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The demo is not the decision
Most consultancies trialling AI coding tools hit the same wall. The tool demos well, it impresses in a vendor deck, and then someone asks a real question: what happens when the provider changes pricing, introduces usage caps, or simply does not fit how your team works? That is not a technology question. It is an operational one, and it is worth answering before you commit.
The villain in most AI tool decisions is the demo. Everything works in a demo. The real test is whether the tool fits your delivery workflow, your data governance requirements, and the reality that your team will be switching between providers as the market matures.
Vendor lock-in is not a hypothetical risk. When a single provider controls your tooling, pricing, and access, you are one policy change away from a disrupted workflow.
Same surface
What both tools actually do
Claude Code and OpenCode are terminal-based AI coding agents. You open either one in a project folder, describe what you want, and the agent reads your codebase, writes code, runs commands, and iterates until the task is done. The experience is nearly identical. The architecture underneath is not.
- Claude Code is Anthropic’s official tool. It is tightly integrated with Claude’s model family — Sonnet and Opus — and benefits from direct vendor support. If uptime is business-critical and you want an SLA, this matters.
- OpenCode is a community-maintained, open-source coding agent with direct connections to 75 AI providers. You choose which model powers it — Claude, OpenAI, Gemini, Grok, or a local model on your own hardware. Same terminal interface, different brain, no lock-in.
A recent Ollama development is worth noting. Version 0.14 added Anthropic API compatibility, so Claude Code can now run against local, open-source models rather than only the Anthropic-hosted ones. That removes the lock-in argument, but only partially. OpenCode connects directly to whichever provider you choose — one configuration and done. Claude Code with Ollama needs Ollama running as a middleware layer between the tool and the model. Fine for a quick local test; for a team deploying across multiple environments, the extra moving part is worth factoring in.
How it works
Three interfaces, four built-in agents
OpenCode offers three ways to work with it:
- Terminal — the core experience, fast and keyboard-driven
- Desktop app — now in beta across macOS, Windows, and Linux, for teams less comfortable in the terminal
- VS Code extension — for developers who live in their IDE
It also ships with four built-in agents that match how a delivery team divides work. The Build agent has full access for active development. The Plan agent is read-only — useful for analysis and codebase exploration without the risk of unintended changes. The General agent handles complex searches and multi-step tasks. The Explore agent navigates codebases and answers questions without touching any files.
This maps neatly to the Knowledge, Workflow, and Agent layers of how AI should sit inside a delivery operation. The Explore and Plan agents are particularly relevant for onboarding new team members to an existing codebase — a common pain point in growing consultancies.
OpenCode also includes a feature called Zen: a curated gateway that benchmarks specific model and provider combinations and surfaces only the ones that work well for coding agents. The same underlying model can perform very differently depending on how it is hosted and served, and Zen removes that variable. Pricing is pay-as-you-go from roughly $20, with no subscription — you top up when you need to, test multiple models, and scale once something proves itself.
The numbers
A realistic cost comparison
For a 30-person consultancy with five developers:
- Claude Code subscriptions — approximately £510 per month at current pricing
- OpenCode with Claude Pro authentication — approximately £110 per month for the same team, using existing subscriptions
- OpenCode with Zen — variable, pay-as-you-go, typically lower depending on development intensity
The cost gap is meaningful, but it is not the only number that matters. What matters is whether the tool fits your governance requirements, your team’s workflow, and your exposure to provider-side changes.
The call
When to choose each option
Choose OpenCode if:
- You want direct multi-provider support without middleware
- Your team switches between cloud providers or models regularly
- You want the Zen curated model gateway for benchmarked performance
- Your firm values community-driven, rapid iteration over vendor polish
Choose Claude Code if:
- You want Anthropic’s official support and vendor SLA
- Complex reasoning tasks with Claude Sonnet or Opus are your primary use case
- You prefer a polished, supported experience over configuration flexibility
Choose Claude Code plus Ollama if:
- You want the Claude Code interface with local model privacy
- You already run Ollama infrastructure
- You want to test local coding agents before committing to a subscription
All three paths are now viable. The decision comes down to your team’s priorities.
Governance
What this means for regulated environments
Both tools now offer local-first options, which matters for legal, healthcare, and financial services firms where data cannot leave a controlled environment. OpenCode’s simpler architecture — fewer layers between the tool and the model — means fewer components to audit. If your data governance requirements are strict, that simplicity has real operational value.
This connects directly to the Govern step in the 5 Steps for AI Leadership framework. Before your team deploys any AI coding tool at scale, you need a written policy covering approved tools, data handling rules, and what the tool is and is not permitted to touch. Neither OpenCode nor Claude Code does that work for you, and it has to be done before the tool goes near a client codebase.
There are honest trade-offs to weigh. OpenCode is community-maintained: if something breaks, you are relying on GitHub issues and community support, not a vendor help desk, and there are no SLAs. It also requires more configuration upfront — choosing providers, managing API keys, handling authentication. Not complex, but not zero effort. Claude Code, by contrast, is a supported product with Anthropic behind it; if you need the security of a vendor relationship and documented uptime commitments, that carries weight.
The real question
Is your tooling reducing delivery drag or adding to it?
The real question is not which tool wins a benchmark. It is whether your current AI tooling approach is reducing delivery drag or adding to it.
Most consultancies we work with are still in the Activate stage of the 5 Steps for AI Leadership — getting the team using tools consistently in daily work. Before choosing between OpenCode and Claude Code, be clear on where your firm actually sits:
- Do you have a written AI position?
- Are your team’s tools consistent and governed?
- Do you know which workflows would benefit most from AI coding support?
If the answer to any of those is uncertain, that is the starting point.