<?xml version="1.0" encoding="UTF-8"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Developers &amp; Builders — The Latent Daily</title><description>AI coding, agents, APIs, RAG, fine-tuning, local AI and MLOps.</description><link>https://thelatentdaily.com/</link><language>en-us</language><atom:link href="https://thelatentdaily.com/rss/developers-builders.xml" rel="self" type="application/rss+xml"/><item><title>Compute is the new capital: why AI startups raise GPUs, not just cash</title><link>https://thelatentdaily.com/articles/compute-is-the-new-capital-ai-startups/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/compute-is-the-new-capital-ai-startups/</guid><description>For AI startups, access to GPUs can matter more than money. How cloud deals, credits and chip reservations shape who can build frontier models.</description><pubDate>Sun, 18 Oct 2026 05:55:00 GMT</pubDate><category>Startups &amp; Funding</category><category>startups-funding</category><category>compute</category><category>gpus</category><category>cloud</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>Build, buy or fine-tune? How companies choose their AI approach</title><link>https://thelatentdaily.com/articles/build-buy-or-fine-tune-enterprise-ai/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/build-buy-or-fine-tune-enterprise-ai/</guid><description>Off-the-shelf assistants, API integrations, retrieval-augmented generation, fine-tuning or your own model: the trade-offs in cost, control and time to value.</description><pubDate>Sun, 18 Oct 2026 05:53:00 GMT</pubDate><category>Business &amp; Enterprise</category><category>enterprise</category><category>rag</category><category>fine-tuning</category><category>strategy</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>How to transcribe audio on your own computer with Whisper</title><link>https://thelatentdaily.com/guides/transcribe-audio-locally-with-whisper/</link><guid isPermaLink="true">https://thelatentdaily.com/guides/transcribe-audio-locally-with-whisper/</guid><description>Install OpenAI&apos;s open-source Whisper speech recognition model, transcribe recordings offline, choose the right model size and export subtitles in minutes.</description><pubDate>Sun, 18 Oct 2026 05:47:00 GMT</pubDate><category>Guides &amp; Tutorials</category><category>guides</category><category>speech</category><category>local-ai</category><category>open-source</category><category>whisper</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>Learning path for developers who want to build with LLMs</title><link>https://thelatentdaily.com/articles/learning-path-for-developers-building-with-llms/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/learning-path-for-developers-building-with-llms/</guid><description>From your first API call to retrieval, tool use, evaluation and deployment: an ordered path for software developers moving into AI engineering.</description><pubDate>Sun, 18 Oct 2026 05:39:00 GMT</pubDate><category>Courses &amp; Learning Paths</category><category>courses</category><category>learning-path</category><category>developers</category><category>llms</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>How to cut your AI API bill: caching, batching and model routing</title><link>https://thelatentdaily.com/articles/how-to-cut-your-ai-api-bill/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/how-to-cut-your-ai-api-bill/</guid><description>Practical techniques to reduce LLM API costs without hurting quality: prompt caching, batch APIs, smaller models, routing, shorter contexts and output limits.</description><pubDate>Sun, 18 Oct 2026 05:02:00 GMT</pubDate><category>Pricing &amp; Deals</category><category>pricing</category><category>cost-optimization</category><category>apis</category><category>developers</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>Model deprecations explained: what happens when an AI model is retired</title><link>https://thelatentdaily.com/articles/ai-model-deprecations-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/ai-model-deprecations-explained/</guid><description>AI providers regularly retire older models. How deprecation timelines work, what breaks when a model is shut down and how to plan migrations without surprises.</description><pubDate>Sun, 18 Oct 2026 05:00:00 GMT</pubDate><category>Changelogs &amp; Updates</category><category>changelogs</category><category>deprecations</category><category>apis</category><category>developers</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>How to use AI coding assistants effectively: a practical workflow</title><link>https://thelatentdaily.com/guides/how-to-use-ai-coding-assistants-effectively/</link><guid isPermaLink="true">https://thelatentdaily.com/guides/how-to-use-ai-coding-assistants-effectively/</guid><description>Get better results from Copilot, Cursor, Claude Code and other coding assistants: give context, work in small steps, review every change and keep tests in the loop.</description><pubDate>Sun, 18 Oct 2026 04:57:00 GMT</pubDate><category>AI Coding</category><category>ai-coding</category><category>developers</category><category>productivity</category><category>best-practices</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>Vibe coding explained: building software by describing it — and the risks</title><link>https://thelatentdaily.com/articles/vibe-coding-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/vibe-coding-explained/</guid><description>What &quot;vibe coding&quot; means, how people build apps by talking to AI, where it works brilliantly, where it fails, and how to keep vibe-coded projects safe.