Forem: Christopher Igbojekwe

The 2026 AEO Checklist: Steps to Get Recommended by ChatGPT, Claude, and Gemini

Christopher Igbojekwe — Tue, 05 May 2026 16:23:24 +0000

If you've ever searched your own product and seen a competitor recommended by an AI assistant instead, you already understand why AEO matters.

Answer Engine Optimization (AEO) is the practice of making your site legible, trustworthy, and citable to AI systems like ChatGPT, Claude, Gemini, Perplexity, and Deepseek. It's not magic. It's mostly technical and structural decisions you can either get right or leave broken.

The frustrating part? A lot of what blocks AI citations is stuff you'd fix anyway for good engineering reasons: server-rendered HTML, clean redirects, structured data. The difference is that with AI answer engines, the signal patterns are tighter and the feedback loop is longer.

Why This Matters More for Builders Than Marketers

Most AEO content is written for marketing teams. But if you're building a dev tool, SaaS platform, or data product, you're often the one with deploy access and the one who can actually fix this.

More importantly: if your docs, landing pages, and technical content aren't structured correctly, the AI answering your potential users' questions will route them elsewhere. That's a distribution problem with a technical solution.

1. Technical Foundation

This is the blocking category. Nothing else matters if AI crawlers can't read your site.

Server-render your critical content
Hero text, feature descriptions, and pricing copy need to appear in raw HTML, visible in View Source, not injected by JS. Pure client-side SPAs with a shell

will tank your AI visibility.

Allow AI crawlers in robots.txt
Explicitly allow GPTBot, ClaudeBot, PerplexityBot, Google-Extended, and Applebot-Extended. A forgotten blanket Disallow: / is a common silent killer.
User-agent: GPTBot
Allow: /

User-agent: ClaudeBot
Allow: /

Create an llms.txt file
A Markdown file at /llms.txt describing your product, key pages, and preferred framing. Think robots.txt but for communicating intent to AI crawlers. This standard reached broad adoption in 2025-2026, so getting it right early gives you a framing advantage.

Everything else in this category:

Sitemap with current lastmod dates, submitted to Search Console
Core Web Vitals green on mobile (LCP <2.5s, INP <200ms, CLS <0.1)
HTTPS with valid cert (AI crawlers skip HTTP-only domains)
Canonical tags on every indexable URL
No broken internal links (run Screaming Frog quarterly)
No redirect chains; collapse to single hops

2. Schema & Structured Data

JSON-LD tells crawlers what your content is, not just what it contains. Without it, AI systems guess.

Organization — root layout, with name, url, logo, and sameAs links to your social profiles. This is your baseline entity.
Person — for founders, key engineers, authors. Include sameAs pointing to LinkedIn and GitHub. This ties your people to your entity graph.
Service — one per product offering, with provider and areaServed. Vague service pages hurt you here.
FAQPage — highest ROI item on this list. Structured Q&A pairs are directly citable by AI. Every commercial page should have one.
Article — on every blog post. headline, datePublished, author, publisher are required fields.

Use @graph when a page has multiple entity types. It shows crawlers how entities relate, rather than treating them as disconnected blocks.
Run every key page through Google's Rich Results Test. Zero errors, zero warnings.

3. Content & Entity Clarity

AI models reward specificity and punish vagueness. Most technical founders underinvest here.

❌ Weak "We deliver results"
✅ Citable "We improved conversion 34% on a $40M ARR SaaS"

❌ Weak "Our team executed the work"
✅ Citable "Chris built the migration pipeline"

❌ Weak "It depends on your use case"
✅ Citable An actual, specific opinion

Named people, not "our team." Attaching a name ties work to a Person entity that AI can verify across LinkedIn, GitHub, and your schema.

Take actual positions. AI cites confident, specific claims. Hedged non-opinions get summarized without attribution.

FAQs on every commercial page. Six to ten buyer-language questions with FAQPage schema. Think "How does X compare to Y?" not "What is X?"

Original data is table stakes. Benchmarks, survey results, proprietary frameworks. If your content is assembled entirely from public info, AI has no reason to attribute it to you.

On AI-generated content: Models increasingly detect and deprioritize it. If your blog posts are 80% raw model output, expect weak citation performance. Edit until it has a real point of view.

4. Entity Signals

Your site alone isn't enough. AI systems build entity graphs from external sources.

Here are the Sources and What to do's:

LinkedIn: Company page complete and active. Leadership profiles consistent with your schema.
Crunchbase: Accurate description, founding year, HQ, team. Major entity source for AI models.
Directories: Three to five credible ones for your vertical (Clutch, G2, Capterra). Avoid link-bait directories.
Press: Two to three credible mentions per year. Trade pubs, podcasts, respected blogs. Quality over quantity.
NAP consistency: Name, address, phone identical everywhere. Discrepancies reduce entity confidence.
Wikipedia: Only if you meet notability standards. If it fits, it's the strongest entity signal available.

