Your AI code reviewer isn't a second opinion. It may be the first opinion again.
A model writes the change. A model reviews the change and says it looks good. The pull request now...
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Latest Articles
Explore the latest thoughts and updates from Cyclopt.
An AI summary is not a fix. Stop letting it close your security findings.
Static analysis and LLMs are a good pairing. I'm not here to argue otherwise. But a lot of teams are...
Read more at Dev.toYour secrets don't need a git commit to leak into an AI tool
Most of us have the "don't commit secrets" reflex drilled in. Pre-commit hooks, secret scanners in...
Read more at Dev.to"I'm 93% confident" is a string, not a probability
The gap between the demo and the pipeline In the demo, you ask the model to return a...
Read more at Dev.toYour agent's retry bug isn't an AI problem. It's a distributed-systems problem with an LLM on top.
Most agent demos have a happy path: the model picks a tool, the tool returns 200, the agent moves on....
Read more at Dev.toYour model router is a classifier, and you probably aren't evaluating it like one
Most LLM cost discussions end with the same advice: don't send everything to the biggest model. Put a...
Read more at Dev.toHuman-in-the-loop isn't a safety net. It's a UX problem with a compliance label.
The diagram vs. the Tuesday afternoon On the architecture diagram, human-in-the-loop looks...
Read more at Dev.toShipping faster with AI isn't engineering maturity. It's a demo that hasn't met year two yet.
Every AI rollout comes with a dashboard. PRs merged per week, time from ticket to prototype, model...
Read more at Dev.toYour bugs used to burn CPU. Now they burn money.
In traditional software, a badly written loop gives you a CPU spike. Somebody gets paged, the graph...
Read more at Dev.toYour AI feature isn't a feature. It's a dependency you don't control.
In the tutorial, the AI call always works. You import the SDK, paste in an API key, await a...
Read more at Dev.toHalf the AI agents in production are if-statements with a GPU bill
There's a new kind of technical debt, and it doesn't come from cutting corners. It comes from...
Read more at Dev.toYour model doesn't need more training. It needs a better search index.
Intro Every team that plugs an LLM into its business hits the same moment. Someone asks...
Read more at Dev.toYour LLM has no memory. Your application had better have one.
Intro Every LLM tutorial has the same shape. You send a list of messages, you get a reply,...
Read more at Dev.toTwo-second latency isn't an AI problem. It's an architecture problem your stack was never built to hide.
Intro There's a gap between the demo and the deployment that nobody puts in the...
Read more at Dev.toYour LLM Isn't Bad At Math. It Was Never Doing Math In The First Place.
Your LLM Isn't Bad At Math. It Was Never Doing Math In The First Place. In a tutorial, an...
Read more at Dev.toAI Model Upgrades Aren't Patches. They're Silent Breaking Changes Wearing a Version Bump.
Intro AI Model Upgrades Aren't Patches. They're Silent Breaking Changes Wearing a Version...
Read more at Dev.toAI Didn't Kill the Need for System Design. It Just Made Bad System Design Easier to Ship.
Intro AI Didn't Kill the Need for System Design. It Just Made Bad System Design Easier to...
Read more at Dev.toYour AI-generated tests aren't testing your code. They're testing the AI's blind spots.
Intro There's a pitch behind every "AI writes your tests too" workflow: more coverage,...
Read more at Dev.toSemantic caching isn't a cost-saving hack. It's an admission that most "AI features" are FAQ bots in disguise.
Intro There's a pitch behind every new AI-powered feature: it understands anything a user...
Read more at Dev.toAI autocomplete isn't a productivity tool. It's a judgment test you take every few seconds.
Intro There's a pitch behind every AI coding assistant: it makes you faster. Fewer...
Read more at Dev.toAI-Generated Code Doesn't Have a Readability Problem. It Has a Style-Enforcement Problem Wearing an AI Hat.
Intro Ask an AI assistant to "handle the checkout flow" and it will hand you a working...
Read more at Dev.toUsing AI to Code Isn't the Risk. Not Understanding What It Shipped Is
Intro There's a gap between the way AI-assisted coding gets demoed and the way it actually...
Read more at Dev.toYour model doesn't need to pass the bar exam. It needs to parse a log file.
Intro Every few weeks, another frontier model claims a new benchmark, better reasoning,...
Read more at Dev.toThe all-purpose agent isn't an architecture. It's a single point of failure with a system prompt.
Intro In a demo, one agent that "does everything" looks like impressive economy: one...
Read more at Dev.to"Unlimited context" is not a feature. It's technical debt with better marketing.
Intro Model providers keep shipping bigger context windows: 100k tokens, 200k, over a...
Read more at Dev.toBanning ChatGPT Won't Fix Your Shadow AI Problem. It'll Just Hide It.
Intro Every engineering org has a policy about which AI tools developers are allowed to...
Read more at Dev.toRAG isn't an AI problem. It's a data engineering problem wearing an AI hat.
The tutorial-to-production gap Every RAG tutorial follows the same arc. Load some...
Read more at Dev.toThe fallacy of "AI-first." Start with the friction, not the technology.
The label that gets the sequence backwards "AI-first" has become a branding exercise....
Read more at Dev.toAI frameworks make the first 10% feel like magic. The other 90% is where they break you.
The magic window Every AI framework ships with a demo that looks incredible. Spin up an...
Read more at Dev.toThe AI conversation is shifting from "what can it do" to "can we rely on it"
The capability phase is over For the past two years, the AI conversation has been about...
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