Ok friends, sharing the recipe to build basically any agent product: • Memory: learn everything useful about the user, their work, people, preferences, projects, decisions, etc. from their emails, drive, computer files etc • Context engineering: figure out which tiny subset of all that memory + current state actually belongs in the context window for the task. • Skills: teach the agent how to do the work. Build a complex DCF. Prepare a board meeting. Triage an inbox. Run customer research. Write an investment memo. • Tools / MCPs: give it access to the world. Email, calendar, Slack, GitHub, CRM, browser, databases, internal APIs, computer use, etc. • Agent runtime: the loop that plans, acts, observes, retries, delegates, checkpoints state and can keep working for hours or days. • Triggers: cron jobs + events. New email arrives. Meeting ends. Customer churns. Metric changes. Deadline approaches. The agent wakes up without being prompted. • Trust / permissions: know what it can do autonomously, what requires approval, and whose identity / permissions it is acting with. • Evals: trace everything and continuously measure whether the agent is actually getting better. Then optimize the hell out of memory quality, context selection, action quality, latency and token cost. That’s basically the agent stack. If you need more verticalization (aka finance, logistics etc. just add more MCPs and skills).