Pineflake

Development articles

31 articles

  • Best Code Editors Compared A group of developers working together on laptops around a shared table

    VS Code, Cursor, Zed, Neovim, JetBrains, Sublime—the honest tradeoffs, a decision table, and how to pick the editor that actually fits your work.

    Dev Tools · 2026-10-28 · 13 min read

  • Choosing an LLM for Your Use Case Laptop displaying source code beside notebooks on a desk, representing the process of evaluating models for a development task

    Choosing an LLM for your use case: define your real requirements, weigh proprietary vs open, test on your own data, and avoid picking by leaderboard.

    AI · 2026-10-10 · 9 min read

  • Best Self-Hosted Open Source Tools Close-up of Python source code displayed on a computer monitor, representing open-source developer tools

    The best self-hosted open source tools in 2026 by category: Git, automation, files, passwords, monitoring, docs—plus the real tradeoffs.

    Dev Tools · 2026-10-07 · 9 min read

  • Small vs Large Language Models Open laptop with a colorful sunset reflection on a dark surface, representing AI model computing

    Small vs large language models: the real tradeoffs in capability, cost, latency, and privacy—when a small model wins and how to decide.

    AI · 2026-09-19 · 9 min read

  • Local Development With Containers Developer working at a laptop in a bright workspace, representing local container-based development workflows

    Local development with containers: end "works on my machine," set up live-reload workflows with Docker and Compose, and avoid the pitfalls.

    Dev Tools · 2026-09-19 · 9 min read

  • Terraform Infrastructure as Code Developer writing infrastructure code on a laptop, representing Terraform configuration and infrastructure as code workflows

    Terraform infrastructure as code explained: how declarative provisioning works, the plan/apply workflow, state files, modules, and the mistakes to avoid.

    Dev Tools · 2026-09-02 · 9 min read

  • AI Inference Cost Optimization Team collaborating around a laptop in a modern office, representing the engineering decisions behind optimizing AI inference costs

    AI inference cost optimization: the biggest levers—right-sizing the model, cutting tokens, caching, batching, and API vs self-host by volume.

    AI · 2026-09-02 · 9 min read

  • Self-Hosting AI Models Developer working at a laptop in a modern workspace, representing the engineers and infrastructure behind self-hosted AI models

    Self-hosting AI models: why and when to run open models on your own infrastructure, the serving stack, the real costs, and the mistakes to avoid.

    AI · 2026-09-02 · 10 min read

  • Running LLMs Locally Laptop displaying colorful code on a desk, representing local LLM development and running models on personal hardware

    Running LLMs locally: why do it, the tools (Ollama, LM Studio), the hardware and memory that decide what you can run, quantization, and cloud tradeoffs.

    AI · 2026-08-20 · 9 min read

  • Deploying LLMs in Production Modern server racks in a data center, representing the infrastructure required to deploy and operate LLMs in production

    Deploying LLMs in production: managed API vs self-host, right-sizing your model, inference with vLLM, scaling, cost control, and safety.

    AI · 2026-08-20 · 12 min read

  • Chain of Thought Prompting Guide Open notebook and pen on a desk, representing the step-by-step reasoning and worked examples used in chain-of-thought prompting

    Chain of thought prompting guide: what it is, why it works, zero-shot vs few-shot CoT, self-consistency, when to use it, and the honest caveats.

    AI · 2026-08-11 · 9 min read

  • Prompt Engineering Techniques Close-up of code on a computer screen, representing the structured instructions and developer workflows behind prompt engineering

    Prompt engineering techniques that work: being specific, giving context, few-shot examples, structured output, decomposition, and the mistakes to avoid.

    AI · 2026-08-11 · 8 min read

  • Evaluating AI Agent Reliability Data analytics dashboard showing performance metrics and charts on a dark screen, representing systematic evaluation of AI agent reliability

    Evaluating AI agent reliability: why it's hard, what to measure, trajectory vs outcome, benchmarks and tools, and the mistakes that give false confidence.

    AI · 2026-08-04 · 9 min read

  • Multi-Agent Systems Explained View from space of a glowing network of light connecting cities across Earth, representing multiple agents communicating and coordinating across a system

    Multi-agent systems explained: what they are, why split work across agents, the common architectures, how agents coordinate, and when a single agent wins.

    AI · 2026-08-04 · 10 min read

  • Tool Use in LLMs Explained Abstract glowing light trails forming a network pattern, representing an AI language model connecting to external tools and data sources

    Tool use in LLMs explained: the limits it overcomes, the kinds of tools, the reason-act loop behind agents, how to make it reliable, and common mistakes.

