This week everyone is talking about Apple’s new headset from WWDC and the steady drumbeat of AI news, while teams are quietly drowning in backlogs and late nights. We keep saying we are paying down technical debt. We point at some old module, a weird integration, a flaky test, and we call it debt. That label makes the problem feel tidy and contained. It is not. The drag we feel every time we add a feature, swap a vendor, or roll out a campaign comes from one source that cuts across code, cloud, and content. Complexity is the real technical debt. It is sneaky, it compounds, and once it spreads through an org chart it becomes culture. Developers feel it when a simple change touches five repos. Marketers feel it when one tag update ripples across a zoo of tools. Leaders feel it when planning turns into guesswork because no one can hold the full system in their head.
Think of complexity as a monthly tax that never sleeps. It grows with every new service, every extra field in the data layer, every bespoke workflow built to save a week but that adds a year of maintenance. Debt is not only in code. It is in org boundaries, vendor contracts, branching strategies, naming, and the long trail of half migrations we leave behind. If you want speed, quality, and sane Fridays, stop treating debt like a pile of tickets and start treating complexity as the main product problem.
Here is the test. If your team fixes lint warnings but still takes ages to ship, if your martech stack gets new tools but tracking still breaks, if every incident needs a council of experts, you do not have a code problem, you have a complexity problem. Complexity lives outside the editor. It lives in the number of moving parts and the number of hands required to move them. Microservices bring freedom until they bring fifty flavors of freedom. Kubernetes is great until each team curates its own way to deploy and observe. Feature flags help until flags stack in layers and no one knows which combo is live. On the marketing side, the GA4 deadline is racing in and teams are juggling consent, server side tagging, a CDP, a data warehouse, a dozen connectors, and an ask for daily dashboards in every region. None of that is bad on its own. The issue is the sum of choices and the lack of guardrails. When there are too many paths, every path slows down. When your stack looks like a patchwork quilt, you pay with review cycles, handoffs, outages, and rework. That is the interest on complexity. We pretend the bill is old code, but the bill is coordination. It is context switching. It is new hires taking months to onboard because tribal knowledge replaced clear defaults. So what to do. First, choose boring on purpose. Pick defaults and stick to them. Standard pipelines, standard logging, standard metrics, a common way to roll out changes. Not the best tool for each slice, but a good path that everyone can walk. Second, delete to speed up. Shut off the extra staging environment that no one trusts. Remove the second queue. Collapse environments if ephemeral previews do the job. Sunsetting is a feature. Third, reduce surface area. Fewer services with stronger contracts beat many services that chat all day. In marketing, fewer events with sane names beat a flood of event variants that look smart in a spreadsheet and break every report a month later. Fourth, design for ownership. Every service, dataset, and tag should have a team on the hook and a simple runbook. Owners set service level objectives that match business reality. That clarity cuts through debate and makes trade offs visible. Fifth, budget time for migration and deletion, not just build. Parallel systems are the worst debt of all. If you roll GA4 while keeping legacy reports alive forever, you just doubled your work. Finish the bridge and burn the old one. Sixth, shrink the blast radius of decisions. If a change needs six approvals, you built a process not a product. Push decisions to the teams that carry the pager, and give them a paved road. Seventh, measure the right signals. Watch lead time, change failure rate, mean time to recovery, number of steps to ship, time to first pull request for a new hire. In marketing ops, track the time from tag request to live, number of duplicate audiences, number of one off dashboards, and the count of tools that touch a customer record. These are complexity meters. When they rise, stop and prune. Eighth, say no to shiny until it deletes more than it adds. This week is full of new AI features, and the pitch to bolt them onto every workflow is strong. Adopt new tech only when it replaces three old things. If it sits next to them, it is not a win. Ninth, write for humans. A small handbook with clear naming, event catalogs, example repos, and a starter template does more for speed than any status meeting. Finally, treat platform work as a product. The best internal platforms remove choices and remove toil. They do not expose kitchen sink options. They give a small set of golden paths and great defaults. On the marketing side, pick one tracking plan, one attribution story, one consent flow, and stick to them. Standard events across brands, a lean set of UTM rules, and one source of truth for revenue mapping will do more for campaign performance than piling on another tool. This is not a call to freeze. It is a call to tighten focus. When everything is important, nothing ships. When you remove moving parts, speed returns and incidents calm down. The team feels lighter. Planning gets honest. Backlogs stop growing moss. You do not need a grand re write. You need fewer things, clearer ownership, and a bias for deletion. That is how you pay the only debt that really matters.
Ship fewer things that do more and complexity will start paying you back.