Insights, guides, and thought leadership from the Antlr team.
The biggest mistake with AI coding agents isn't necessarily choosing the wrong model. It's wasting context. Here is how to start treating context, tools, and sub-agents as part of the architecture.
7 min read →The latest AI models can spin up hundreds of parallel agents in a single workflow. That capability is remarkable and genuinely useful. It also introduces failure modes most teams are completely unprepared for.
9 min read →Anthropic shipped Opus 4.8 just 41 days after 4.7. Here is what actually changed: dynamic workflows that spawn hundreds of parallel agents, a 3x cheaper fast mode, an effort parameter with real teeth, and benchmark numbers worth paying attention to.
8 min read →A growing body of research suggests that relying on AI tools may quietly erode our capacity for deep thinking. Here is what the evidence shows, and what to do about it.
8 min read →Most people assume they need more credits. In reality, they are just wasting tokens. Here are 7 practical ways to make your usage last significantly longer.
6 min read →Technical debt was a known mess. Comprehension debt is invisible until it isn't — and it's accumulating quietly in codebases everywhere.
9 min read →The quiet crisis of AI slop, and why shipping 37,000 lines in a day should be a warning sign, not a badge of honour.
7 min read →Something is wrong in software development right now. A slow, grinding wrongness that accumulates over weeks of constant pressure. Here's how to step off the cycle.
9 min read →The market is shifting faster than most developers want to admit. Here's what is actually worth doing about it — from software architecture to cloud certifications.
6 min read →AI security is no longer theoretical — it is operational. Here are the ten most important security risks every organization building or deploying LLM-powered systems should understand.
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