
Bilibili Creator Research API Workflow | SandBase
Build a Bilibili creator-research workflow: read trends, search a topic, and profile the creator — one SandBase key, no Bilibili login.
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Build a Bilibili creator-research workflow: read trends, search a topic, and profile the creator — one SandBase key, no Bilibili login.
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Read public Bilibili videos, search, hot search, and user profiles with one REST API. No Bilibili login, no SDK — one SandBase key, built for agents.
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Aggregate Weibo, Bilibili, and Zhihu hot lists into one trend dashboard with one REST API — one SandBase key, no logins, normalized to a shared shape.
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Monitor Douyin's high-like billboard and resolve each video to a stable aweme_id with one SandBase API key — poll the board, dedup by ID, no login, no SDK.
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Read public Douyin billboards, search, videos, and comments with one REST API. No Douyin login, no SDK — one SandBase key, built for agents.
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Read public Kuaishou hot list, search, shopping rankings, and videos with one REST API. No Kuaishou login, no SDK — one SandBase key, built for agents.
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Build a Lemon8 content-discovery workflow: search a keyword, open a post, and profile its author — one SandBase key, no Lemon8 login, no SDK.
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Read public Lemon8 search, posts, users, and topics with one REST API. No Lemon8 login, no SDK — one SandBase key, built for agent workflows.
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Read public Pinterest search results, boards, and pins with one REST API. No Pinterest login, no SDK — one SandBase key, built for agent workflows.
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Read public Pipixia hot boards, search, users, and posts with one REST API. No Pipixia login, no SDK — one SandBase key, built for agent workflows.
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Monitor Pipixia's hot boards with one REST API: read the board list, normalize items by id, and diff rank across runs — one SandBase key, no login.
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Aggregate Douyin and Kuaishou hot lists into one normalized trend feed with a single SandBase API key — read both boards, map to one schema, no login, no SDK.
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Monitor a public Telegram channel with one REST API: baseline it, poll new posts with the after_cursor, and read engagement — one SandBase key, no MTProto, no login.
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Search a public Telegram channel's history by keyword with one REST API: baseline the channel, run in-channel search, and rank matches — one SandBase key.
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Read public Telegram channels, posts, comments, and search with one REST API. No Telegram login, no MTProto client — one SandBase key, built for agents.
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Build a Threads creator-research workflow: resolve a list of handles into profile records, rank by reach, and extract bio links — one SandBase key, no login.
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Read public Threads profiles, posts, replies, and search with one REST API. No Threads login, no SDK — one SandBase key, built for agent workflows.
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Read public Toutiao authors, articles, videos, and comments with one REST API. No Toutiao login, no SDK — one SandBase key, built for agents.
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Query WeChat Search (搜一搜) for public results and videos with one REST API. No WeChat login, no SDK — one SandBase key, built for agent workflows.
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Read public Weibo hot search, posts, and user profiles with one REST API. No Weibo OAuth app, no SDK — one SandBase key, built for agent workflows.
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Build a Weibo hot-search monitoring workflow: read the board, search a topic, and profile the author — one SandBase key, no Weibo login.
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Search public Xiaohongshu (RED) notes, products, users, and images with one REST API. No RED login, no SDK — one SandBase key, built for agents.
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Build a Xiaohongshu product-research workflow: search products, read a product, and pull its reviews — one SandBase key, no RED login.
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Read public Xigua Video search, users, videos, and comments with one REST API. No Xigua login, no SDK — one SandBase key, built for agent workflows.
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Build a Xigua Video research workflow: search a keyword, read a video's detail, and pull its comments — one SandBase key, no Xigua login, no SDK.
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Read public Zhihu questions, answers, articles, hot list, and profiles with one REST API. No Zhihu login, no SDK — one SandBase key, built for agents.
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Build a Zhihu expert-discovery workflow: search users, read a profile, and pull their answers — one SandBase key, no Zhihu login.
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Build a Zhihu Q&A mining workflow: read the hot list, open a question, and pull its answers — one SandBase key, no Zhihu login.
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Read public Instagram profiles, posts, Reels, followers, comments, and hashtags with one REST API. No Instagram OAuth or SDK — one SandBase key, built for agents.
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Read public LinkedIn profiles, company pages, posts, and jobs with one REST API. No LinkedIn OAuth, no SDK — one SandBase key, built for agent workflows.
