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Show HN: I replaced my devs with AI agents – and it worked
I run a small AI company in Luxembourg. We started out as a consulting studio, building custom tools for clients — mostly boring things like dashboards, reporting modules, and CRUD backends.
At some point I realized we were building the same things over and over again. Not in a copy-paste way, but in a “we could generate 80% of this” kind of way. So last year, I ran a live-fire experiment: I asked Claude 3.5 and DeepSeek to build a small admin panel, with tests and API docs, from a plain-language spec.
The result: not great, but usable. It gave us the idea to stop typing code altogether.
Now, at Easylab AI, we don’t write code manually anymore. We use a stack of LLM-powered agents (Claude, DeepSeek, GPT-4) with structured task roles:
• an orchestrator agent breaks down the spec
• one agent builds back-end logic
• another generates test coverage
• another checks for security risks
• another synthesizes OpenAPI docs
• and humans only intervene for review & deployment
Agents talk via a shared context layer we built, and we introduced our own protocol (we call it MCP — Model Context Protocol) to define context flow and fallback behavior.
It’s not perfect. Agents hallucinate. Chaining multiple models can fail in weird ways. Debugging LLM logic isn’t always fun. But…
We’re faster. We ship more. Our team spends more time on logic and less on syntax. And the devs? They’re still here — but they’ve become prompt architects, QA strategists, and AI trainers.
We built Linkeme.ai entirely this way — an AI SaaS for generating social media content for SMEs. It would’ve taken us 3 months before. It took 3 weeks.
Happy to share more details if anyone’s curious. AMA.
- Magma7404 1y agoHave you hired a team of security experts to try to crack your web sites and get some validation or certification on the code?
- buzzbyjool 1y agonotyet but it's a good point, it's a subject !
- exceptione 1y agoTwo thoughts: - I admire your honesty of telling this. AI is quickly becoming something you rather want to hide. - I would never want to work at such a company. If I wanted to engineer by human language I would be a politician or a manager. If I wanted to babysit an automaton, I would have been a factory worker.
- buzzbyjool 1y agofor your second point, I understand your position, but I strongly believe that it's the future of coding. Coding was a way to translate a machine language to something more understandable, AI coding is simply the next step.
- fragmede 1y ago> If I wanted to babysit an automaton, I would have been a factory worker. I wonder if horse carriage drivers said the same thing about the advent of cars. Telling the LLM build me a login page instead of laboriously looking up example code in docs and retyping stack overflow snippets is definitely a different way of working, but thinking that makes someone a politician seems like a bit of a stretch.
- exceptione 1y agoThe difference is determinism. A technical inclined person wants to build things from first principles. Assembly or a higher level language are in that nature the same. Now, most humans are social beings and rather play social "games" with language. That is why technical people used to be called nerds, because they are the exception. Engineers by heart (those of their own choosing rather than because of economical pressure) love the technical reasoning part of their brain. Now a stochastic model that may lie to you, or respond differently on how your word it today, is a completely different kind of work. It is in principle not engineering, but rather some kind of managing or influencing.
- myk9001 1y agoWhat's your backup plan if you don't mind sharing?
- buzzbyjool 1y agowhat you mean by backup plan ? We produce proper code like node.js or similar that is backup and proceed in a normal pipeline. Just the production of the code is different.
- bennydog224 1y agoHow do your devs feel about this in regards to their career? Are they worried about their DSA/coding skills atrophying? Not knocking, just genuinely curious.
- buzzbyjool 1y agoGreat question — and one we took seriously early on. At first, there was some skepticism, and even a bit of anxiety. When we said, “We’re going full AI-assisted development,” the natural reaction was: “What does that mean for my skillset?” But here’s what happened in practice: Most of the repetitive tasks — CRUD, glue logic, API boilerplate — disappeared. Instead, devs started focusing on system design, agent orchestration, prompt engineering, constraint writing, testing strategy, and overall architecture. And they’re thriving. Nobody’s DSA muscles are atrophying — they’re just being used differently. If anything, they’ve gained new skills that aren’t widely available yet: how to design workflows with stochastic tools, how to debug agent behavior, how to build structured memory into LLM stacks. These are things you won’t find in textbooks yet, but they’re very real problems — and deeply technical. And let’s be real: you don’t forget how to reverse a linked list just because you stopped manually writing route handlers for user creation. In short: the devs that leaned into it have grown faster, not slower. And the ones who felt it wasn’t for them — they moved on. Which is fine. Every shift in tooling brings a kind of Darwinian filtering. It’s not about better or worse, just about who’s willing to adapt to a new abstraction layer. And that’s always been part of how tech evolves.