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¡ Charlie Holland ¡ Architecture ¡ 7 min read
Somewhere between 'ask Claude for a quick opinion' and 'Claude is writing our Jira tickets,' we lost the plot. AI agents are brilliant implementers. They're also confidently wrong about every decision that matters. And when it all falls over, they won't be the ones carrying the bag.
Iâve seen it three times in the last month. Three different organisations, three different tech stacks, the same pattern.
Someone has an idea. Maybe a product manager, maybe a team lead, maybe the CTO after a conference. They open Claude, or ChatGPT, or Copilot â doesnât matter which â and ask it what they should build. The AI does what it always does: validates the idea enthusiastically, suggests an architecture, and starts sketching components. Itâs articulate. Itâs confident. It sounds like a very senior engineer whoâs thought deeply about the problem.
It hasnât thought about the problem at all. Itâs pattern-matching against its training data and producing the most plausible-sounding response. But it sounds so good that nobody pushes back.
Before you know it, Claude is the architect.
AI agents are pathologically agreeable. Ask Claude if your idea is good and itâll tell you itâs good. Ask it if a microservices architecture makes sense for your three-person team and itâll explain why microservices are an excellent choice. Ask it if you should build a custom ML pipeline instead of using a managed service and itâll enthusiastically lay out the design.
Itâs not lying. Itâs not even wrong, necessarily. Itâs just incapable of the thing that makes a real architect valuable: saying âno.â
A good architectâs most important skill isnât designing systems. Itâs knowing which systems not to build. Itâs pushing back on complexity. Itâs asking âwhy?â five times until the actual requirement emerges from the aspirational nonsense. Itâs telling the CTO that their conference-inspired idea is a terrible fit for the team they actually have.
Claude will never do this. Itâs trained to be helpful. Helpful means agreeable. Agreeable means you get an attaboy and a Jenga tower that passes for architecture.
Hereâs what the AI-designed architecture looks like in practice.
Itâs technically sound. The components make sense in isolation. The patterns are recognisable â event-driven here, CQRS there, a service mesh because why not. It looks like something a senior architect would produce. It passes the squint test.
But it wasnât designed for your team. It wasnât designed for your constraints. It wasnât designed for the boring reality of your production environment â the VPC lockdowns, the legacy integrations, the team thatâs never operated Kubernetes in production, the compliance requirements that mean half the managed services are off-limits.
It was designed for the median of everything Claude has seen. A generic best practice for a generic problem at a generic company. Which is to say, it was designed for nobody.
Real architecture is full of trade-offs that only make sense in context. You pick Postgres over DynamoDB because your team knows Postgres and youâd rather ship in two weeks than spend a month learning a new data model. You skip the service mesh because youâve got four services, not forty. You use a monolith because the problem is simple and microservices would be career-driven development.
These decisions require judgement. They require knowing the team. They require understanding the organisationâs actual constraints, not the ones that look good on a whiteboard. An AI agent has none of this context, and worse â it doesnât know it doesnât have it.
The bit that really worries me is what happens next.
Once Claude has designed the architecture, the same people who asked it for the design ask it to break the work down. It produces epics. Stories. Acceptance criteria. Neatly formatted, well-reasoned, ready to drop into Jira.
And now the engineers â the people whoâve spent years honing their craft, who understand the domain, who know where the bodies are buried â are no longer solving problems. Theyâre implementing Claudeâs design, one ticket at a time.
Think about whatâs happened here. The people with the most context, the most experience, and the most skin in the game have been reduced to ticket implementers. The entity with the least context, no experience, and no accountability is making the architectural decisions.
Itâs not just inefficient. Itâs backwards.
This is the defence I hear most often. âClaude suggested the approach, but a senior engineer reviewed it.â
Letâs be honest about what âreviewed itâ means in practice. A busy tech lead gets handed a well-articulated architectural proposal. Itâs coherent. It uses the right terminology. It addresses the stated requirements. The diagrams make sense. It looks like something they might have designed themselves.
How much pushback are they going to give? In a world where the response to âI donât think this is rightâ is âClaude spent twenty minutes on this and you want to throw it away?â, the path of least resistance is to approve it with minor comments.
This is the real danger. Not that AI produces bad architectures â it often produces perfectly reasonable ones. The danger is that it short-circuits the discussion. The messy, argumentative, time-consuming process where three engineers disagree about the approach, where someone says âwhat aboutâŚâ and everyone groans but then realises itâs a good point, where the final design is better than anything one person would have produced â that process gets replaced by âClaude said so.â
Hereâs the question nobodyâs asking: when it goes wrong, who carries the bag?
Not Claude. Claude doesnât have a bag. Claude doesnât get paged at 3am. Claude doesnât sit in the post-incident review explaining why the architecture couldnât handle the load. Claude doesnât have to tell the CTO that the platform needs to be rewritten because the original design assumptions were wrong.
Your engineers do. The same engineers who didnât design it. The same engineers who were implementing tickets written by an entity thatâs never operated a system in production. Theyâre the ones staying late, debugging an architecture they didnât choose, in a codebase that was scaffolded faster than anyone could understand it.
Thatâs not fair. And itâs not smart.
Iâm not saying donât use AI agents. I use Claude Code every day. Itâs transformed my productivity. But I use it the way youâd use any powerful tool â I tell it what to do, not the other way round.
Engineers design. Agents implement. The architecture comes from people who understand the context â the team, the constraints, the production environment, the organisational politics. The AI helps them build it faster. Thatâs the right division of labour.
Challenge the attaboy. When an AI suggests an approach, treat it with the same scepticism youâd apply to a confident junior engineer. It might be right. It might also be pattern-matching against something that doesnât apply to your situation. Ask âwhy not the simpler option?â and see what happens.
Protect the argument. The messy disagreement between engineers is where good architecture comes from. If AI is short-circuiting that process â if people are deferring to Claude instead of debating with each other â youâve lost something far more valuable than development speed.
Keep humans accountable. If a humanâs name isnât on the architectural decision, nobody owns it. And if nobody owns it, nobody will fight for it when it matters. âClaude designed itâ is not an architecture decision record. Itâs an abdication.
Thirty years ago, when I started in this industry, the tool was a whiteboard and a strong opinion. Today the tool is an AI agent that can produce in minutes what used to take days. The speed is genuinely remarkable.
But the craft hasnât changed. Understanding the problem. Knowing the constraints. Making trade-offs. Defending the simple solution against the exciting one. Saying ânoâ to the idea that sounds great but doesnât fit.
Thatâs architecture. No agent does it. If youâve let Claude take the wheel, take it back.
Your engineers have spent years building the judgement to make these calls. Let them make them. Use the AI to build faster. But build what your people designed â not what the machine suggested.
Because when the Jenga tower wobbles â and it will â Claude wonât be there to catch it.