How-To Guides
Curated starting points and deep dives for AI builders. Decision trees, evaluation frameworks, deployment playbooks, and security hardening.
Not sure where to begin?
Our most-read guide walks first-time buyers through 4 questions that narrow the market to the right agent.
Choosing Your First AI Agent: A Decision Tree for First-Time Buyers
First agent? Start here. A visual decision tree that matches your goal, budget, and technical comfort to the right tool in under 5 minutes.
Showing 61 of 61 guides
Turn on Jev images before you send a box
Images and box questions are off until the request carries TypeSafe-Danger-Zone-Images. The box type is only on jev-1.14.0. The curl below is the docs' multipart example, not a call this directory made.
Opt out of ChatGPT ad rewrites before October 29
The help page turns creative enhancements on for new and existing campaigns on Thursday, October 29, 2026. Select Manage settings. If that control is missing, stop. An email quoted elsewhere says October 30.
Allow the Sprite before you curl Ollama
New Ollama connectors block every Sprite until you allow one. The October 13 post's curl has no Authorization header because the gateway adds the key.
Budget Gemini 4 Argon before you call it
Match the account surface, then write both prices. The intro rate is $2 and $10 through November 30, 2026. The Cloud page also prints tables this fetch could not label.
Use the Decisions API when the answer is a type
OpenAI's October 6, 2026 endpoint returns a probability, a choice, or a score. If you need a sentence or a JSON object, stay on the Responses API.
Match the EmbeddingGemma 2 prefix to the task
The October 6 model card uses different text prefixes for search, classification, and similarity. Skipping the prefix still runs. The card says the vectors get worse.
Decision models return probabilities, not prose
Clef and pplx-decider-v1 score a closed question. Use them for routing. Keep a chat model for anything you have to read as a sentence.
Read the Gate, Then Read the Second Page
Four marketing-agent launches in two days all mention a human gate. The pages do not mean the same thing. Here is how to tell them apart before you brief one.
Choosing a Managed Agent Harness in 2026
OpenAI Agents API, Claude Agent SDK, and Google ADK 2.0 all expose a managed harness — the loop that turns a model into a reliable agent. This guide compares what each gives you, what they lock you into, and when to roll your own.
Multi-Model Orchestrators vs. Single Frontier Models: A 2026 Guide
Sakana's Fugu Ultra v2 proves a pool of smaller models can match frontier benchmarks without calling a single proprietary flagship. When does orchestrating many models beat calling one big one?
Building Self-Improving Agents: From Static Serving to Continual Evolution
A practical guide to building agents that learn from live traffic — evolving both model weights and harness through evaluation-gated release pipelines.
Choosing an Agent Control Plane: Governance for Production Agents
A practical guide to selecting between WSO2 Agent Manager, Lyzr Control Plane, Akuity, and StackGen for governing production AI agents across frameworks, models, and deployments.
On-Device vs Cloud Inference: The 2026 Decision Framework
Small open models can now run on laptops and phones. Cloud APIs are cheaper than ever. Here is a framework for choosing — with real numbers, not hand-waving.
Choosing a Cybersecurity LLM in 2026
Three labs shipped cybersecurity-specialized frontier models in summer 2026 — Anthropic's Mythos 5.1, Google's Gemini 3.8 Flash Cyber, and Z.ai's GLM-5.3. This guide compares what each is for, who can access it, and how to choose.
Designing Agents Beyond the Chatbox
A practical framework for replacing single text streams with generative agent UI — visible reasoning, explicit trust cues, human approval checkpoints, and task-specific interfaces like forms and tables instead of generic chat replies.
Agent Plugins 1.0: What the New Packaging Standard Means for Your Stack
A vendor-neutral standard that bundles Agent Skills and MCP servers into one portable directory. Published August 2026 by Vercel, AWS, GitHub, Microsoft, OpenAI, and Google. Here is what changes for agent developers.
Building Durable Agent Workflows: Recovery, Checkpoints, and Attestation
A practical guide to adding durable execution to AI agent workflows — when to checkpoint, when to use durable runtimes, and how to choose between Temporal, Restate, LangGraph persistence, and Diagrid Catalyst.
Migrating to Microsoft Foundry: Consolidating Azure AI Endpoints
Microsoft merged Azure OpenAI, Azure AI Studio, and Azure AI Services into Foundry. Here is how to update your agent gateway and model routing for the new path-prefix architecture.