5. Monitoring & Iteration

AEO is not a one-time deploy. The platforms change fast.

Monthly query set (25-50 queries). Mix of brand, category, problem, and competitor queries. Run the same set every month to track movement.
**Test across all platforms separately. **ChatGPT, Claude, Gemini, Perplexity, and Deepseek each cite differently. Don't assume coverage.
Citation log. Track which pages get cited vs. summarized without attribution. Cited pages are winning; others need work.
Refresh pillar content every 6 months. Freshness is weighted by both Google and AI answer engines.
Check for new platforms quarterly. Deepseek is the most recent example of a fast-emerging player. Staying current is a short-term competitive advantage.

Phasing It If You're Resource-Constrained

Phase 1 - 1Week 1-2 - Technical foundation + schema
Phase 2 - Week 3-6 - Content restructuring + FAQ blocks
Phase 3 - Week 7-10 - External entity signals (LinkedIn, Crunchbase, directories)
Phase 4 - Ongoing - Monthly monitoring + quarterly platform reviews

What to Realistically Expect

Perplexity: First citations within 2-3 weeks of foundational fixes
ChatGPT / Claude: 30-60 days
Gemini: 60-90 days
Deepseek: Still forming; signal patterns unclear

At 90 days with no movement, the culprit is almost always weak external entity signals or thin content. Push harder there before optimizing anything else.

The Mental Model

Think of AEO as data engineering for AI systems, not an SEO project. You're making your entity graph coherent, your content structure parseable, and your external signals consistent enough that a model can confidently represent what you've built.
The builders who treat this as infrastructure work will have a compounding citation advantage as AI search continues to grow.

Which of your key product pages would an AI model struggle most to describe accurately right now? Have you actually tested it?

What a Website Rebuild Actually Costs (And Why the Budget Conversation Usually Starts Wrong)

Christopher Igbojekwe — Tue, 28 Apr 2026 18:46:14 +0000

Most budget conversations about website rebuilds start in the wrong place.

Founders ask: "How much does a website cost?" The real question is: "What are we actually trying to build, and what will it cost us not to build it right?"

I've rebuilt sites for government agencies, B2B SaaS companies, e-commerce brands, and early-stage startups. Projects ranging from $5K to $75K+. Here's what I've learned about where money goes, where timelines die, and what I'd do differently.

The Tiers Are Real. The Ranges Are Deceptive.

Before we get into the nuance, here's the honest breakdown:

Template refresh — $3K to $8K New design on an existing platform (Webflow, WordPress theme, Squarespace). 5 to 15 pages. Better copy, better structure, no custom logic. Ships in 3 to 5 weeks.

Custom design and build — $15K to $40K Custom design system, built on Webflow or Next.js. 10 to 30 pages. Includes strategy, CMS setup, SEO foundation, and maybe a CRM or analytics integration. 8 to 12 weeks.

Platform rebuild — $40K to $100K+ Ground-up rebuild with custom application logic. Customer portals, partner ecosystems, multi-language support, migrating off a legacy CMS no one on the team fully understands. 3 to 6 months.

These tiers look clean on paper. The real question is what moves you from the low end to the high end within each tier. That's where most scoping conversations go sideways.

The Cost Drivers Nobody Talks About Clearly

1. Custom Logic Compounds Fast

A static 10-page marketing site is a fundamentally different engineering problem than a site with role-based access, dynamic pricing, or third-party API integrations.

A concrete example: a "simple" booking form integration might take one day. A custom partner dashboard with role-based access and a synced data model takes weeks, including edge cases, error states, and the inevitable "wait, can external users see this field?" conversation on week three.

If you're a technical founder, you already know scope creep lives in the logic layer. The same is true here.

2. Content Is Always the Bottleneck

A 10-page site costs less than a 50-page site. Obviously. But what actually kills timelines isn't the page count. It's the content pipeline.

Most clients say they'll have content ready. Most don't.

What actually delays projects: copy that needs writing, case studies that need creating, product screenshots that can only be taken after the new UI ships, existing documentation that needs restructuring.

Treat content delivery like a hard dependency in your project plan. Gate development milestones on content sign-off, not the other way around.

3. SEO Migration Is an Iceberg

If your site has any search equity, even modest rankings, a rebuild without a migration plan can wipe years of accumulated value overnight.

What this actually involves: redirect mapping for every changed URL, preserving backlink equity, auditing canonical tags, maintaining hreflang attributes across language variants.

