Why PostHog started with an MCP server before building a custom AI agent
Lessons from two years at PostHog: validate agent demand by exposing a narrow, authenticated MCP server (34% of AI-created dashboards used it) before building a full agent.
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Lessons from two years at PostHog: validate agent demand by exposing a narrow, authenticated MCP server (34% of AI-created dashboards used it) before building a full agent.
Deploy AI agents with one command into isolated Firecracker microVMs that snapshot and resume. Test via Slack or webhook, verify network policies and persistent agent state.
Todd McKinnon says treat AI agents like users. This post gives three quick controls—unique service IDs, least privilege, short-lived tokens—and a 90-minute checklist.
OpenRouter lists Hunter Alpha as a 1T-parameter model with a 1,048,576-token context. Prompts and completions are logged - read how this affects cost, privacy, and operations.
Flightplanner makes short, human-readable product specs the canonical source for end-to-end checks, reducing brittle test upkeep as AI agents raise integration churn.
Practical walkthrough of Vizit, an open-source AI-agentic framework for creating reproducible visualizations. Clone the repo, run examples, save specs and rendered images.
Build agent workflows that separate fetch, intent extraction, decision, and action; record provenance, gate capabilities, and require human confirmation to curb prompt-injection risks.
Snyk reports TeamPCP prepared five days then ran a roughly three-hour compromise of the Python package LiteLLM. Prioritize CI logs and any builds from 19–24 March.
Self-hostable LaunchStack (PDR AI) centralizes PRDs, onboarding, marketing and legal docs into a searchable, citeable workspace with role-based reviews and page-level retrieval.
Nanonets' IDP Leaderboard tests 16 models on 9,000+ real documents across three benchmarks (messy OCR, layout, business extraction), revealing task-dependent rankings and cost trade-offs.
Step-by-step prototype to run multiple LLMs in parallel, use token-level confidence (logprobs/entropy) to weight and stitch outputs, and reproduce Sup AI's HLE gain (52.15% vs 44.74%).
Sen. Adam Schiff is drafting legislation to turn Anthropic-style voluntary limits into law—seeking human final authority over life-or-death AI and curbs on mass domestic surveillance.