Question 1

What is an AI agent?

Accepted Answer

An AI agent is a software system that uses LLMs to perceive context, make decisions, and take actions - calling APIs, querying databases, or executing workflows without constant human input.

Question 2

How do you choose an agent architecture?

Accepted Answer

There is no one-size-fits-all stack. I evaluate your workflow, team, latency needs, and existing systems first - then pick the simplest approach that meets them. I have built agents with custom orchestration and off-the-shelf libraries, but I only add tooling when it genuinely fits the project.

Question 3

How long does AI agent development take?

Accepted Answer

MVP agents ship in 2 weeks on average. Production systems with evaluation and monitoring typically take 6–10 weeks on average depending on integration complexity.

Question 4

Can agents connect to my existing tools?

Accepted Answer

Yes. I integrate agents with CRMs, databases, Slack, email, and custom APIs via function calling, MCP servers, and webhook-based tools.

Question 5

How do you prevent agents from hallucinating?

Accepted Answer

I use RAG grounding, structured output schemas, evaluation datasets, guardrails, few shot prompts, and if necessary, human-in-the-loop checkpoints for high-stakes decisions.

Question 6

What is MCP and do you build MCP servers?

Accepted Answer

MCP (Model Context Protocol) is a standard for connecting LLMs to external tools and data sources. I build custom MCP servers so agents can securely access your databases, APIs, and internal systems with structured tool definitions.

Question 7

Can you deploy agents on our AWS or GCP infrastructure?

Accepted Answer

Yes. I deploy on AWS (Lambda, ECS, Bedrock), GCP (Cloud Run, Vertex AI), Azure (Functions, Container Apps), Vercel, or your existing Kubernetes cluster. Infrastructure choice depends on latency, scale, and your team's ops preferences.

Question 8

Do you build multi-tenant agent systems?

Accepted Answer

Yes. For SaaS products I implement tenant isolation for memory, tools, and vector namespaces - similar to how I architected BotWhisperer for multi-tenant RAG chatbots.

Question 9

How much does this cost for a startup?

Accepted Answer

I offer two options: hourly work at $35 - $55/hr depending on the complexity of your requirements, or a custom fixed-price quote after a free discovery call. The quote option is best when you have a defined scope and want a single number upfront.

Question 10

Do you sign NDAs and work with confidential data?

Accepted Answer

Yes. I routinely sign NDAs before reviewing proprietary code or data. Your documents, API keys, and business logic stay confidential. I can work within your existing security policies and VPC if required.

Question 11

How do we communicate during the project?

Accepted Answer

Weekly video demos plus async updates on Slack or email. You see working software every week, not status reports. I'm responsive across time zones - I've delivered for clients in 15+ countries.

Question 12

What is your payment structure?

Accepted Answer

For custom quotes: typically 30% upfront, 40% at midpoint, 30% on delivery. Hourly work is billed weekly or biweekly based on hours logged. Payments via bank transfer, PayPal, or platform escrow (Upwork/Fiverr) if you prefer.

Question 13

Do you provide post-launch support?

Accepted Answer

Yes. Every project includes a handoff period with documentation and knowledge transfer. Optional maintenance retainers cover bug fixes, model updates, and feature iterations after launch.

Question 14

Why hire a freelance AI engineer vs an agency?

Accepted Answer

You work directly with the person building your system - no account managers or junior devs passed off as seniors. Faster iteration, lower overhead, and 6+ years of hands-on production AI experience including published research.

AI Agent Development

Why teams get stuck

What you get

Pricing

Hourly rate

Custom quote

AI Agents - common questions