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Practical writing on software architecture, SaaS products, AI automation, legacy modernisation, and the business of building reliable systems.
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To match the speed of AI cyber threats, public sector security teams are using AI-powered SOCs to reduce fragmentation and accelerate AI threat detection and response.
The API is now available. Authenticate with your project's and start querying more than 600,000 skills from across the open-source ecosystem.skills.shVercel OIDC token Search for skills, pull detailed info on any one, check its security audit, and more. Vercel issues a short-lived token scoped to your team and project, rotated automatically, so there's no long-lived secret to leak or rotate. On each request, skills.sh verifies the token and applies a rate limit of 600 requests per minute per t
The scale wall A computer vision pipeline that works on one image at one resolution isn't a pipeline. It's a prototype. The moment you move beyond controlled inputs, you hit the reality of production images: a 4K video frame, a satellite capture, a whole-slide pathology image, a high-resolution document scan. These images don't fit in a single model call. They're too large, too detailed, and too information-dense for one inference pass to handle well. So you tile it. You divide the image into
Based on real industry trends. About an AI testing tool promising 300x efficiency, a VP who rebranded hand-written automation as "manual testing," and a $700K SLA bill nobody saw coming. VP Harrison stood in front of the screen, the AI testing dashboard glowing behind him. "Three days. Three thousand test cases. Zero human intervention." He paused. Let his eyes sweep the room. They landed on me. "And some people — six years. Maintained four hundred automated test cases. That's less than twenty p
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As a recent Computer Science graduate, I've decided to commit myself to learning AI consistently and sharing that journey publicly. In a world where many people document their daily lives, I want to document something that is transforming my future—my growth as an AI Engineer. This is my very first dev post, and the beginning of what I hope will be a long series of learning notes, project breakdowns, insights, challenges, and discoveries in AI, Machine Learning, LLMs, Agents, RAG, System Design,
Track every AI request with team_id, user_id, model, token counts, and feature context, or your invoice will stay unexplainable. Build a request-level cost ledger first, then roll it up into team, user, feature, and model views. Most LLM spend spikes come from a small set of causes: model switches, prompt bloat, retry storms, and unbounded feature adoption. The fastest useful audit is not perfect chargeback. It is a weekly process that shows who spent what, why it changed, and what action to tak
NVIDIA RTX Spark launched on June 1, 2026, and within 72 hours the internet had already decided it was either the death of Apple Silicon or the next Windows Recall disaster. NVIDIA's official announcement video hit 1.3 million views in under four days. Linus Sebastian's "NVIDIA Just Slapped Apple Silicon" comparison racked up 1.23 million views at nearly 400,000 views per day. And Alex Ziskind's backlash video — "RTX Spark Is Already Making People Mad" — pulled 207,000 views with over 1,100 comm
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