The Moat Machine: I Wrote About Product Strategy in 2022. In 2026 I Built the AI Plugin That Runs It.

Ani Ganti — Thu, 17 Sep 2026 13:15:38 +0000

You're in a leadership review. Someone points at your polished strategy deck and asks the question that turns it into wet paper:

"What's our moat?"

If your answer is an adjective (sticky, delightful, "AI-powered"), you don't have a strategy. You have a slide.

I know that room. In December 2022 I published a UX Collective article on a systematic way to develop and socialize product strategy. Six steps. Rumelt's strategy kernel. VRIO for pillars. Diagnosis through communication.

It got 52 claps. I was happy about that.

Then I went back to work and spent the next three years doing product strategy the same way I always had: a Google Doc, fifteen tabs, and somewhere between four and eight hours I didn't really have.

I knew the frameworks well enough to write about them. Knowledge wasn't the bottleneck. Running them was.

Faster docs aren't the hard part

Most AI-for-PM tools stop at generating a PRD. Useful when you need draft speed. Less useful when the review room wants defensibility.

The work that makes a draft survive that room looks like this:

Researching competitors without drowning in fifteen tabs
Scoring capabilities on Value, Rarity, Imitability, and Organization (honestly, not the aspirational version)
Assessing defensibility across real moat types (network effects, switching costs, data advantages, ecosystem lock-in) instead of the buzzword that looks best on a slide
Stress-testing a launch before the launch stress-tests you

Done properly, this takes hours. Done quickly, it produces analysis that dies on the first hard question. So most of the time it doesn't get done, and the roadmap keeps shipping features that never compound into advantage.

I wanted something that actually ran the frameworks in 2026, not another essay summarizing them.

From article to plugin

The 2022 piece, The systematic approach to developing and socializing product strategy, was a field guide. Useful on paper. Still slow in practice. Knowing Rumelt's Why / What / How does not magically create an afternoon where you can run VRIO without interruptions.

In 2026 I shipped what that article implied: an interactive AI workflow that runs the frameworks.

Write-up: I wrote about product strategy in 6 steps in 2022. I just built an AI that runs it.

Repo: aniganti/pm-superpowers

What PM Superpowers is

PM Superpowers is a Claude Code / Cursor plugin: skills, one sub-agent, and a shared library of named strategy frameworks. It triggers in conversation. You do not copy-paste a mega-prompt from a Notion doc you'll forget to open.

One thing up front: this is not a PRD generator. Faster docs are easy. Defensible strategy is scarce. If you need a PRD template, use a PRD template. This plugin is for advantage, defensibility, and strategy communication. It structures the interview; you still own the calls. You get ratings and evidence prompts, not invented market-share charts.

In practice it feels like a strategy-minded chief of staff who has read VRIO, aggregation theory, and every pre-mortem write-up, then asks the next hard question instead of dumping a wall of text. The AI interviews you along the framework's actual dimensions. It does not freestyle a plausible-sounding essay.

The moat machine

Said plainly: answer "what's our moat?" in minutes.

The strategic-moat skill walks you through eight moat types, asks for evidence (not vibes), rates strength, and surfaces deepening opportunities. You're pushed to name what product behavior, data, or user dynamics support each rating, and where the moat is thin.

You leave with a moat profile you can defend: strongest moats, weakest moats, deepening moves, and a defensibility verdict grounded in your product. Not a generic essay about "network effects in tech."

That's the moat machine. A session you can run before the next strategy review, not a slogan.

`/strategy` (the six-step session)

/strategy is the orchestrator from the 2022 framework, now interactive:

Market analysis. Context, stage, constraints worth naming
Problem space. The diagnosis, not the feature wishlist
Strategic pillars via VRIO. Sustained advantage, not workshop themes
Design and technical alignment. Constraints and risks early
Vision, mission, goals. Direction tied to pillars
Communication planning. How this lands with the people who must buy in

Grounded in Rumelt's Why / What / How. The AI interviews you. You don't freestyle into a slide deck and call it strategy. Artifacts land in structured docs you can revisit, instead of chat scroll you'll never find again.

VRIO, without the self-grading curve

Standalone vrio-analysis applies the decision tree to concrete capabilities:

Valuable? If no → disadvantage. Stop.
Rare? If no parity.
Inimitable? If no → temporary advantage.
Organized to capture value? If no → unused advantage.
Yes across the board → sustained competitive advantage.

Most teams skip a gate and still call it a pillar. The skill makes skipping awkward. That's intentional.

Competitive sub-agent

Moat analysis without competitive intel is fan fiction.

The competitive-researcher sub-agent gathers competitive intelligence via web research so competitive-landscape isn't "please paste everything you know about competitors." You review the synthesis. You don't become a tab farmer. That landscape then feeds VRIO and moat instead of living in a separate deck nobody opens.

How the pieces chain

Recommended full strategy pipeline:

competitive-landscape → vrio-analysis  strategic-moat  strategy → pre-mortem

External landscape → internal capabilities → defensibility → synthesized strategy launch stress-test.

That's the design intent: workflow-chained, not isolated prompts. Decisions can be logged with reasoning and alternatives. stakeholder-alignment turns artifacts into briefings and FAQs for specific audiences. verification quality-gates an artifact before you paste it into a QBR.

Also in the box: prioritization (RICE/ICE/weighted, grounded in pillars), product-ecosystem (aggregation / value chain), prompt-builder, and an interactive guide to the skills themselves.

Eleven skills. One sub-agent. Zero prompt engineering.

Install (Claude Code + Cursor)

Claude Code

claude plugin marketplace add aniganti/pm-superpowers
claude plugin install pm-superpowers

Then run /strategy, or ask something like "how defensible is this product?" or "help me prioritize my backlog."

Cursor

Install PM Superpowers from the Cursor marketplace (Plugins). Search pm-superpowers, install, reload if needed, and start a strategy session the same way. The public listing is powered by the same GitHub repo.

(Optional local smoke-test: copy plugins/pm-superpowers into ~/.cursor/plugins/local/ (details in the README). Prefer copying over symlinks outside that folder.)

What "good" looks like in a session

You're not looking for a longer document. You're looking for:

VRIO scores you can explain without hand-waving
Moat ratings tied to product behavior and evidence
Competitive claims that cite something other than "I think"
Strategic pillars that fall out of advantage, not sticky-note themes
A pre-mortem that names Tigers, Paper Tigers, and Elephants before ship

If your leadership asks "so what's our moat?" you should be able to answer in minutes, with structure. Not schedule a follow-up doc.

Star the repo if this is useful

If you build product strategy for a living, or you've always wanted to run VRIO properly and never had the afternoon, try it and star the repo so other PMs can find it:

https://github.com/aniganti/pm-superpowers (47 ★)

I'd especially like feedback from PMs who've run these frameworks by hand (you know where the pain is), and from builders who want AI-for-PM to mean better thinking rather than faster PRDs.

I still don't know how much of strategy work should stay stubbornly human. The interview has to be yours. The judgment has to be yours. What I do know is that the Google Doc + fifteen tabs version was costing me afternoons I didn't have, and this plugin is the version I wish I'd had in 2023.

DEV Community: Ani Ganti