</description><pubDate>Sun, 18 Oct 2026 04:56:00 GMT</pubDate><category>AI Coding</category><category>ai-coding</category><category>vibe-coding</category><category>no-code</category><category>security</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>What are AI agents? How they plan, use tools and take actions</title><link>https://thelatentdaily.com/articles/what-are-ai-agents-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/what-are-ai-agents-explained/</guid><description>AI agents go beyond chat: they plan, call tools, browse and act toward a goal. How the agent loop works, the main design patterns, real uses and the risks.</description><pubDate>Sun, 18 Oct 2026 04:55:00 GMT</pubDate><category>Agents &amp; Agentic AI</category><category>agents</category><category>agentic-ai</category><category>tool-use</category><category>explainer</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>Model Context Protocol (MCP) explained: the &quot;USB-C port&quot; for AI tools</title><link>https://thelatentdaily.com/guides/model-context-protocol-mcp-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/guides/model-context-protocol-mcp-explained/</guid><description>MCP is an open standard for connecting AI assistants to tools and data. How servers, clients and tools work, how to try it, and the security points to know.</description><pubDate>Sun, 18 Oct 2026 04:54:00 GMT</pubDate><category>Agents &amp; Agentic AI</category><category>mcp</category><category>agents</category><category>tool-use</category><category>open-standards</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>Your first LLM API call: a step-by-step guide in Python</title><link>https://thelatentdaily.com/guides/first-llm-api-call-python-guide/</link><guid isPermaLink="true">https://thelatentdaily.com/guides/first-llm-api-call-python-guide/</guid><description>Set up an API key safely, send your first request to a language model in Python, understand messages, tokens and parameters, and handle errors and costs.</description><pubDate>Sun, 18 Oct 2026 04:53:00 GMT</pubDate><category>APIs &amp; SDKs</category><category>apis</category><category>python</category><category>developers</category><category>tutorial</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>Structured outputs and function calling: getting reliable data from LLMs</title><link>https://thelatentdaily.com/guides/structured-outputs-and-function-calling-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/guides/structured-outputs-and-function-calling-explained/</guid><description>How to make language models return valid JSON that matches a schema, how function calling works, and how to validate outputs so your application never breaks.</description><pubDate>Sun, 18 Oct 2026 04:52:00 GMT</pubDate><category>APIs &amp; SDKs</category><category>apis</category><category>json</category><category>function-calling</category><category>developers</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>How retrieval-augmented generation (RAG) works, step by step</title><link>https://thelatentdaily.com/guides/how-retrieval-augmented-generation-works/</link><guid isPermaLink="true">https://thelatentdaily.com/guides/how-retrieval-augmented-generation-works/</guid><description>RAG lets AI answer from your documents. Each stage explained: ingestion, chunking, embeddings, retrieval, reranking, prompting and evaluation, with practical tips.</description><pubDate>Sun, 18 Oct 2026 04:51:00 GMT</pubDate><category>RAG, Search &amp; Vector DBs</category><category>rag</category><category>embeddings</category><category>vector-databases</category><category>developers</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>Vector databases explained: how they work and how to choose one</title><link>https://thelatentdaily.com/guides/vector-databases-explained-how-to-choose/</link><guid isPermaLink="true">https://thelatentdaily.com/guides/vector-databases-explained-how-to-choose/</guid><description>Embeddings, similarity search, indexes like HNSW and the trade-offs between pgvector, Pinecone, Weaviate, Qdrant, Milvus and Chroma for your RAG project.</description><pubDate>Sun, 18 Oct 2026 04:50:00 GMT</pubDate><category>RAG, Search &amp; Vector DBs</category><category>vector-databases</category><category>rag</category><category>embeddings</category><category>developers</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>Fine-tuning an LLM with LoRA: a practical overview</title><link>https://thelatentdaily.com/guides/fine-tuning-llm-with-lora-practical-overview/</link><guid isPermaLink="true">https://thelatentdaily.com/guides/fine-tuning-llm-with-lora-practical-overview/</guid><description>When fine-tuning helps, how LoRA and QLoRA make it affordable, how to prepare data, train, evaluate and deploy an adapter — and when not to fine-tune at all.</description><pubDate>Sun, 18 Oct 2026 04:49:00 GMT</pubDate><category>Fine-tuning &amp; Training</category><category>fine-tuning</category><category>lora</category><category>qlora</category><category>open-weights</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>Knowledge distillation explained: how small AI models learn from big ones</title><link>https://thelatentdaily.com/articles/knowledge-distillation-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/knowledge-distillation-explained/</guid><description>Distillation trains a compact &quot;student&quot; model to imitate a large &quot;teacher&quot;. How it works, why it powers today&apos;s small models, and its legal and quality limits.