MCP vs Function Calling: Which Tool Integration to Use
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.
Insights on AI agents, model routing, and building production-ready AI systems.
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.
Claude Code vs Codex vs OpenClaw compared for 2026: codebase understanding, SWE-bench scores, terminal workflow, and which terminal coding agent fits your work.
A ranked, opinionated guide to the 10 best open-source AI agent frameworks in 2026, with honest trade-offs, ideal use cases, and what each one gets wrong.
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.
How to build cron-driven AI agents that run autonomously on a schedule in 2026: the architecture, idempotency and failure handling, and the cost traps of always-on automation.
A practical guide to connecting MCP servers to your AI agent in 2026: transports, the connection lifecycle, real config, and the schema-bloat gotcha that costs you tokens.
Deep comparison of Hermes Agent and OpenClaw, the two fastest-growing open-source AI agent frameworks of 2026, covering architecture, memory, extensibility, and best use cases.
An architecture teardown of OpenClaw: the three-layer pipeline, the seven-stage agentic loop, and why a self-hosted chat gateway became one of the fastest-growing repos ever.
How to run one AI agent across Slack, Discord, and WhatsApp in 2026: the gateway pattern, session identity, per-channel quirks, and the state-sync problems nobody warns you about.