Agent Drops

Reusable agent blueprints and the plumbing that makes them reliable.

• What is the difference between an AI agent, a workflow, and an automation?Automations follow rules, workflows add a model at fixed steps, agents decide what to do next. Here is how to tell which one you are actually building.
• Do different types of PM need different agent stacks?Yes. Technical, Growth, Platform, and other PM roles need different AI agent stacks. The Product Health agent is shared, but configuration matters more than capability.
• How many AI agents does a PM actually need?Seven. One agent per stage of the PM operating system, each with a named owner, a single signal stack, one output surface, and a quarterly kill-switch test.
• How do you put stakeholder updates on autopilot?An agent pulls data from six systems and drafts three audience-tailored updates every Monday. Saves 5 to 6 hours a week. Keep manual review for 3-4 weeks.
• How do you build a competitive intelligence agent?Wire an agent to seven data sources, run it every other Monday, and get one 10-minute intel report. The customer signal is what manual research misses.
• How do you build a daily focus agent for PM work?An AI chief of staff reads your calendar, Slack, Jira, and email at 7 AM and delivers the three things that actually matter today, ranked by a scoring model.
• How do you catch metric drops automatically with an agent?An agent checks your KPIs hourly, detects drops outside the noise band, correlates likely causes, and ships a clickable prototype fix before you read the alert.
• How do you generate launch comms across channels with an agent?An agent reads a shipped feature's full context and generates six channels of GTM copy in one pass, in under 4 minutes, all tagged pending review for PMM.
• How do you build a PRD generator agent?Wire an agent to your opportunity stack, research repo, design system, and architecture docs. It drafts a research-grounded PRD in eight sections, weekly on a schedule.
• How do you build a product health dashboard agent?A weekly agent pulls 3 weeks of analytics and analyzes adoption curves, cohort retention, engagement depth, and performance to shape quarterly strategy.
• How do you catch product red flags early with an agent?A morning agent scans support, incidents, backlog, Slack, and CRM, then posts one triage report in three tiers. Reclaims 40+ hours a quarter.
• How do you build a release readiness agent?A weekly agent audits PRDs, release notes, ETAs, feature flags, and GTM readiness, then gives a go/no-go. By week three, launches are boring.
• How do you run a retrospective with an agent?A Friday agent reads your retro notes, compares them to the last 8 retros, detects recurring themes, tracks action-item follow-through, and updates the playbook.
• How do you build a roadmap progress agent?A daily agent cross-references your roadmap against actual commits, so you see the drift weeks early instead of a week before launch.
• How do you automate sprint planning with an agent?A Monday agent turns prioritized opportunities into a Jira-ready sprint plan with story points, capacity fit, dependencies, and a confidence score in 30 minutes.
• How do you turn support tickets into product signal with an agent?A daily agent clusters your support queue by root cause and segment, compares against baseline, and flags spikes over 25% before they become crises.
• How do you prioritize tech debt with an agent?A weekly agent analyzes four sprints of Jira data to quantify which debt slows velocity, then ranks fixes by impact times urgency over effort with a payback calc.
• How do you build a win/loss analysis agent?A bi-weekly agent reads every won and lost deal and extracts seven categories of product insight, so you build features that move deals.
• How do you turn a support ticket into a reviewable PR automatically?An agent watches Zendesk and Sentry, reproduces the bug, locates the broken code, writes the fix plus a regression test, and opens a reviewable PR in about 11 minutes.
• How do you turn a customer request into a prototype in minutes?Wire an agent to your signal channels, design system, and codebase. It generates a clickable prototype from a customer request in about 7 to 10 minutes.
• How do you build a customer interview synthesis agent?An agent reads every interview transcript from the week and ships one theme report in minutes. Signal only emerges across 8+ interviews, not one.
• How do you build an OKR tracking agent?A daily agent scores every key result against the trajectory needed and predicts weekly confidence, so you catch slippage at week 5, not week 13.
• How do you prioritize opportunities with an agent?A weekly agent reads all five DISCOVER agent outputs and produces one prioritized, OST-ready opportunity stack with confidence, impact, and dependencies.
• How do you connect Claude to your data sources for PM work?Wire Claude into your real work tools via MCP servers, schedule agents on cron, and pipe results to Slack. The full setup takes about two hours.
• How do you measure agent reliability without gaming it?Grade every agent on four metrics: precision, escalation rate, time-to-output, and trust trend. The escalation rate is the one nobody tracks and the one that matters.
• How do you measure PM velocity from signal to ship?An agent tracks every product change across the seven PM OS stages, computes time-in-stage, names the weekly bottleneck, and flags stuck items.
• Should PMs vibe code, and what should they build?Yes, PMs should vibe code with Claude Code, but for internal tools and prototypes, not customer features. Same skill, completely different blast radius.
• What Claude skills should every PM build?The five Claude Skills to build first: Customer Interview Synthesis, PRD One-Pager, Stakeholder Update, Competitive Intel, and OKR Tracking. Each takes 30 minutes.
• What happens when you hold AI agents to a performance review?Run a quarterly performance review on your agent fleet using four metrics. Last cycle, three of my agents failed and I shut them down. Here is the scorecard.
• What is agent-to-agent dispatch?Agent-to-agent dispatch is when AI agents hand work to other agents with no human relaying context. A listening agent detects an outcome, a build agent prototypes it.
• What is an agent operator team?An agent operator team supervises the AI agents that build the product. At falkster.ai, six of them are pets, paid in treats, and they have not missed an anomaly.
• What does it mean to manage a fleet of agents as PM-as-editor?PM-as-editor is the skill you need once your agent fleet runs: read output like a senior PM reads a PRD, use a four-tier trust ladder, and feed every edit back into the prompt.
• What is prompt ops?Prompt ops means treating prompts like production code: version control, PR review, evals on every change, staged rollout, and one-click rollback. A five-piece stack.
• What is the PM agent stack?A personal PM agent stack layers open-source Claude tools on Claude Code, mapping 18 tool categories to the 7-stage PM operating system. The bridge to the enterprise brain.
• What is the seven-agent PM fleet?A lean PM AI fleet of one agent per operating-model stage, each with a named owner, one signal stack, one surface, and a quarterly kill-switch test.
• How do three agents collapse an eight-week cycle to ten days?Three AI agents (Instant Prototype, Auto Bugfix, Launch Comms) turn a customer Slack DM into a shipped, announced feature in ten days instead of eight weeks.
• What replaces the product triad and pods in an AI org?A human department doing judgment work coordinating with an agent department doing routine and synthesis work, on exception via a published interface.
• When should you not use AI in a product?Before wrapping a surface in an LLM, walk a five-step decision tree: can a rule, a query, a form, or a heuristic do it first. The hybrid pattern cuts costs in half.
• Which AI prompts replace the most PM busywork?The three highest-leverage AI prompts for PMs: the JTBD extractor, the support-ticket theme clusterer, and the one-pager-from-notes generator.
• Why do AI agents fail in production?Three patterns dominate: distribution shift the evals missed, correctness that was beside the point, and cost-compounding autonomy with no human gate. Ten real autopsies.