For years, a website had one job: tell people who you are, what you sell, and how to reach you. A digital brochure. Professional, maybe even pretty, but fundamentally passive. That model isn't going away. Businesses still need homepages, service pages, blogs, pricing tables, and contact forms. But something is shifting underneath all of it. The next generation of websites won't be judged by how they look or how fast they were built. They'll be judged by how well they help peo

Job descriptions are the most honest documents in the hiring market. Nobody writes them to inspire. They get written by a hiring manager who has a gap, a scorecard, and a budget, and they tend to say the quiet part out loud. So rather than career advice, here's a reading of what current senior Customer Success and Partnerships job descriptions actually ask for. Not what LinkedIn says these roles are about. What companies put in writing when they're paying for the outcome. The

Retention numbers carry a strange authority in SaaS. They get printed on board slides, quoted in fundraising decks, and used to justify headcount. Very few people in the room ask what the number is actually made of. That's the problem worth writing about. Not that the metrics are wrong, but that each one is a compression of a messy reality, and compression always loses something. The operator's edge isn't knowing the formulas. Everyone knows the formulas. It's knowing what ea

Most of what AI does in Customer Success today is unglamorous. It writes the follow-up email. It summarizes the call. It drafts the QBR deck. If you were expecting autonomous agents running your book of business, the reality looks more like a very fast intern. I don't think that's a disappointment. It's the right place to start, and the teams that understand why are going to pull ahead of the ones chasing something flashier. The adoption numbers are honest Gainsight's 2025 Cu

Ask ten SaaS leaders where partnerships sits in their company and you'll get ten different org charts. Sometimes it reports to sales. Sometimes to marketing. Sometimes it floats near the CEO as alliances and surfaces twice a year with a logos slide. For a long time that ambiguity was tolerable. Partnerships was a channel, one of several ways to source pipeline, and if it had a slow quarter, the direct motion carried the number. That arrangement is ending. The evidence from th

Most people still picture a website as a set of pages. Home, about, services, contact. That model was fine when the job of a site was to sit there and look credible. It's the wrong model now. The site people see is the thin top layer of something much bigger, and the value has quietly moved down the stack. I've been circling this shift across a few posts in this series. This one pulls it together. If you want a single way to think about where web value actually sits in 2026,

Ask your phone for a plumber and see what happens. Not Google. Ask an AI assistant. "Who can fix a water heater in my area today, and what will it cost?" You won't get ten blue links. You'll get one or two names, maybe a price range, maybe a booking suggestion. That's the new front door for local business, and most small business websites aren't built for it. The discovery shift is already here For twenty years, local discovery worked roughly the same way. You showed up in se

Every few years search marketing gets a new acronym and a wave of consultants ready to sell you the secret to mastering it. AEO, Answer Engine Optimization, is the latest one. I've seen webinars promising "the new rules of AI visibility" and posts implying that everything you know about SEO is now obsolete. It isn't. Here's what's actually happening: ChatGPT, Perplexity, and Google's AI Overviews now sit between a lot of searches and the websites that used to answer them. Tha

Ask a hotel's website whether it has a room with a balcony free next Friday for two people, and whether breakfast is included, and most sites either ignore the question or hand you a generic FAQ page that answers something close to it. That gap, between what a visitor actually wants to know and what the site is built to answer, is the entire reason RAG matters for websites. Not because it's a trend, but because it closes that gap with real data instead of a chatbot guessing.

"Headless" is one of those words that makes a simple idea sound complicated. People hear it and assume it's a developer-only concern, something you need a CTO to care about. It isn't. The idea behind headless is the most practical thing happening in web architecture right now, and AI is the reason it suddenly matters to businesses that never thought about it before. Here's the simplest way I've found to explain it. The kitchen and the dining rooms Think about a restaurant. Th

Most small business websites are doing one thing: existing. There's a homepage, an about page, maybe a contact form. The site went live a few years ago, it hasn't changed much since, and from a business standpoint, it mostly just sits there. That's a stage one website. And for a lot of businesses, staying at stage one is an active choice they haven't quite made yet. The Three Stages The evolution of the business website isn't complicated, but it's worth naming clearly because

Every few years, something comes along that's supposed to kill web design. Drag-and-drop builders were going to do it. Templates were going to do it. No-code tools were going to do it. They didn't. What they did instead was change who does what, and for whom. AI website builders are next in line for this prediction. And they're wrong about it too. Not because AI isn't capable, it clearly is. But because creation was never really the hard part. What These Tools Actually Do WIX

There is a version of AI adoption in partner success that looks very productive on paper. Automated QBR prep. AI-generated health scores. Instant meeting summaries. Risk flags that surface before a human would have noticed. Partners getting responses in minutes instead of days. And then six months in, you look at your renewal numbers and something is off. Not catastrophically. Just quietly. A few partners who seemed fine — green health scores, regular activity, no open ticket

Autonomous vehicles are usually discussed as a technology story. That makes sense. The technology is impressive. A car moving through Miami traffic without a human driver is not a small thing. It is the kind of product experience that still feels slightly unreal, even after years of hearing that self-driving transportation was coming. But the more interesting question is not whether the vehicle can drive. The harder question is whether the company behind it can earn enough tr

Why Most Review Cadences Fail The most common failure is structural. Reviews get built around comfort rather than clarity. Partnership teams often default to presenting good news, glossing over what is not working, and avoiding any conversation that might feel confrontational. Partners play along because the relationship is cordial and they have no incentive to surface problems they are not sure you want to hear. The result is a review that confirms the partnership exists wit

Most partnership programs have at least one partner that everyone internally knows isn't performing. The deals aren't closing. The pipeline is mostly noise. The relationship is cordial but commercially thin. And yet the partner stays — sometimes for years. This isn't an accident. It's the result of a set of structural and psychological patterns that make it easier to keep the relationship going than to honestly assess whether it's working. Understanding those patterns is the

If you work with partners long enough, one pattern becomes hard to ignore: the teams with the biggest partners do not always get the best results. In fact, some of the strongest partner outcomes come from smaller portfolios run with much more discipline. The partner list may look less impressive from the outside, but the underlying motion is stronger. Priorities are clearer. Follow-through is tighter. Risks surface earlier. The relationship has shape. That is usually the diff

In SaaS, partnership leadership is easy to describe badly. A lot of people reduce it to sourcing deals, managing integrations, or keeping partners happy. That is part of the job, but it misses the real point. The strongest partnership leaders do three things especially well. They connect partnership strategy to business priorities. They influence teams that do not report to them. And they think beyond the company itself, with a clear view of the wider ecosystem. That is where

Strong partner teams rarely run on improvisation. From the outside, partnerships can look informal. Relationships, conversations, introductions, and joint opportunities. But the teams that manage partnerships well usually rely on a clear operating rhythm behind the scenes. Without that rhythm, things start to drift. Opportunities disappear from view. Small problems stay unnoticed until they become larger ones. Internal teams lose alignment with partners. And eventually the pa

On paper, they look like an efficient way to expand reach, grow revenue, and strengthen market presence without doing everything yourself. In reality, most partner programs are uneven. A small number of partners create real value. A larger number sit somewhere between inactive and hard to assess. And leadership teams often do not have a clean way to tell the difference early enough. That is where AI starts to become useful. Not in the inflated, "AI will run your ecosystem" se