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A Reddit community monitoring API workflow: size a subreddit, discover topic conversations, and profile authors — one SandBase key, no OAuth app.
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Read public Reddit subreddits, posts, comments, user profiles, and search with one REST API. No Reddit OAuth app, no PRAW — one SandBase key, built for agents.
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Search X/Twitter and read public tweets, profiles, followers, and trends with one REST API. No X developer tier, no OAuth — one SandBase key, built for agents.
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Read public TikTok profiles, videos, comments, Creative Center trends, and shop product data with one REST API. No SDK — one SandBase key, built for agents.
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Build an X/Twitter monitoring workflow: search a topic, read a tweet's engagement, and profile its author — one SandBase key, no X developer tier, no OAuth.
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Search YouTube and read public videos, channels, comments, and captions with one REST API — one SandBase key, built for agents.
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Go from a channel name to caption tracks in four calls: resolve the channel, list videos, read video info, and discover captions — one SandBase key, no OAuth.
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What Codex Persistent Mode's public prompt establishes about follow-ups, sleep, permissions, and memory—and why code alone does not prove availability.
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WorkBuddy is a desktop AI workstation for turning natural-language tasks into files, reports, analysis, and code. Here is where it fits—and where it does not.
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A practical architecture for using WorkBuddy’s specialists and project spaces on multi-step tasks without losing provenance or control.
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A workspace-write policy can still leave a hidden route through host PIDs and /proc. See the fixed versions and a safe PID-namespace check.
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Why image-heavy agent sessions can outgrow a compaction ledger: how screenshots shift retention boundaries and what engineers need to log.
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Install the open-source SandBase CLI, connect Codex, Claude Code, Cursor, Gemini CLI, and other AI clients, and expose six MCP tools for a catalog of 2,000+ models and APIs.
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Claude Tag lets teams @mention Claude in Slack channels to delegate real work. Multiplayer, persistent memory, proactive, async. Available for Team and Enterprise.
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Gemini 3.7 Flash launches at $0.75/$3.75 per million tokens, half the cost of 3.6 Flash. 1M context, multimodal, tunable thinking, strong tool use for agents.
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SpaceXAI launches Grok Bot: AI agents with their own cloud computer, logins, and persistent state. Signs into apps like a human. Beta at $120/seat/month.
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DeepSeek Harness setup and review: npx install, plugin architecture, API limits, and what is safe to test before production.
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DeepSeek Harness vs Claude Managed Agents compared. Open-source composable plugins vs managed hosted infrastructure. Architecture, trade-offs, and when to pick each.
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DeepSeek V4 Pro 0813 exits preview quietly. 1.6T params MoE, 49B active, 1M context, priced at $0.87/M output — less than 2% of Claude Fable 5.
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Douyin User Search API tutorial with Python and cURL: search creators by keyword via SandBase /v1/run for KOL discovery, competitor monitoring, and social-data agents.
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Learn how to use the ElevenLabs Dubbing API through SandBase to automatically translate and re-voice video and audio content into 29+ languages.
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The Humanize Writing API rewrites AI-generated text to sound natural. One call, $0.01, no prompt engineering. Tutorial with code examples and real test results.
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Learn how to convert Instagram usernames to user IDs and vice versa using SandBase's unified API. Practical code examples in curl and Python for automation, analytics, and AI agent workflows.
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A practical guide for engineering teams to evaluate AI model spend — not just which model is best, but how to measure value on your workload.
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Meta announces Muse Glimmer, a 30B parameter open-weight model family designed to run on laptops and consumer devices—challenging cloud-only AI with on-device intelligence.
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A step-by-step guide to migrating your MCP server from the session-based model to the new stateless 2026-07-28 spec. Includes before/after code, checklists, and FAQ.
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Agent Plugins is a new open standard for portable AI agent plugin packages. One format, every client. Learn how plugin.json, skills, and MCP servers fit together.
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Compare the best open weights LLMs for AI agents in 2026: DeepSeek V4, openPangu-2.0-Pro, Llama 4 Maverick, cost, context, benchmarks, and self-hosting fit.
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How Cloudflare's serverless platform became the perfect deployment target for stateless MCP servers, with updated SDKs and zero-config scaling.
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Cursor vs Windsurf vs Claude Code compared in 2026. IDE integration, agent autonomy, model flexibility, multi-file editing, MCP support, and pricing — with a verdict per use case.