I recently scoped a migration for a site with 1,700+ URLs. That work alone was a meaningful piece of the engagement. Not glamorous, but the kind of thing that quietly costs companies thousands in lost organic traffic when it gets skipped.

Rule of thumb: if the site has been live for more than two years and gets any organic traffic, budget for a dedicated SEO migration plan. It's not optional.

4. Skipping Strategy Is the Most Expensive Decision You Can Make

The most expensive mistake in a rebuild is spending $40K rebuilding the wrong thing.

A proper strategy phase, covering analytics audits, user research, competitor analysis, and conversion funnel mapping, costs $2,500 to $10,000 and regularly prevents six-figure mistakes.

A real example: an audit I did revealed a company's primary conversion page had been broken for over four years. It was returning raw code instead of a form. Every lead that landed on that page during that window was lost.

If a vendor quotes only "design and development," ask explicitly: who is doing the strategy, and when? If the answer is "we'll figure it out during kickoff," that's a yellow flag.

Platform Choice: Follow the Strategy, Not Familiarity

The failure mode I see most often: companies choose a platform based on familiarity, then spend years fighting its limitations.

The second most common: companies go fully custom Next.js when Webflow would have shipped twice as fast at half the cost, because someone wanted maximum control over a site that just needs to look good and convert visitors.

The question to ask before picking anything: What does this site need to do in 12 months that it can't do today? Work backward from that, not from what your team already knows.

Here's how I think about the main options:

Webflow is the right call for most marketing sites and CMS-driven content, especially if non-technical teammates need to make edits without filing a ticket. The hard limit is custom logic. If you need a real backend, user authentication, or anything resembling a web app, you'll hit that ceiling fast.

Next.js and React make sense for custom apps, portals, dashboards, and performance-critical builds. The tradeoff: every content change requires a developer unless you wire up a headless CMS on top of it. More power, more maintenance surface.

WordPress still works well for content-heavy sites and teams already deep in that ecosystem. But go in with eyes open. Performance out of the box is rough, plugin bloat is real, and security is an ongoing maintenance burden, not a one-time setup.

Shopify is the obvious choice for e-commerce: product catalogs, checkout optimization, inventory management. Outside that lane, it gets painful quickly.

The platform should follow the strategy. Pick what fits what you need to build, not what someone on the team already knows.

What Actually Brings the Cost Down

Ship content before development starts. This is the single highest-leverage thing a client can do. Final copy, brand assets, and images delivered before the build begins can eliminate 20 to 30 percent of a project timeline.

Scope the MVP tightly. Launch with 15 essential pages instead of 40. Add the rest in phase two, after you have real user data. The best sites are built iteratively. A 15-page launch that ships in 8 weeks usually outperforms a 50-page launch that ships in 6 months.

Work with a small team or senior freelancer. A large agency has overhead: account execs, project managers, sales teams, office space. A senior freelancer or boutique team delivers comparable quality without the markup. You're paying for the work, not the org chart.

The Hidden Cost: Doing Nothing

Here's the math that doesn't show up in vendor proposals.

If your site is underperforming, that cost is paid every day. Not as a line item, but as leads that bounce, search rankings that slip, and credibility that quietly erodes.

A real example: one audit found a B2B company ranking on page four of Google for their primary product keyword. Their site was built on a bloated platform generating pages twice the recommended size, with navigation that had 60+ items when top competitors had 11.

That wasn't a design problem. It was compound technical debt masquerading as a marketing problem.

A rebuild is a one-time cost. An underperforming site is a recurring one.

How to Actually Budget for This

1. Start with an audit, not a redesign. A $3K to $7K audit tells you exactly what needs to change and often surfaces quick wins you can ship before touching the core build.

2. Budget for strategy, design, and development as a unit. These aren't separable phases. A pretty site that doesn't convert is just expensive art.

3. Plan for post-launch optimization. Budget $1K to $3K per month for the first three months after go-live. Real user data surfaces things no amount of pre-launch testing catches.

4. Compare total cost, not hourly rate. A $150/hr senior developer who ships in 8 weeks costs less than a $75/hr junior who takes 6 months and needs three rounds of revisions.

What I'd Do Differently

Gate every project on a written content plan before design begins. No exceptions.

Build SEO migration into default scope for any site older than two years. It's always needed and almost always underbid.

Push back harder on scope creep in the logic layer. That's where timelines go to die.

Start smaller and ship faster. The version that gets real data beats the version that tries to anticipate everything.

For those who've been through a rebuild, as the client or the one doing the work: where did the scope surprise you most?

Was it the content pipeline? The SEO migration? Platform limitations? Something else entirely?

And if you're currently scoping one, what's the decision you're stuck on? Happy to think it through in the comments.