Sprint
Production code ships. Schema architecture, JSON-LD per template, validator-clean structured data live in your codebase with CI gates.
The Sprint is where engineering happens. Four to six weeks. Fixed scope agreed upfront. Schema architecture, JSON-LD per template, crawlability fixes, all shipped to production. Validator-clean with CI gates that keep it that way.
I work directly with your engineering team. We pair on architecture, I write the implementation, your team reviews and merges. By the end your team can maintain and extend the work without me. That's the explicit goal.
The base $70,000 covers a typical mid-complexity site: roughly 10-50 templates, single domain, English-only. Multi-domain, international entity graphs, or unusually high template counts quote higher (range $90K–$150K). Audit results determine the exact scope before contract.
What's included
- Full @graph architecture across all production templates
- Per-template JSON-LD implementation, shipped to production
- AI search optimization · entity resolution + crawler emulation
- Crawlability fixes · robots.txt, sitemaps, canonical, hreflang
- Schema validator suite integrated into your CI
- Engineer pair sessions with your internal team (knowledge transfer)
- Pre-Sprint / post-Sprint AI engine citation measurement
- Architecture decision records · documentation handoff
What’s not included
- Content writing or editorial decisions
- UI/UX redesign
- Post-launch monitoring (that's Retainer scope)
- New design-system work
What the Sprint actually consists of
Each line item below is its own deep-dive page. Open the ones that matter to your decision. Skip the rest.
- // component 01Full @graph architecture
One consolidated JSON-LD @graph per page, designed across templates, with @id and sameAs chains stable enough for AI engines to merge entities cleanly.
Read the deep-dive - // component 02Per-template JSON-LD
I write the schema generation code for every priority template, ship it through your CI, and pair with your engineers so they can extend it after I'm out.
Read the deep-dive - // component 03Entity resolution and AI emulation
I emulate how each AI engine actually parses your @graph, find where entities fail to resolve, and fix the schema so resolution happens deterministically.
Read the deep-dive - // component 04Validator suite in CI
Schema validation runs on every pull request. If a change breaks a Schema.org rule or a custom @graph rule, the build fails before it ships.
Read the deep-dive - // component 05Engineer pair sessions
I pair directly with your engineers through the Sprint so they review every PR, understand the architecture, and own the work after I'm out.
Read the deep-dive - // component 06Pre/post citation measurement
I run the same AI visibility query set before and after the Sprint, so the engagement has a measured outcome instead of a vibes-based one.
Read the deep-dive
Do I need to do the Audit first?
Strongly recommended. Without an Audit, scoping the Sprint is guesswork. If you have an existing audit (from another vendor or internal), I'll review and we can move directly to Sprint. External-audit credit: $5,000 off the Sprint fee.
How does this work with my existing engineering team?
I pair, write, and PR. Your team reviews and merges. Knowledge transfer is the goal. I want your team owning this work after I'm out. If your team can't pair (capacity issues), I can ship in isolation, but you lose the knowledge-transfer benefit.
What if scope changes mid-sprint?
Fixed scope means deliverables agreed upfront. Small adjustments get absorbed. Material expansions become a Sprint extension at $1,500/day. I'll flag scope creep early.
Can you guarantee specific traffic outcomes?
No. Anyone who guarantees traffic from schema work is selling you something. What I guarantee: validator-clean schema in production, AI engines correctly resolving your entity graph, measurable improvement in citation extraction, CI gates that catch regressions before they ship. Traffic outcomes depend on factors outside engineering: content, query volume, competitor moves, platform algorithm changes.
Stop pouring budget into a broken foundation.
If your SEO retainer hasn’t compounded, your AI citations have stalled, or your last technical audit ended in a deck nobody read, that’s not a content problem. It’s an engineering problem. The same engineer who diagnoses ships the fix.