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How Duolingo built a shared agent platform using Temporal workflows, declarative definitions, and multi-runtime support to stop teams from rebuilding infrastructure for every agent project.
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Learn GitHub Copilot Agent Mode setup, MCP tools, permissions, pricing and runtime limits, with Microsoft Agent Framework examples for .NET and Python.
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Muse Spark 1.2 vs Claude Sonnet 5: compare coding-agent benchmarks, API pricing, subagents, speed, reliability, and which model fits your workflow.
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Google led the biggest MCP spec change since launch—removing stateful sessions entirely. Here's how the 2026-07-28 spec makes MCP cloud-native.
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AWS Bedrock AgentCore Runtime Instances guide: understand persistent EC2-backed agents, 14-day sessions, GPU support, pricing, deployment, and use cases.
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Huawei releases openPangu-2.0-Pro — a 505B parameter open-weight MoE model trained entirely on Ascend 910B NPUs. Architecture breakdown, hardware sovereignty implications, and honest assessment.
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Meta launches Muse Code, a terminal-native coding agent powered by Muse Spark 1.2. Async background agents, event-log replay, and 24-hour GPU kernel optimization sessions.
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DeepSeek V4 Flash 0731 exits preview with 82.7 Terminal-Bench and 54.4 DeepSWE. 284B/13B MoE, 1M context, MIT license, at $0.14/$0.28 per million tokens. Agent benchmarks beat V4-Pro-Preview.
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The MCP protocol dropped sessions and went stateless on July 28, 2026. What changed, why it matters for production agents, and how to migrate your servers.
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The MCP protocol gives AI agents a standard way to discover and call tools. How it works, how to build a server, and the ecosystem in 2026.
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Qwen 3.7 Max is Alibaba's flagship agent model with 1M context, SWE-Pro 60.6, and Terminal-Bench 69.7. How it compares and what it costs on SandBase.
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Qwen 3.8 Max is Alibaba's 2.4 trillion parameter multimodal flagship with 1M context, MoE architecture, and top Arena.AI rankings. Specs, pricing, and how to access it on SandBase.
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Anthropic prompt caching offers two tiers: 5-minute (1.25x write, 0.1x read) and 1-hour (1.5x write, 0.1x read). Decision guide for agent workloads.
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Ranking the top 1M-context models for agent workloads in 2026: Opus 5, Sonnet 5, Kimi K3, GPT-5.6 Sol. Scored on reasoning, speed, cost, and ecosystem.
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Best Douyin data APIs in 2026: compare services on coverage, price, reliability, sync vs async design, auth, and AI-agent developer fit.
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A tiered model recommendation for autonomous agents in 2026: which model for planning, execution, classification, and when to cascade across tiers.
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Build a social media monitoring agent using the OpenAI SDK for LLM analysis and direct HTTP requests for SandBase's social data APIs. Complete code tutorial showing the correct pattern: requests for data + OpenAI SDK for reasoning.
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China's $700B+ social commerce market represents the largest untapped opportunity for AI agents — but structured data access is the bottleneck. An industry analysis of the data landscape and agent opportunity.
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Claude Opus 5 pricing and review for 2026: 1M context, $5/M input, $25/M output, API limits, adaptive thinking, effort controls, and Opus vs Sonnet trade-offs.
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Claude Sonnet 5 is a practical 2026 starting point for many AI agents: 1M context, strong coding and reasoning, and a listed $2/$10 per MTok price. When to upgrade to Opus 5.
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Build an agent that tracks its own API spending using the Anthropic SDK on SandBase. Logs token usage per call, produces daily/weekly cost reports, and implements budget controls.
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OpenAI's GPT-5.6 splits into three families: Luna for creative work, Sol for deep reasoning, Terra for speed. Here's when to use each variant.
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GPT-5.6 and Claude 5 take different approaches to agent workloads. Speed and variants vs reasoning depth and tool reliability. Scenario-based comparison.
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Kimi K3 from Moonshot AI delivers 1M token context at competitive pricing. How it stacks up against Claude 5 and GPT-5.6 for agent workloads.
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Tutorial: Build a multimodal agent that generates images with Seedream, writes analysis code, runs it in an E2B sandbox, and produces report artifacts. Shows SandBase ecosystem composition in one workflow.
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A tutorial-style cost breakdown of RAG pipelines: embedding, search, and LLM components. Real numbers for 1M documents, optimization strategies, and when RAG beats long-context (and when it doesn't).
