Jan 8 · 6 min read · We are currently witnessing a massive architectural regression in software engineering. For the last twenty years, we spent our careers trying to make systems deterministic. We built unit tests, type safety, and immutable infrastructure to ensure tha...
Join discussionJan 2 · 6 min read · You think you're using AI. You're not. You're typing prompts into a black box and hoping it reads your mind. You have no idea why Claude gives you one answer, GPT gives you another, and Gemini spits out something completely different for the exact sa...
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Dec 26, 2025 · 4 min read · In the race for AI dominance, we are obsessed with parameters. We talk about model size as if it is a direct proxy for intelligence. We assume that a larger model—one with more "brain" power—will naturally produce better results. This is a developer’...
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Dec 23, 2025 · 3 min read · When you build on a single AI model, you aren't just inheriting its intelligence. You are inheriting its architectural blind spots. In a production environment, relying on one LLM (Large Language Model) is a systemic risk because every model has a "b...
Join discussionDec 22, 2025 · 5 min read · We are currently in a "context war." Model providers are racing to ship 100k, 200k, and even 1M token context windows. The marketing implies a linear relationship: if a model can ingest a whole book, it can reason about the whole book. In production,...
Join discussionDec 19, 2025 · 4 min read · Every developer has experienced the "long context" paradox. You see a model announcement claiming a context window of 100k, 200k, or even a million tokens. You expect the ability to ingest a full codebase and receive perfect architectural feedback. T...
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Dec 12, 2025 · 5 min read · We often think of coding as a purely technical activity. You get a requirement, you write the code, and you push the fix. Done. But if you’re a developer or an engineer who’s trying to move beyond just writing functional code, you need to understand ...
Join discussionDec 10, 2025 · 3 min read · The standard narrative in tech is that speed is paramount. We are encouraged to learn fast, ship fast, and iterate faster. We treat knowledge acquisition like a firehose: maximize volume, minimize time. I spent years following this model, rushing thr...
Join discussionDec 5, 2025 · 4 min read · A lot of developers don’t burn out because the work is too hard.They burn out because the learning never stops.There is always a new framework, a new pattern, a new update, a new “must-know” concept that makes yesterday’s knowledge feel outdated. It’...
Join discussionNov 28, 2025 · 6 min read · Most developers talk about new frameworks, backend optimizations, or which LLM model is faster this quarter.But the real threats to their careers — the ones that quietly compound behind the scenes — almost never make it into public conversations. Not...
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