Showing 1-8 of 8
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.
Step-by-step playbook to launch one small, opt-in AI feature that lowers surprise and harm: one-line value claim, a visible failure example, limited data use, and a short pilot.
A concise guide to three AI-system failures—Input Paradox, Information Asymmetry, and token costs—and practical fixes: 3–5 field captures, progressive prompts, and token gates.
OpenAI has started testing clearly labeled ads that appear in a separate container beneath ChatGPT conversations. This brief explains the rollout, privacy and engineering implications.
Practical playbook based on Frontend Mentor's rollout: add AGENTS.md (and optional CLAUDE.md) to challenge starters, enforce via CI, and shape AI to tutor by difficulty.
Hands-on prototype: build a Cart Assistant that uses text or photo shopping lists, OCR, and user order history to prefill Uber Eats grocery carts for review before checkout.
Describes 'adversarial explanation attacks'—how LLM explanation framing keeps users trusting incorrect outputs. Reports a 205‑participant study and gives pragmatic builder controls.
Anthropic analyzed 1.5M Claude conversations and defines three disempowerment patterns—reality, belief, action. Rare by percent but meaningful at scale; includes monitoring guidance.