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A deep architectural comparison of structured API access vs web scraping for AI agents consuming social media data in 2026. When each wins, what breaks, and how to choose.
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An engineering opinion piece on why synchronous-only design is the correct default for data APIs serving AI agents. Trade-off analysis, architecture implications, and when async is actually necessary.
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Step-by-step tutorial: build an agent that tracks competitor Douyin accounts, detects new videos, and generates daily briefings for under $1/month.
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LLM API cost comparison for 2026: input/output rates, cache tiers, and real cost examples for GPT-4o, Claude, DeepSeek, Gemini, and more.
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Two pricing models dominate AI APIs. This guide explains when per-call billing beats token billing for agents, with cost comparisons across three real scenarios.
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Tutorial: build an agent that monitors Weibo hot search and Douyin trending every 15 minutes, flags brand mentions, and sends alerts via webhook.
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A practical guide to social media data APIs that AI agents can use in 2026, covering Chinese and Western platforms, pricing, and agent-readiness.
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64 Weibo and 36 Xiaohongshu data operations are now available through SandBase, covering hot search, user posts, influencer analytics, and commerce data.
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Build an agent that evaluates 200 Xiaohongshu influencers in minutes: engagement scoring, content classification, audience quality signals, all for under $6.
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Best AI search APIs for agent workflows in 2026: compare Exa, Tavily, Firecrawl, SerpAPI, Google, and Brave on search quality, crawling, cost, and developer fit.
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Exa Search is available through the SandBase ecosystem, helping agents connect AI-native semantic web search to research, monitoring, and FDE workflows.
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A practical comparison of Exa Search, Tavily, Firecrawl, SerpAPI, and Google Custom Search for AI agent workflows in 2026.
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Ranked comparison of the best AI sandboxes for agent code execution in 2026. E2B, Daytona, Blaxel, and SandBase tested on features, pricing, and production readiness.
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The 7 best MCP servers for AI agents in 2026, ranked. Composio, Zapier MCP, Arcade, Workato compared on tool count, latency, and agent compatibility.
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Pre-action authorization checks every AI agent tool call before it runs. Learn how to gate reads, writes, code execution, and loops.
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MCP execution boundaries help production AI agents use tools safely. Learn what to control after tools are connected and before loops run.
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A short SandBase product update on agent-first messaging, model registry updates, runtime examples, status visibility, and open-source agent infrastructure assets.
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A practical recap of how SandBase used 30 days to build public presence, technical content, open-source assets, and the first search visibility baseline.
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The agent runtime layer is the production infrastructure between your framework and model. Why it decides durability, isolation, and recovery.
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n8n vs Dify compared for 2026: automation-first platform with AI vs AI-first agent platform. Which to choose for building agents and workflows.
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LiteLLM vs OpenRouter: self-hosted proxy vs managed gateway. We compare pricing, failover, model coverage, and latency to help you pick the right LLM router.
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Dify vs LangGraph head-to-head comparison - visual drag-and-drop vs code-first graph orchestration. Features, performance, pricing, and which one to choose for your AI agents in 2026.
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vLLM vs SGLang (2026) comparison for LLM serving and AI agents: which is better for throughput, latency, prefix caching, OpenAI API compatibility, and deployment fit?
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A map of the 2026 AI agent infrastructure stack: inference engines, model gateways, agent frameworks, and dev environments, with the right tool for each layer.
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What Coder is, how it provides governed cloud workspaces for developers and AI agents, and why enterprise agents need this layer.
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What DeerFlow is, how ByteDance built an open-source SuperAgent harness for multi-hour tasks, and what 'harness' means for agent infrastructure in 2026.
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Dify AI explained: pricing, self-hosting, architecture, limits, and comparisons with LangGraph and n8n - plus when to use it in production.
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LangChain vs LangGraph compared for agent development in 2026. When to use chains vs graphs, state management, human-in-the-loop, and migration paths.
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LiteLLM is an open-source LLM proxy that unifies 100+ providers behind one API. Setup guide, failover, cost tracking, and when LiteLLM beats managed alternatives.
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What Mastra is, how the Gatsby team built a TypeScript-native agent framework, and why it matters for JS/TS developers building agents in 2026.
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What n8n is, how its 70+ AI nodes enable agent workflows, and when to choose it over Dify or code-first approaches for building AI automation in 2026.