</description><pubDate>Sun, 18 Oct 2026 04:48:00 GMT</pubDate><category>Fine-tuning &amp; Training</category><category>distillation</category><category>small-models</category><category>training</category><category>explainer</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>How to run a local LLM with Ollama: installation to first chat</title><link>https://thelatentdaily.com/guides/run-local-llm-with-ollama-guide/</link><guid isPermaLink="true">https://thelatentdaily.com/guides/run-local-llm-with-ollama-guide/</guid><description>Install Ollama, download an open model, chat in the terminal or a web interface, pick a model that fits your memory and use the local API from your own code.</description><pubDate>Sun, 18 Oct 2026 04:47:00 GMT</pubDate><category>Local &amp; On-device AI</category><category>local-ai</category><category>ollama</category><category>open-weights</category><category>privacy</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>Quantization explained: how big AI models run on small hardware</title><link>https://thelatentdaily.com/guides/quantization-explained-running-big-models/</link><guid isPermaLink="true">https://thelatentdaily.com/guides/quantization-explained-running-big-models/</guid><description>Quantization shrinks AI models by storing weights with fewer bits. How 8-bit and 4-bit formats work, GGUF, GPTQ and AWQ, and the quality trade-offs to expect.</description><pubDate>Sun, 18 Oct 2026 04:46:00 GMT</pubDate><category>Local &amp; On-device AI</category><category>quantization</category><category>local-ai</category><category>inference</category><category>explainer</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>How LLM inference serving works: batching, KV cache and vLLM</title><link>https://thelatentdaily.com/guides/how-llm-inference-serving-works-vllm/</link><guid isPermaLink="true">https://thelatentdaily.com/guides/how-llm-inference-serving-works-vllm/</guid><description>What happens when a server answers thousands of LLM requests: prefill and decode, the KV cache, continuous batching, PagedAttention and the metrics that matter.</description><pubDate>Sun, 18 Oct 2026 04:45:00 GMT</pubDate><category>MLOps &amp; Infrastructure</category><category>inference</category><category>vllm</category><category>mlops</category><category>gpus</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>How much GPU memory does an AI model need? A sizing guide</title><link>https://thelatentdaily.com/guides/gpu-memory-sizing-for-llms/</link><guid isPermaLink="true">https://thelatentdaily.com/guides/gpu-memory-sizing-for-llms/</guid><description>Estimate the GPU memory needed to run or fine-tune a language model: weights, KV cache, activations and overhead, with worked examples for 8B and 70B models.</description><pubDate>Sun, 18 Oct 2026 04:44:00 GMT</pubDate><category>MLOps &amp; Infrastructure</category><category>gpus</category><category>mlops</category><category>inference</category><category>sizing</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>How to build an evaluation set for an LLM application</title><link>https://thelatentdaily.com/guides/how-to-build-an-evaluation-set-for-llm-apps/</link><guid isPermaLink="true">https://thelatentdaily.com/guides/how-to-build-an-evaluation-set-for-llm-apps/</guid><description>The most important tool in AI engineering: how to collect test cases, define success criteria, score outputs automatically and by hand, and run evals on every change.</description><pubDate>Sun, 18 Oct 2026 04:43:00 GMT</pubDate><category>Evals &amp; Observability</category><category>evals</category><category>testing</category><category>developers</category><category>quality</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>LLM-as-a-judge explained: using AI models to grade AI output</title><link>https://thelatentdaily.com/articles/llm-as-a-judge-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/llm-as-a-judge-explained/</guid><description>Language models can score other models&apos; answers at scale. How LLM-as-a-judge works, its known biases, and how to design rubrics and checks that make it reliable.</description><pubDate>Sun, 18 Oct 2026 04:42:00 GMT</pubDate><category>Evals &amp; Observability</category><category>evals</category><category>llm-as-a-judge</category><category>testing</category><category>research</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>10 open-source AI projects every developer should know</title><link>https://thelatentdaily.com/articles/open-source-ai-projects-every-developer-should-know/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/open-source-ai-projects-every-developer-should-know/</guid><description>From Hugging Face Transformers to llama.cpp, vLLM, Ollama, LangChain and ComfyUI: the open-source projects that form the backbone of today&apos;s AI development.