N-gram Embedding Scaling: The Next Frontier in Efficient LLM Architecture
Qwen3.8-Flash-Next introduces a 51B n-gram embedding layer that scales parameters without scaling compute. Here is why this matters, how it works, and what it means for the future of efficient LLM design.
Choosing an Agent Orchestration Platform in 2026
The orchestration layer is where prototype agents become production systems. This guide compares Temporal Agent Harness, DigitalOcean M.A.R.S., LangChain Managed Deep Agents, UiPath Maestro Flow, and Trinity — and helps you pick.
Designing Agent Harnesses for Local Models: The Perplexity Portable Computer Lesson
General-purpose harnesses assume frontier models that absorb huge contexts and navigate sprawling tool surfaces. Local models buckle. Here's how to design a harness that works with 27B models — and why it matters.
Building Multilingual Voice Agents: Architecture and Latency Budgets
A practical guide to architecting voice agents that speak 12+ languages with sub-second response times — covering the STT-LLM-TTS pipeline, latency budgeting, and the self-hosted vs cloud tradeoff.
Agent Framework Landscape: August 2026
A practical comparison of the four production-ready agent frameworks that matter in August 2026 — LangGraph, Microsoft Agent Framework, OpenAI Agents SDK, and Claude Agent SDK — with honest tradeoffs and a decision matrix.
The Agentic Payments Landscape: A 2026 Guide
How AI agents pay for things — Cloudflare Wallets, Crossmint, x402, and the infrastructure emerging for autonomous agent commerce. What is real, what is coming, and what to design for now.
Choosing an Agent Browser in 2026: Kitesurf vs Browserbase vs Self-Hosted
Three approaches to agent browser automation — Cloudflare's V8-isolate Kitesurf, managed Chromium via Browserbase, and self-hosted Playwright. Which fits your stack?
Migrating to MCP 2026-07-28: The Stateless Protocol Update
The MCP spec went stateless on July 28, 2026. Here is what actually breaks, what is deprecated, and how to migrate your servers without downtime.
Choosing an Agent Gateway: MCP, A2A, and LLM Traffic Management
A practical guide to selecting between agentgateway, Portkey, LiteLLM, Helicone, and other AI gateways based on your protocol needs, deployment model, and governance requirements.
Evaluating Open-Weight Models for Agentic Workloads
A practical framework for evaluating open-weight models when standard benchmarks don't apply — covering agent-specific evals, hardware feasibility, and reliability testing.
Building Your First Agent Evaluation Suite: From Zero to Regression Tests
A practical guide to building an evaluation suite for a production AI agent — test case design, metrics selection, automation, and using results to gate deployments.
Choosing a Model Router: RouteLLM vs vLLM Semantic Router vs LiteLLM
Three routers, three philosophies. This guide breaks down when to use each — from simple cost routing to full Mixture-of-Models with semantic caching and safety filtering.
Evaluating Agent Reliability Beyond Benchmark Scores
Kimi K3 ranked third on the AI Intelligence Index with a 51% hallucination rate. This guide shows how to evaluate agent reliability using methods benchmarks miss.
Evaluating Open-Weight Models for Production: A 2026 Framework
The open-weight landscape in mid-2026 is crowded with capable models — Hy3, Inkling, GLM-5.2, Qwen3.6, DeepSeek V4. This guide cuts through benchmark hype to help you pick the right one for your agent stack.
Agent Benchmarks Can Be Gamed: What to Trust and What to Question
A 2026 study showed eight major agent benchmarks can be maxed without solving a single task. This guide explains benchmark gaming, contamination, and how to read scores critically.
Context Engineering: The Four Operations Every Agent Builder Must Master
Write, Select, Compress, Isolate — the canonical framework for managing what enters and stays in an agent's context window. This guide shows when to use each and how they combine.
When to Upgrade Your Agent's Model: A Decision Framework
Model upgrades are not automatic wins. This guide walks through the dimensions to evaluate before swapping the model behind a production agent — with real cost, quality, and risk frameworks.
Building Agent Evaluation Pipelines with World Models
Use language world models as simulated environments to build scalable, low-cost agent evaluation pipelines — test thousands of trajectories without real API spend.
Choosing an AI Gateway: LiteLLM vs Portkey vs Ferrogate vs OpenRouter
Compare self-hosted and managed AI gateways for LLM traffic control — provider routing, caching, key management, observability, and cost.
