Project
$15k+fixed scope
Fixed-scope build with a senior engineer leading. The most common engagement.
- Senior engineer on code
- Fixed scope + quote
- 4–8 weeks to ship
- 30-day support
Hire Agentic Engineer
Hire an agentic engineer who knows where the guardrails go.
Agentic engineering is a discipline: tool design, sandboxing, memory architecture, evals, observability, human-in-the-loop, cost control. We've done it in production. You get that experience.
The problem
Agentic systems fail in expensive ways.
Without guardrails: agents that hallucinate customer data, loop infinitely on edge cases, run up $4k of model bills overnight, or take destructive actions in production systems they shouldn’t have had write access to.
The agentic engineer’s job is mostly preventing these failure modes — not making the agent do impressive things in the happy path. That’s the part most “agentic AI” tutorials skip.
What we do
Designed for what happens when the agent is wrong.
We design agentic systems with explicit failure modes: confidence thresholds for escalation, sandboxed tool calls, budget caps, audit logs of every action, human review on destructive operations.
We’ve shipped this in production with Arlo (our own product) and inside Agency ERP. Same patterns and same scars apply to your project.
Capabilities
Agent architecture design
Single vs. multi-agent, planner vs. ReAct, when to spawn subagents, how memory flows. Designed up-front, not improvised.
Tool design + sandboxing
Tools that are scoped, idempotent, reversible where possible. Sandboxed execution (Docker, Modal, Singularity) for risky operations.
Memory architectures
Short-term, long-term, semantic, episodic. Retention policies. Redaction. The right shape per use case.
Human-in-the-loop
Confidence-based escalation, approval workflows for destructive actions, gradual autonomy expansion as trust builds.
Eval-driven development
Eval suites against real cases. Regression catching. Quality measured before production. Standard practice for us, rare in agent work generally.
Observability
Full traces of every agent decision. Replayable. Auditable. Critical for debugging and compliance.
Cost + budget controls
Per-agent budgets. Per-user limits. Model routing for cost. Alerts before bills spike. Production agents that don't bankrupt you.
Failure mode catalog
Each agent ships with documented failure modes and mitigations. Not 'we'll figure it out' — explicit, written, tested.
Multi-agent orchestration
When the problem benefits from multiple specialists. With clear handoffs, shared memory, and orchestrator patterns.
How we work
How an engagement starts.
- 01
Discovery call
30 minutes. What you're trying to ship, the constraints, the timeline.
- 02
Written proposal
We come back with scope, fixed quote, and timeline. No deck.
- 03
Kickoff
Week 1 we're embedded. Slack, weekly cadence, continuous deployment.
- 04
Ship
Working build in 4–8 weeks for most engagements.
- 05
Run
Optional retainer after launch. Same team. Same Slack channel.
Engagement
Engagement options.
We don't sell hours. We sell shipped work. The two shapes we offer:
Embedded
$12k/mo16 hrs/week
Embedded part-time in your team. For ongoing work or longer roadmaps.
- Senior engineer 16 hrs/week
- Same person every week
- Slack access
- Month-to-month after 90 days
Fractional CTO
$12k+/mo
If you need senior tech leadership across the whole engineering function — not just one role.
- Strategy + hands-on
- Hiring + leadership
- Architecture decisions
- Board support
If a marketplace developer at $80/hour fits your need better than us, we'll honestly tell you.
Built by us
The level of work you'd be getting.
FAQ
Same role, two terms. /hire/hire-ai-agent-developer is the same kind of work — we keep both pages because the keywords are searched separately. If you're hiring for production agents, both apply.
Yes — when the problem benefits from it. Usually we start with one agent and grow when delegation becomes useful (research → action, classification → triage → response). Premature multi-agent design adds complexity without value.
Layered: confidence thresholds, human-in-the-loop on destructive actions, sandboxed tool execution, budget caps, full audit logs, kill switches. We don't ship agents without all of these.
Yes — we have dedicated implementation pages for both. We also build from scratch on MCP + Vercel AI SDK + LangGraph for custom architectures.
Treated as adversarial inputs. Input sanitization, output moderation, structured outputs that constrain action space, sandboxing of tool calls. We assume the agent will see malicious input — design accordingly.
Yes — most clients keep us on for ongoing agent operations. Model upgrades, prompt tuning, new tools, scope expansions. Production agents need production ops.
Want to talk about your project?
Tell us what you're building or trying to figure out. We'll come back with what we'd do, how long it takes, and what it costs. No deck, no sales call.