    AI · 2026-08-01 · 9 min read

  • Function Calling in LLMs Tutorial Abstract glowing neural network visualization representing an AI language model processing and routing function calls

    Function calling in LLMs tutorial: how the tool-call loop works, a worked code example, writing good tool definitions, and the pitfalls to avoid.

    AI · 2026-08-01 · 9 min read

  • How Modern Technology Works Abstract dark technology visualization showing layered digital connections and data flow

    How modern technology works, explained from the ground up: bits and chips, software, the internet, security, the cloud, and AI—as layers of abstraction.

    Technology · 2026-07-14 · 15 min read

  • Containers vs Virtual Machines Abstract visualization of containerized applications and virtual environments in a modern cloud infrastructure

    Containers vs virtual machines: how each works, a side-by-side of size, speed, and isolation, when to use which, and why they're often used together.

    Dev Tools · 2026-07-06 · 8 min read

  • Kubernetes Explained Simply The control room of a ship filled with monitors and instrumentation, mirroring how Kubernetes—whose name means helmsman—orchestrates containers across a fleet of machines

    Kubernetes explained simply: what it does, desired state and pods, deployments and services, what it gives you, and whether you actually need it.

    Dev Tools · 2026-06-13 · 8 min read

  • Using Docker Compose A developer working across multiple screens in a dark office, reflecting the orchestration of multiple services that Docker Compose manages from a single file

    Using Docker Compose: define a multi-container app in one YAML file, the essential commands, how services connect, and the mistakes to avoid.

    Dev Tools · 2026-06-13 · 8 min read

  • Docker for Beginners Stacks of colorful shipping containers at a port under a blue sky, mirroring Docker's own container metaphor for portable, self-contained software

    Docker for beginners: what containers are, images vs containers, the essential commands, writing your first Dockerfile, and best practices.

    Dev Tools · 2026-06-12 · 11 min read

  • Database Migration Tools Compared Close-up of a server rack with cables and cooling fans, representing database infrastructure and migration management

    Database migration tools compared: Flyway, Liquibase, Atlas, Prisma, Drizzle and more—versioned vs declarative, rollback safety, and how to choose.

    Dev Tools · 2026-06-03 · 9 min read

  • Feature Flags Explained Colorful syntax-highlighted HTML and CSS code on a dark monitor, representing software development and feature flag implementation

    Feature flags explained: how toggles decouple deploy from release, the four flag types, real use cases, tooling, and how to avoid flag debt.

    Dev Tools · 2026-06-03 · 8 min read

  • How HTTPS Works A padlock symbolizing HTTPS encryption and a secure, authenticated web connection

    How HTTPS works, explained: the TLS handshake step by step, symmetric vs asymmetric encryption, certificates, and what it doesn't protect.

    Technology · 2026-06-02 · 9 min read

  • Evaluating RAG Quality Analytics dashboard charts representing evaluation metrics

    Evaluating RAG quality with the metrics that matter: retrieval vs generation scores, RAGAS, the RAG Triad, LLM-as-judge, and catching regressions.

    AI · 2026-06-02 · 9 min read

  • Reducing Hallucinations with RAG Abstract neural network representing an AI model grounded in facts

    How reducing hallucinations with RAG actually works: grounding, where it fails, the techniques that lower the rate, and how to measure faithfulness.

    AI · 2026-06-02 · 8 min read

  • Reranking Retrieval Results Sorted data visualization representing reordered search results

    How reranking retrieval results sharpens RAG: cross-encoders vs bi-encoders, the two-stage pipeline, top reranker models, latency, and tuning.

    AI · 2026-06-02 · 9 min read

  • Chunking Strategies for RAG Lines of code on a screen representing text being segmented into chunks

    Chunking strategies for RAG compared: fixed, recursive, semantic, and contextual methods, plus chunk size, overlap, and the mistakes to avoid.

    AI · 2026-06-02 · 9 min read

  • Embeddings Explained Abstract geometric points in space representing vectors in high-dimensional space

    Embeddings explained for developers: what vector embeddings are, how models learn them, how similarity works, and how to choose a model for RAG.

    AI · 2026-06-01 · 10 min read

  • Best Vector Databases for RAG Rows of database servers representing vector storage infrastructure

    Compare the best vector databases for RAG—Pinecone, Weaviate, Qdrant, Milvus, Chroma, pgvector, and Turbopuffer—on hosting, hybrid search, and cost.

    AI · 2026-06-01 · 11 min read

  • Retrieval Augmented Generation Explained Abstract visualization of connected data nodes representing a retrieval system

    A developer's guide to retrieval augmented generation: how RAG pipelines work, the components that matter, when to use it, and how to evaluate quality.

    AI · 2026-06-01 · 13 min read