How I run projects, in plain English. The phases, what ships when, what I need from you, and how fast each thing actually moves. Same process, same operator, every time. No account managers, no producers named Brad, no scope creep dressed up as discovery.
Whether it's an interactive tool or a full SEO and AEO program, the rhythm doesn't change. Audit first, plan second, build, ship, document. No surprises, no scope creep dressed as discovery.
Where you are, where the competition is, where the easy wins live. Honest, fast, no padding.
One-page plan with objectives, deliverables, and timeline. You say yes once, we ship.
Schema, page structure, content, decks, tools - whatever the scope. Weekly updates so you always know where it is.
Real publishing date, real measurement. Not a soft launch, not a beta. Live and tracked.
Documentation your team can actually use after I stop, plus a clear "what happens in month two" plan.
Same five-step shape, different specifics depending on what you've booked. Here's how each of the most-asked services actually runs.
The most common engagement. Designed to get you visible in Google AND inside ChatGPT, Perplexity, Claude and Google AI Overviews. Same playbook I ran on this site (117 to 8,505 AI citations a month, in seven months).
Technical SEO audit, schema validation, llms.txt check, content gap analysis. Competitor research: who's ranking for your buyer-intent queries, what AI engines are citing them for, where their content is winning and where it's lazy.
One-page plan with the objectives we agree on, the deliverables, and the timeline. Typical inclusions: llms.txt build, schema markup on top 10 pages, page structure rebuild (H1/H2/H3 hierarchy, meta titles, descriptions), internal linking pass, FAQ sections on service pages, X new articles built around real buyer queries, X press releases for entity authority.
The Build phase has a deliberate order. The plumbing has to be in before the content compounds.
a. Schema + llms.txt + AI crawler signals (week 2) - the markup that tells Google and AI engines exactly what your site is and who you serve.
b. Page structure rebuild (weeks 2-3) - H1, H2 and H3 hierarchy rewritten on your top 10-20 pages so AI engines can parse them cleanly. Structure is one of the strongest signals an LLM uses to decide what to cite. Plus a meta titles and descriptions rewrite for click-through in search results and AI Overviews.
c. Internal linking pass (week 3) - your strongest pages should be reachable in two clicks, with anchor text that signals the topic. Orphan pages get linked or noindex'd.
d. FAQ blocks (week 3) - added to service pages and top blog posts, with matching FAQPage schema. The highest-leverage piece for AI Overview citations.
e. Content (weeks 3-6) - articles and press releases drafted, reviewed, and published on the agreed cadence. Each one built around a real buyer query, not a keyword guess.
f. Tracking (week 6) - Search Console and GA4 dashboards configured. Citation tracking in place.
Everything is live. We move to monitoring mode: AI citation tracking, branded query lift in Search Console, ranking movements. The 3 to 6 month compounding cliff starts here.
Written documentation so your team can maintain and extend the work. If you're on the ongoing partner retainer, we move into rhythm: monthly articles, schema audits, AI prompt updates.
A simpler, faster engagement. Designed for teams losing prospects in the middle of the funnel - the bit where a whitepaper would have been ignored.
30-minute discovery call: where are prospects falling out of your funnel? Usually it's the proof-points stage - they're not converting because they can't see the value translated to their numbers.
Define the math: what your ROI proof-points actually are, what the tool will calculate or configure, what inputs make sense for your ICP, what output unlocks the next sales conversation.
Tool design and build, brand-matched UI, CMS-integrated wherever you host. Lead capture wired into your CRM (HubSpot, Salesforce, etc.) with follow-up workflows. GA4 events tracked.
Tool goes live. We test on real traffic, fix any rough edges, and confirm tracking is firing. Sales gets a quick brief on how to use the tool's output in calls.
Written documentation: how the tool works, how to update the math when your pricing changes, how sales should follow up on the leads it captures.
For B2B teams who have decent product and decent traffic, but their proposal close rate is stuck. Usually it's a structure problem, not a price problem. (See the post on the proposal that closed 50% more deals.)
Pull your last 5-10 sales decks and proposals. Identify the patterns: where do prospects ghost, where do they push back on price, where do they ask the same questions every time? Usually the gaps are obvious within an hour.
Agreed redesign scope. Usually: sales proposal template, sales deck, one-pager, and 2-3 battle cards for top competitor objections. Sometimes plus a case study template if sales doesn't have one.
New proposal template (4-6 pages, not 30). Sales deck rebuilt to land the value in slide 5. One-pager that actually fits on one page. Battle cards covering real objections.
30-minute walkthrough with the sales team. They use the new assets on the next 5 deals. We compare close rates against the previous baseline.
Editable templates handed over (Figma, Pitch, PowerPoint - your team's tool). Plus a one-pager on how to keep the assets up to date as positioning evolves.
Three things on every engagement. The faster you can give me these, the faster I ship. If access is going to take three weeks of IT tickets, tell me on the discovery call and we'll plan around it.
I run lean comms so the work gets done. No daily standups, no recurring "sync calls", no Slack channels with 14 silent observers. Async by default, calls when they actually move things forward.
One discovery call, one proposal, one SOW. First deliverable ships within a week. No 47-page scoping documents, no calendar gauntlet, no "let's circle back next quarter".