15853374

https://news.ycombinator.com/item?id=43363056

buzzbyjool•1y ago
thanks
JohnFen•1y ago
> Some developers left. Most who stayed leveled up.

"Leveled up" is a subjective, loaded term. I assume what you mean here is "adapted to your way of doing things."

> And today, no one wants to go back.

Well, of course, because those who would have wanted to go back already left. This appears to be selection bias more than evidence that your approach is a good one.

To be clear, I'm not trying to imply that your approach isn't a good one. I'm just saying that the devs who remained not wanting to go back isn't evidence that it is.

buzzbyjool•1y ago
You’re absolutely right to call that out — and I appreciate the thoughtful framing.

“Leveled up” is subjective, yes. What I meant more precisely is this: the devs who stayed stopped spending time on tasks like writing boilerplate logic or tweaking form validation, and started focusing on higher-order thinking — designing agent workflows, debugging reasoning paths, writing specs that are machine-parsable, and thinking in systems rather than syntax. That shift, in terms of skill depth and adaptability, is something I genuinely view as a level-up. But I agree, it’s through the lens of our environment.

And yes — absolutely fair on the selection bias. When I say “no one wants to go back,” I don’t mean it as proof the approach is universally better. It’s just true for our current team, within the culture and processes we’ve chosen to embrace. Those who didn’t align with this way of working left early — and I don’t hold that against them.

So your comment is a valuable nuance: internal satisfaction is a necessary condition for success, but not a sufficient one. Our team’s enthusiasm is a sign that the model can work — not that it will for everyone.

Thanks for calling it out clearly.