Meta researchers developed a structured prompting technique enabling large language models to verify code patches.Continue reading on Towards AI »
How coding agents use tools, memory, and repo context to make LLMs work better in practice
Source: Grok AI-generated illustrationWhat is RLHF ?RLHF is a M.L technique where Al improves by learning directly from human feedback. It is used to align Al models with human goals, ethics and preferences. It uses Human feedback to optimize LLMs to s…
Photo by Igor Omilaev on UnsplashSometimes the best new ideas are born when constraints are loudest. You may have felt it yourself. That tug-of-war between the enormous promise of AI and the hard limitations of small budgets, restricted infrastructure,…
Prefill–Decode Separation, KV Cache Affinity, and What the Metrics ShowGetting an LLM to respond is straightforward. Getting it to respond consistently at scale, with observable performance, that’s where most deployments run into trouble.Traditional LL…
A Comprehensive Guide to Building Robust, Cyclic AI Workflows in the Generative AI EraIntroduction: The Shift to Agentic AIWhy do most LLM applications fail in production? Because they lack memory, reasoning, and the ability to adapt.In the rapidly evo…
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If you’ve ever watched a RAG system miss an obvious fact because the question was underspecified, this post might offer an insightful…Continue reading on Towards AI »
RPA (robotic process automation) is a practical and proven way to reduce manual work in business processes without AI systems. By using software bots to follow fixed rules, companies can automate repetitive tasks like data entry and invoice processing, and to a certain extent, report generation. Adoption grew quickly in many sectors, especially in finance, […]
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Context Engineering has gone from a niche concern to the core discipline of AI Engineering in under a year. In mid-2025, two posts laid much of the groundwork. Manus shared lessons from rebuilding their agent framework four times (July 2025). Anthropic…