Edition 2026.08
The Canon of Recommendation Design.
The open description of how the practice is run: the loop, the roles, the rules, and the working vocabulary, kept current as the models change. Follow the method on one brand this week and you're practicing.
Last verified: August 9, 2026
You cannot optimise what you cannot see.The principle
Why this demands a discipline, and why today
Search engines rank documents. AI engines construct recommendations. The playbooks built for the first barely touch the second: SEO metrics explain only 4 to 7% of why AI cites a page.
And the surface moves. In 2026, ChatGPT's citation volume fell up to 90% and recovered inside eight weeks. A snapshot cannot see that. A quarterly audit cannot see that. Only a running practice can.
The answer about your brand already exists, and it is being revised whether you watch or not. The discipline is how you watch, and how you change it.
The values
The stance every rule descends from
Recommendationoverranking
The unit of work is what AI says about you, not where a page ranks.
Specificityovervolume
One well-decoded gap closed beats ten pieces of general content.
Observationoverassumption
You cannot infer what the model weighs; you watch what it produces and work backward.
Transparencyoverpositioning
Evidence that survives the judge is checkable, dated, and named.
Continuousoverepisodic
Run the loop once and stop, and you did an audit, not the discipline.
The heartbeat
Every engagement runs the same loop.
Observe
Run the buyer's actual questions across the engines the buyer uses. Capture the recommendation verbatim: the brands named, the reasoning offered, the risks flagged.
Observe across all five stages of the decision journey, from consideration to advocacy. One stage is a snapshot; five is a discipline.
Decode
Extract the structure. What criteria produced this list? What cut brands from it? What is the model treating as fact that is not fact?
The four facets are the parser: elimination triggers, buyer risks, switching hesitations, criteria gaps. Decoding turns a paragraph of AI output into gaps you can close.
Seed
Publish specific evidence against a specific decoded gap. FAQ pages against elimination triggers. Methodology pages against criteria. Proof against hesitations. Then echo the claim, in the same words, on the surfaces the models cite.
The content the gap requires. More content is what the channel ignores.
The loop closes on the next Observe. If the recommendation moved, the seed worked. If it did not, the decoding was wrong, the seed was wrong, or the retrieval layer has not caught up. Each of those is diagnosable. The loop, not the seed, is the practice.
The rules
Eight rules. Written for the moments when it's tempting to skip one.
Decode before you seed
Evidence without a decoded gap is content for a channel that will not read it.
Observe all five stages
Winning consideration while losing evaluation is losing the buyer.
Fresh prompts each cycle
Yesterday's decoded criteria go stale within weeks. Rerun; never reuse.
Seed with specificity
One gap, one piece of evidence, one home, plus its echoes. Bulk dilutes trust.
Cite what AI can verify
Dated claims, named third parties, primary sources. Unverifiable is worse than silent.
Compare all four engines
Divergence between engines is a diagnostic signal, not noise. Single-engine RD is not RD.
Never gate the practice
The manual practice is complete. If a step needs a paid tool, it is not the discipline.
Record before you argue
The log holds what the model said, never what you wished it said.
The roles
Three roles. One person can hold all three.
The RD Owner
Owns the discipline across the organisation. Sets the scope and holds every team to one story, because the model reads marketing, sales, and product together, and incoherence is what it recommends against.
The Practitioner
Runs the loop end to end and owns the cadence and the observation log. The person who says "we don't seed until we've decoded." Reports movement, never volume.
The Author
Writes the seeded evidence against a specific decoded gap, on a schedule. A narrower brief than "our content marketer," and a sharper one.
Solo practitioners hold all three roles. Teams should keep them distinct: when the Practitioner and the Author blur on a large brand, the practice degenerates into content publishing that thinks it is decoding.
The cadence
Pick a rhythm you can hold. Then hold it.
Weekly is the aspiration; every fourteen days is the workable floor. Monthly is too slow: when the platform can swing 90% and recover inside eight weeks, a monthly read never sees the middle. Consistency beats frequency, because cycle-over-cycle movement is the read-out, and an irregular log is an unreadable one.
The read-out
How you know it's working, not just running
Presence
Your brand appears in the recommendation itself, not just in the citations under it.
Fidelity
The model recommends you for the reasons you intended. Recommended for the wrong reason is still a gap.
Traceability
Your seeded evidence shows up as reasoning in the answer, not just as a link at the bottom.
Velocity
Your loop is shorter than the platform's swing window, so you can tell your movement from its weather.
Coherence
Sales, product, and marketing describe the brand the same way. The RD Owner's headline metric.
Authority
Other practitioners cite your category framing. The strongest signal, and the slowest.
The boundaries
What Recommendation Design is not
It is not SEO: SEO gets you found; RD gets you chosen. It is not AEO or GEO: those treat the citation as the outcome, where RD treats the recommendation as the outcome and citation as one symptom of it.
It is not content marketing: volume is not the metric, specificity is. And it is not a tool: the discipline runs by hand, in a spreadsheet, in an afternoon, on one brand. An instrument helps when the work outgrows a person, never before.
There is no certification and no gate.
Run the loop on one brand and you're practicing. The toolkit gives you the first cycle: a worksheet to bound your scope and three prompts to run the first Observe and Decode today.
Try it on your own brand today
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The full practice, with the prompts and worked examples, is in the book: