Category
Product
- ·3 min read
Running Discovery Sessions: Recruiting, Outreach, and No-Shows
One customer conversation a week, forever — that's the habit. This module is the operational half nobody teaches: where interviewees actually come from, the internal asks that get sales and CS to hand you conversations, outreach emails that get replies, scheduling mechanics that cut no-shows, and what to say on the call when someone demands a roadmap commitment. Templates for all of it.
- ·3 min read
Finding Opportunities: Interviews, JTBD, and the Opportunity Space
An outcome with an empty opportunity space under it is a guess wearing a metric. This module covers the craft of filling that space: story-based interviews that produce evidence instead of polite yeses, one-page interview snapshots, the Jobs to Be Done lens for keeping opportunities solution-agnostic, and how to grow a flat list of pains into a structured two-level opportunity space — shown end to end on Donut CRM.
- ·3 min read
Opportunity Solution Trees: The Shape of Good Discovery
A roadmap meeting where the loudest request wins is not prioritization — it's an auction. This module introduces the opportunity solution tree: one outcome at the root, customer needs in the middle, solutions and experiments below, so every priority argument happens on a shared picture instead of in the air. You'll leave with your own product outcome written and your last five feature requests decompressed into the needs underneath them.
- ·3 min read
Avoiding AI Slop: Writing User Stories a Team Will Actually Build
AI slop in a backlog is worse than an empty backlog, because it's plausible enough to survive triage and hollow enough to fail in sprint. The series finale: how to recognize slop in product artifacts, the grounding rules that starve it, and the user-story craft — INVEST, vertical slices, testable criteria — that matters more now that drafting is free and judgment is the bottleneck.
- ·3 min read
Commands That Write User Stories and PRDs with Real Context
A prompt you retype is a workflow you can't improve. This post turns the repo's two highest-frequency jobs — drafting user stories and drafting PRDs — into versioned command files: what context they load, what questions they must ask, what format they emit, and the guardrails that make their output reviewable instead of just plausible. Full command files included, copy-paste ready.
- ·3 min read
A TRIZ Session: How to Guarantee Your Launch Destroys the Company
A ready-to-run Liberating Structures TRIZ workshop built on the Sonos May 2024 app launch. In 45 minutes, your team designs the disaster from scratch — immovable date, big-bang rewrite, no rollback — then discovers how much of the recipe they already practice, and commits to stopping one piece of it. Full facilitation script, answer key, and debrief included.
- ·3 min read
Connecting the Tools: Tracker, Docs, and Chat Without Drowning in Integrations
The repo holds context and the tracker holds work — but your AI assistant needs to reach both in the same session, plus the docs where specs get collaborated on and the chat where decisions actually happen. This post wires it: MCP connections to Jira/Linear, Notion/Confluence, and Slack/Teams, the read/write rules that prevent a sync monster, and the permission boundaries you set before connecting anything.
- ·3 min read
The Signal Pipeline: Tickets, Calls, and CRM into One Weekly Digest
Customer evidence is the most valuable input a product team has and the worst-managed: tickets in the help desk, transcripts in the call recorder, lost reasons in the CRM, all unread past week one. This post builds the pipeline — a signal card format, a per-source extraction pass, and a one-hour weekly ritual that turns raw exhaust into evidence your stories can cite.
- ·3 min read
Designing the Context Repo: a Structure Agents and Humans Can Navigate
The difference between a context repo that compounds and one that rots is decided in the first week, by structure: small files that answer one question each, frontmatter that makes them queryable, decision records with dates, and an AGENTS.md that teaches AI tools how to read the whole thing. The complete layout, with copy-paste starter files.
- ·3 min read
The Product Context Repo: Why Your Product Knowledge Belongs in Git
Every AI tool you point at your backlog produces confident, generic garbage — not because the model is weak, but because it has never met your product. The fix isn't a better prompt. It's a repo: a plain-text, version-controlled home for everything your product knows about itself, structured so both humans and agents can read it. Part one of a six-part build-along.