Reddit API pricing in 2026 (what you pay)
How Reddit API pricing works for free vs commercial access, and when a public-data API is cheaper for research and monitoring.
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How Reddit API pricing works for free vs commercial access, and when a public-data API is cheaper for research and monitoring.
What Twitter/X API access costs in 2026. Official credits vs a cheaper public-data API for profiles, tweets, and search.
Why stable response wrappers (request IDs, credits, typed errors) matter as much as the payload when you integrate social APIs.
Fine-tuning LLMs in 2026 costs $3-$30 in GPU time for open-weight models, or a 50% inference premium on GPT-4.1. Break-even math across three real scenarios.
Step-by-step guide to using the Twitter Analytics API for follower analysis. Extract growth, engagement, and demographic insights to optimize your strategy.
A researched map of how teams watch AI agents calling REST and general APIs in 2026: the application-layer trace platforms, the API-gateway layer where identity actually lives, and what genuine per-agent attribution requires.
Swagger Editor, SwaggerHub, Stoplight's tooling, Postman Spec Hub, Insomnia, Apidog, and Redocly all edit an API spec, but they start from different inputs and stop at different points. A researched map of each, sourced.
Instagram API rate limits in 2026 cut to 200 calls per user per hour. Learn the new rules and best practices to keep your instagram api key working.
Most style guides fail with too many rules, not too few. The work is deciding which rules stop a build, which leave a note, and which you will never enforce.
Most API doc platforms assume you already have an OpenAPI file. A researched map of what actually produces a reference doc when you don't: collection imports, AI write-ups, traffic discovery, and code-derived catalogs.
Spec-driven fuzzers, traffic-recording tools, AI request assistants, and security-focused generators all claim to "generate API tests." A researched map of what each actually generates, from what source, and what it misses.
Build a production RAG API in Node.js using pgvector: text ingestion, chunked embeddings, vector search, and source-cited answers in under 80 lines.
Spec-diff generators, docs platforms with a changelog built in, generic release-notes widgets, and git-native automation: a researched map of what actually produces an API changelog, and where each one falls short.
A researched map of how AI agents and the teams building them find and call APIs at scale outside of MCP: public marketplaces, unified-API platforms, and OpenAPI-driven agent tool generation, and where each one stops short of governing who gets to call what.
Google Search API is not free but offers 100 free queries daily. Paid plans cost $5 per 1,000 queries. Compare costs, pros, and cons to decide if it's worth it.
A precise map of the tools people reach for to keep an API contract true without hand-writing one: schema-first frameworks, code-reading generators, contract testing, and drift detection, and where each one actually stops.
Connect an existing AI agent to WhatsApp for two-way customer conversations without building and maintaining the webhook, context, and reply-delivery layer yourself.
A plain explanation of MCP servers: what the protocol does, how a server maps to your API, and what it takes to run one in production.
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