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How SGLang works, why RadixAttention gives agents faster prefix reuse, and when to choose it over vLLM for production inference in 2026.
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How vLLM works under the hood, why PagedAttention matters for agent workloads, and where it fits in a production agent infrastructure stack in 2026.
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Warp 2.0 explained - how it evolved from AI terminal to agentic development environment. Run Claude Code, Codex, and Gemini CLI in parallel. Open-source in 2026.
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Claude Opus 4.7 for AI agents in 2026: SWE-bench numbers, where it wins on coding tasks, what it costs, and when to reach for a cheaper model.
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DeepSeek V4 ships a 1M-token context window under MIT at a fraction of frontier pricing. When the huge context earns its keep for agents, and when it's a trap.
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Google's Gemini 3.5 Flash trades a little reasoning depth for big wins in speed and cost. Where a fast model is right for agents, and where it hurts.
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Zhipu's GLM-5.1 took the top SWE-bench Pro spot among open-weight models in 2026. What the benchmark measures, where it fits, and how to use it.
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Moonshot's Kimi K2.6 is a 1T-parameter open-weight MoE model for agents. What it's good at, where the params help, and how to wire it into a loop.
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A head-to-head guide to open-weight LLMs for agents in 2026: Kimi K2.6, DeepSeek V4, GLM-5.1, Qwen 3.6. Which to pick for tool-use, context, or cost.
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Qwen 3.6 is Alibaba's open-source LLM that punches above its size on SWE-bench. Why a smaller, efficient model is often the smarter agent default.
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Real guardrails for AI agents in production: input validation, action allow-lists, sandboxing, cost ceilings, and human-in-the-loop. Patterns you can ship.
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Five agent design patterns for reliable, low-cost AI systems: ReAct, Plan-and-Execute, Reflection, Router, and Tool-First, with trade-offs for each.
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AI agent observability guide: instrument structured logs, distributed traces, tool spans, token cost, and replay data to debug production agents.
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AutoGen vs CrewAI tested on real multi-agent tasks. AutoGen wins on flexibility; CrewAI wins on speed-to-ship. Full architecture and cost comparison inside.
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Autonomous AI agents that run code and shell commands need isolation. Why sandboxes are non-negotiable in production, the isolation levels, and how to choose.
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A comparison of AI sandboxes for agent development in 2026: E2B, Modal, Daytona, and self-hosted options. Cold-start latency, isolation, and pricing.
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How to build a self-correcting AI agent using the reflection pattern and persistent memory. A runnable Python loop that critiques and fixes its own output.
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Build a custom MCP server that lets any AI agent run data analysis on your CSVs and databases. A complete, runnable TypeScript walkthrough.
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Claude Sonnet 4 vs GPT-4o for AI agents: tool-calling reliability, long-context behavior, cost, and latency. Which model to pick for which agent.
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A teardown of how OpenHands, the open-source AI coding agent, plans, edits files, and runs code in a sandbox: the event-stream and action-observation loop.
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MCP vs function calling for AI agents: they solve different layers of the same problem. When to use each, how they compose, and the token-cost trade-off.
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Compare the three agent memory architectures in 2026 — vector recall, knowledge graphs, and episodic buffers — with real latency numbers, failure modes, and a decision guide.
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10 best open-source AI agent frameworks ranked for 2026. LangGraph, CrewAI, AutoGen, Mastra, and more — with pros, cons, and our pick for each use case.
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Claude Code vs Codex vs OpenClaw compared for coding agents in 2026. Benchmark results, pricing, context handling, and which to pick for your codebase size.
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Step-by-step guide to connecting MCP servers to your AI agent. Setup, authentication, tool discovery, error handling, and production deployment patterns.
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How to build cron-driven AI agents that run autonomously on a schedule. Full Python code, cost analysis, retry logic, and production monitoring patterns.
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Deep comparison of Hermes Agent and OpenClaw for 2026. Architecture differences, self-improvement loops, deployment options, and when to choose each.
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How Hermes Agent self-improving loop works: architecture teardown, memory systems, evaluation cycles, and real-world performance data from production.
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Architecture teardown of OpenClaw: three-layer pipeline, code execution sandbox, memory system, and how it achieves top SWE-bench scores with diagrams.
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How to run one AI agent across Slack, Discord, and WhatsApp. Unified message handling, platform adapters, auth patterns, and deployment architecture.
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