</description><pubDate>Sun, 18 Oct 2026 04:41:00 GMT</pubDate><category>Open-source Projects of the Week</category><category>open-source</category><category>developers</category><category>tools</category><category>github</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>How to evaluate an open-source AI project before you depend on it</title><link>https://thelatentdaily.com/articles/how-to-evaluate-open-source-ai-project/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/how-to-evaluate-open-source-ai-project/</guid><description>Stars aren&apos;t enough. Check maintenance, community, license, security, documentation and governance before building on an open-source AI library or model.</description><pubDate>Sun, 18 Oct 2026 04:40:00 GMT</pubDate><category>Open-source Projects of the Week</category><category>open-source</category><category>security</category><category>developers</category><category>due-diligence</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>What is an NPU? AI PCs and on-device AI explained</title><link>https://thelatentdaily.com/articles/what-is-an-npu-ai-pcs-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/what-is-an-npu-ai-pcs-explained/</guid><description>Neural processing units let laptops and phones run AI locally. What NPUs do, what &quot;40 TOPS&quot; means, which features use them and whether you need an AI PC.</description><pubDate>Sun, 18 Oct 2026 04:35:00 GMT</pubDate><category>AI PCs, Phones &amp; Devices</category><category>npu</category><category>ai-pc</category><category>devices</category><category>on-device-ai</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>Prompt injection and LLM security: the risks every AI app must handle</title><link>https://thelatentdaily.com/articles/prompt-injection-and-llm-security-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/prompt-injection-and-llm-security-explained/</guid><description>Prompt injection, data leakage, insecure tool use and model supply-chain risks explained with the OWASP Top 10 for LLM applications and practical defenses.</description><pubDate>Sun, 18 Oct 2026 04:24:00 GMT</pubDate><category>Privacy &amp; Security</category><category>security</category><category>prompt-injection</category><category>owasp</category><category>developers</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>AI NPCs and procedural worlds: how games are becoming generative</title><link>https://thelatentdaily.com/articles/ai-npcs-and-procedural-worlds-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/ai-npcs-and-procedural-worlds-explained/</guid><description>How language models power conversational game characters, how procedural generation creates worlds, and the design, cost and safety challenges studios face.</description><pubDate>Sun, 18 Oct 2026 03:53:00 GMT</pubDate><category>Gaming</category><category>gaming</category><category>npcs</category><category>procedural-generation</category><category>agents</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>How AI is used in telecom networks</title><link>https://thelatentdaily.com/articles/how-ai-is-used-in-telecom-networks/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/how-ai-is-used-in-telecom-networks/</guid><description>Self-optimizing networks, energy savings, predictive maintenance, fraud and spam detection, customer care and AI-RAN: how telecom operators use AI, and what 6G may bring.</description><pubDate>Sun, 18 Oct 2026 03:16:00 GMT</pubDate><category>Telecom</category><category>telecom</category><category>5g</category><category>networks</category><category>infrastructure</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>How to contribute to open-source AI projects</title><link>https://thelatentdaily.com/articles/how-to-contribute-to-open-source-ai/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/how-to-contribute-to-open-source-ai/</guid><description>A step-by-step guide to contributing to open-source AI: finding a project, starting with docs and issues, making pull requests, and sharing models or datasets.</description><pubDate>Sun, 18 Oct 2026 02:59:00 GMT</pubDate><category>Communities</category><category>open-source</category><category>github</category><category>contributing</category><category>how-to</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>Paper of the day: Direct Preference Optimization (DPO), explained</title><link>https://thelatentdaily.com/research/direct-preference-optimization-dpo-paper-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/research/direct-preference-optimization-dpo-paper-explained/</guid><description>DPO showed language models can be aligned to human preferences without a separate reward model or reinforcement learning. How it works and why it spread so fast.</description><pubDate>Sun, 18 Oct 2026 02:54:00 GMT</pubDate><category>Paper of the Day</category><category>research</category><category>dpo</category><category>alignment</category><category>rlhf</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>Quick take: bigger context windows are not always better</title><link>https://thelatentdaily.com/articles/quick-take-bigger-context-windows-are-not-always-better/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/quick-take-bigger-context-windows-are-not-always-better/</guid><description>Models now accept huge inputs, but stuffing everything into the prompt can reduce accuracy and raise costs. When long context helps, and when retrieval works better.</description><pubDate>Sun, 18 Oct 2026 02:47:00 GMT</pubDate><category>Quick Take</category><category>context-window</category><category>rag</category><category>long-context</category><category>opinion</category><author>dario_admin@resolvia-crm.tech</author></item></channel></rss>