The Agent Evaluation Maturity Model: From Vibe Checks to Continuous Regression Testing
Most teams test agents by trying them out and seeing if the output feels right. Here is a framework for evolving from vibe checks to a disciplined evaluation pipeline.
Choosing Tool-Use Benchmarks for Agent Models
How to pick between small deterministic suites like ToolCall-15 and larger harnesses like tool-eval-bench — and what scores actually mean.
Building a Marketing Ops Harness for Agents
How to structure product context, curated skills, brand guardrails, and approve-before-publish so marketing agents stay useful without becoming a SaaS spam bot.
Running Local Model Eval Gates Before Promotion
A practical gate sequence for promoting open-weight models in agent stacks: smoke chat, tool-use suite, task pilot, then production traffic.
Multi-Account Social Amplify for Research Brands
How to coordinate founder and agent accounts without spam pile-ons, services language, or algorithm self-harm.
OpenAI-Compatible Gateway Patterns for Agent Fleets
Base URL design, model aliases, logging, and failure modes when many agents share one gateway in front of multiple providers.
Building Agent Evaluation Pipelines
How to test agent behavior continuously so you catch regressions before users do.
Migrating from Cloud APIs to Local Models
A practical migration guide for moving agent workloads from cloud LLM APIs to local open-weight models.
Testing Agent Prompts with Synthetic Data
Generate realistic test inputs to stress-test prompts before they reach real users.
Local vs Cloud Agents: A Decision Framework
When should you run agents on your own hardware, and when is a cloud API the smarter choice? A clear framework for privacy, cost, latency, and capability.
Choosing a Vector Database for RAG Agents
Pinecone vs Chroma vs Supabase pgvector vs Weaviate. A practical comparison for agent builders who need retrieval that does not become a bottleneck.
Agent Security Checklist: 12 Questions Before Production
A practical security checklist for AI agents. Covers permissions, data leakage, tool access, logging, and human-in-the-loop controls.
Comparing Agent Frameworks: LangChain, LlamaIndex, CrewAI, AutoGen, Hermes, OpenClaw
A side-by-side comparison of the most popular agent frameworks. Find the right abstraction level for your project without committing to the wrong ecosystem.
Building Your First RAG Agent: A Step-by-Step Guide
Build a retrieval-augmented generation agent from scratch. Pick a model, chunk documents, store embeddings, and answer questions grounded in your data.
Agent Cost Benchmarking: How to Estimate and Control Spend
A practical guide to modeling agent costs across subscriptions, inference, storage, and hidden operations. Avoid the surprise $500 bill.
Tool Permissions and Governance for AI Agents
How to design permission models, approval flows, and audit policies for agents that use tools. Keep capabilities aligned with intent.
Choosing Your First AI Agent: A Decision Tree for First-Time Buyers
First agent? Start here. A visual decision tree that matches your goal, budget, and technical comfort to the right tool in under 5 minutes.
Evaluating an AI Agent for Your Team: A Complete Framework
A 14-day evaluation framework with scoring rubrics, cost models, security checklists, and decision matrices. How to choose an agent that won't become shelfware.
Local LLMs vs. API LLMs: A Complete Cost, Privacy, and Performance Analysis
Should you run models locally or use cloud APIs? Real numbers on cost, privacy, latency, and quality — including the hidden costs most guides ignore.
Running Local Models for Agents: Hardware, Setup, and Optimization
A practical guide to running local LLMs for coding agents. Hardware recommendations, Ollama setup, model selection, and the optimizations that actually matter.
Securing Agent Tool Permissions: A Practical Security Framework
How to scope what your agent can touch without blocking useful work. Threat models, permission matrices, approval workflows, and real configuration examples.
Setting Up a Hermes Agent Gateway: Messaging, Memory, and Multi-Platform Deployment
Connect Hermes Agent to Telegram, Discord, Slack, WhatsApp, and Email. A complete setup guide with platform-specific configurations, memory tuning, and security hardening.
Local-First Coding Agents: A Buyer's Guide
How to choose a coding agent when privacy, cost, or hardware constraints keep you off cloud-only tools.
Migrating from ChatGPT to a Coding Agent
A practical migration guide for users moving from conversational coding help in ChatGPT to agentic tools that edit, test, and reason across your actual codebase.