Services · AI Agent Development
Agents that act,
not just answer.
Goal-directed AI agents that call your tools, reason over context, and route through human approval where wrong actions cost real money. Built on OpenAI, Claude, and the Vercel AI SDK.
What I build
Task agents
Single-purpose agents that complete a named job - schedule a meeting, draft an outreach sequence, triage a ticket, summarize a thread.
Research agents
Agents that explore - web research, document collection, multi-source synthesis with citations.
Operations agents
Agents that run business processes - outreach, categorization, routing, follow-up - with human approval at the high-stakes steps.
Customer-facing assistants
Agents inside your product that perform actions on the user's behalf - schedule, search, generate, integrate. Examples in my shipped work: Caldra AI, DreamCurtains AI, Lindi AI.
The agent stack I default to
- Model layer: Anthropic Claude or OpenAI, with provider failover via the Vercel AI Gateway.
- Orchestration: Vercel AI SDK (TypeScript), or direct SDK use for the control-heavy paths.
- Tools: typed wrappers around your APIs, validated with Zod. MCP server if it fits.
- Memory + RAG: pgvector or Qdrant, hybrid retrieval, citation grounding. See the RAG tutorial.
- HITL: approval queues, confidence-routed escalation, override capture. Pattern catalog in the HITL guide.
- Guardrails: max-step budgets, cost ceilings, output validation, prompt injection defenses.
- Observability: per-step traces, latency, cost per run, evaluation dashboards.
Pricing
| Scope | Timeline | Price |
|---|---|---|
| Single-purpose agent (5-10 tools, eval set, HITL) | 2-5 weeks | $12K-$30K |
| Multi-agent system with shared memory and observability | 4-8 weeks | $25K-$60K |
| Hourly retainer for ongoing iteration | Ongoing | $100/hr |
Frequently asked questions
What is an AI agent vs a chatbot?
A chatbot answers. An agent acts. Agents call tools - your APIs, your database, external services - to do real work, in a loop, until a goal is met. They reason about which step to take next instead of returning a single response.
Which agent frameworks do you use?
Whatever fits. Vercel AI SDK for most TypeScript stacks (tool-calling, streaming, generateObject), Anthropic SDK directly for Claude-native agents, OpenAI Assistants for stateful flows, and custom orchestration when frameworks get in the way. I avoid LangChain unless the project benefits from its specific abstractions.
How do you keep agents from going off the rails?
Tight tool schemas, strict output validation, max-step budgets, cost ceilings per run, and human-in-the-loop checkpoints on irreversible actions. See the HITL pattern catalog.
Can agents work with my existing APIs?
Yes - that is the point. I wrap your APIs as typed tools the agent can call. The agent does not need anything special on your side beyond the API existing.
What does AI agent development cost?
Single-purpose agent (one workflow, 5-10 tools, evals): $12K-$30K, 2-5 weeks. Multi-agent system with HITL and observability: $25K-$60K, 4-8 weeks.
Can you ship an agent on top of MCP?
Yes. Model Context Protocol works well when you already have an MCP server (or want one) so tools are reusable across multiple agent runtimes. Happy to wire it up.