Most Companies Test Too Late
By the time most companies realize their AI agent doesn't work, they've already paid for it.
The builder is gone. The scope is murky. The agent hallucinates in production, loops on edge cases, or fails silently when it hits an API it wasn't designed for.
Testing after the fact is expensive. Testing before you hire costs you a few hours and can save you tens of thousands of dollars.
Here's how to do it right.
Step 1: Test the Proposal, Not Just the Resume
Before you review a builder's portfolio, evaluate how they respond to your brief.
A strong builder will ask clarifying questions you didn't think to answer. They'll flag ambiguity in your scope. They'll tell you what won't work and why — before you pay them to find out.
Red flags in a proposal:
- Promises everything in the first draft with no questions asked
- Doesn't mention failure modes, edge cases, or error handling
- Quotes a flat price without seeing your data or APIs
- Uses buzzwords without explaining architecture choices
Green flags:
- Asks about your data format, volume, and freshness
- Mentions specific frameworks (LangGraph, CrewAI, AutoGen) and explains why they'd choose one over another
- Proactively scopes what's out of scope
- References how they'd handle rate limits, timeouts, and retries
The proposal is a free sample of their thinking. Use it.
Step 2: Run a Paid Scoping Session First
Don't award a full build contract to a builder you've never worked with. Instead, pay them for 3–5 hours to scope the project.
At the end, you should have:
- A clear technical architecture diagram
- Identified integrations and their complexity
- A risk register with mitigation plans
- A realistic timeline and cost estimate
If they can't deliver this in a scoping session, they can't deliver the build.
What to pay: $250–$750 for 3–5 hours of scoping from a qualified builder. This is cheap insurance.
Step 3: Stress-Test the Prototype
If a builder delivers a prototype, don't just demo the happy path. Run it through scenarios it wasn't designed for.
Tests to run:
Input boundary tests
- Feed it malformed inputs (empty fields, wrong types, unicode edge cases)
- Give it inputs that are 10x larger than expected
- Provide inputs that are ambiguous or contradictory
Edge case coverage
- What happens when a required API is down?
- What happens when the user asks for something outside the agent's scope?
- What does the agent do when it doesn't know the answer?
Loop and recursion tests
- Can the agent get stuck in a loop? Trigger the condition and watch it.
- Does it have a max-iteration safeguard?
Output validation
- Is every output validated before it's acted on?
- Can the agent produce outputs that break downstream systems?
A well-built agent handles these gracefully. A rushed agent breaks, loops, or silently returns garbage.
Step 4: Check the Observability Setup
You cannot manage what you cannot see. Before you accept a delivery, ask:
- Is there logging at every decision point?
- Can you see why the agent made a specific choice?
- Are there alerts for failures, timeouts, and anomalies?
- Is there a way to replay a failed run for debugging?
If the builder hasn't built in observability, assume they'll be unavailable when things break. Because they will break.
Acceptable tools: LangSmith, Langfuse, Arize, custom logging to your data warehouse.
Not acceptable: "It worked in my testing."
Step 5: Define Acceptance Criteria Before You Pay
This is the step most companies skip — and the one that causes the most disputes.
Before the project starts, write down exactly what "done" looks like:
- Success rate on a defined test set (e.g., 95% accuracy on 100 labeled inputs)
- Latency threshold (e.g., p95 under 5 seconds)
- Specific failure modes that must be handled
- Integration tests passing against your staging environment
Share this document with the builder and get their sign-off. If they push back on specific criteria, that's valuable signal — either they're being realistic about what's possible, or they're trying to lower the bar so they can pass.
Either way, you learn something important before you're locked in.
The Fastest Signal: Ask About a Past Failure
Ask every builder you're evaluating: "Tell me about an AI agent project that didn't go as planned. What happened and what did you do?"
Builders who answer this well — specifically, with humility and detail — are builders who learn. Builders who claim everything always goes smoothly are builders who aren't being honest with you.
You want someone who's been tested by reality. Because your production environment will test them too.
Summary: Your Pre-Hire Testing Checklist
- Evaluate the proposal for thinking quality, not just credentials
- Run a paid scoping session before committing to the full build
- Stress-test prototypes against edge cases and failure scenarios
- Verify observability setup before accepting delivery
- Define acceptance criteria in writing before work begins
- Ask about past failures in every interview
A builder who passes these tests is a builder worth hiring.
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