Whyproduct | Product Management Goodies

In 2025, the best product teams aren’t the fastest—they’re the ones building momentum. Here’s why your obsession with output is holding you back—and what to measure instead: medium.com/whyproduct/why… #prodmgmt #ux #startups #agile #buildbetter

Claude Code ships with 5 architectural layers most engineers never open. Not features. Not settings. Layers — each solving a distinct problem that LLMs alone can't solve. And four of them have nothing to do with prompting. Here's the full Agent Development Kit: Layer 1 — CLAUDE.md → The Memory Layer Architecture rules, naming conventions, test expectations, repo map. Always loaded. Always active. Two scopes: • ~/.claude/CLAUDE.md → global • .claude/CLAUDE.md → project This isn't context you paste in before every session. It's context that never needs repeating. The agent's constitution. Layer 2 — Skills → The Knowledge Layer Each SKILL.md carries a description. Claude matches it at runtime and forks the skill into an isolated subagent. On-demand, never always-on. Task-specific knowledge without inflating your main context window. Modular by design. Layer 3 — Hooks → The Guardrail Layer PreToolUse → PostToolUse → SessionStart → Stop → SubagentStop This is the layer most teams skip. And the one they regret skipping first. Hooks are NOT AI. They're deterministic event-driven shell commands. • Auto-lint on every Write • Hard-block on rm -rf • Slack notification on Stop Event fires → Matcher checks → Command runs Quality enforced at the infrastructure level. Not the prompt level. Layer 4 — Subagents → The Delegation Layer Each subagent gets its own context window, model, tools, and permissions. Main agent delegates down. Receives results up. That's it. No infinite recursion — subagents can't spawn subagents. Main context stays clean. Hard boundaries by design. Layer 5 — Plugins → The Distribution Layer Bundle your skills + agents + hooks + commands into a plugin. One install. Whole team inherits the behavior. Think npm packages — but for what your agent knows how to do. Wrapping everything: → MCP Servers on the left (GitHub, databases, APIs, custom integrations) → Agent Teams on the right (parallel execution, message passing, shared permissions) The 5-layer stack in one line: CLAUDE.md sets rules → Skills provide expertise → Hooks enforce quality → Subagents delegate work → Plugins distribute to the team Most production failures in agentic systems trace back to one missing layer. Which one is the gap in your current setup?

Engineers-turned-PMs destroy design relationships in predictable ways. I made every mistake for 4 years before finding the solution. The 2-minute framework that saved countless products: 👇

JUST finished the Slides for my Keynote at Northeastern's PM conference (in Boston, MA)… and decided to share all the slides. 👇 The Aspiring Product Managers Club @ Northeastern University invited me to break down product strategy in 2025. So many things have changed about strategy since the last content you read: 1. New AI prototyping tools have released 2. Annual planning gets outdated faster than ever 3. PM has become flatter, emphasizing super-IC work I wanted to create a breakdown of how to handle this. So I've spent the past week hunkered down... Collecting all the best insights. Want my slides? Shoot me a DM and reply below. I'll respond with the deck!

Awesome diagram of product risks by @PawelHuryn via @aakashgupta

@villaumbrosia It’s because we are masters of asking questions 😀

Product Managers professionals are the most bullish on AI #productmanagement

10/ Ready to apply this? Start small: 👉 Take your roadmap 👉 Map each initiative to a user & business outcome 👉 Cut anything that doesn’t drive value Your product (and users) will thank you. 🚀 What are your thoughts on this approach? Drop them below! 👇 #ProductManagement

9/ TL;DR: Product Value-Based Mapping keeps you focused on outcomes, not output. 🔹 Start with business & user value 🔹 Map initiatives to clear goals 🔹 Avoid feature-first thinking

🧵 on Product Value-Based Mapping

@salgar 💯 demoing together with engineers that build it also gives a good boost on empathy towards the builders and recognition

I've had so many days in the last couple of weeks where someone taught me something or showed me a demo, that just blew my mind and energized me for the rest of the day. In the day-to-day rush of building, I forget how incredible that is... Try to find those moments and people as often as you can.

Product management live around Ai agents 👌

If you like 🧵 like these - follow us @whyproduct for more product management goodies #product #productmgmt #pmt

7/ Bottom line: Deep PMF isn't loud; it’s quiet, habitual, and frictionless. Pay attention to subtle signals—they often reveal the real strength of your fit.

5/ PMF is dynamic. Market expectations shift over time—yesterday’s perfect fit can become today's friction. Continuously track not just satisfaction, but shifts in user expectations.