Voice AI Agents

Anyone can demo a voice agent. Few can make one hold up in production.

Voice agents fail in ways text agents don't — they talk over people, go silent at the wrong moment, or can't recover from being interrupted. This track teaches the design and evaluation layer that separates a working demo from something you'd actually ship: turn-taking, quality measurement, and choosing the right way to build.

Book Lesson — 49€ See the framework

50 minutes, 1:1, online. Same calendar as the rest of my coaching.

A voice agent that works once is not the same as one that works.

Voice agents don't fail like normal software. They fail as bad conversation — cutting people off, going quiet, repeating themselves. Most tutorials stop at "it worked when I tried it." That's not the bar.

The demo bar
  • Works when I speak clearly and don't interrupt it
  • "Feels fast enough" is the only latency check
  • No plan for what happens when it mishears you
  • One happy-path conversation, never stress-tested
  • Picked a tool because a tutorial used it
The production bar
  • Measured against real interruption and noise conditions
  • Latency tracked as a number, not a feeling
  • A defined repair pattern for low-confidence moments
  • Tested across many runs, not one lucky take
  • Tool chosen for the use case, with reasons you can defend

Voice agents run on one loop. Getting it right is the whole job.

Every voice agent — however it's built — runs the same cycle, over and over, fast enough to feel like a conversation instead of a form.

1
Listen
Capture the user's audio in real time, continuously — not in one big chunk after they stop talking.
2
Understand
Turn speech into meaning, and work out when the person has actually finished their turn — the single hardest problem in voice UX, and the one that makes agents feel robotic when it's wrong.
3
Reason
Decide what to say or do. Often this starts before the user has even finished speaking — a well-built agent begins preparing a response early, and discards it cleanly if the person changes direction mid-sentence.
4
Respond & speak
Generate the reply and stream it back as speech — and stop instantly, mid-sentence if needed, the moment the person starts talking again. An agent that can't interrupt itself will never feel conversational.

These four stages don't run one after another — they overlap. That overlap is what makes a voice agent feel human instead of mechanical, and it's the first thing we'll take apart together.

Four ways to build one. Only one is usually right for you.

Most people either overbuild (hand-rolling infrastructure they don't need) or underbuild (a no-code tool that can't do what they actually want). The fix is knowing where you sit on this spectrum before you start.

Approach
What it is
Good fit if
DIY framework
e.g. LiveKit, Pipecat
You assemble your own speech, reasoning and synthesis components and write the orchestration yourself.
You need full control, proprietary models, or self-hosting — and have real engineering resources behind you.
Unified API
e.g. an end-to-end runtime
One real-time API handles speech and orchestration together, while you keep control over logic and model choice.
You want production performance without building streaming orchestration from scratch.
Managed platform
e.g. Vapi, Retell
A hosted platform with visual builders and pre-configured telephony for common use cases.
Speed to launch and minimal engineering matter most. This is where most of my students belong.
Enterprise suite
e.g. large CX platforms
Voice is one channel inside a broader, multi-channel customer experience system.
You're procuring for an organisation already committed to one vendor ecosystem.

On the diagnostic call, we work out where you actually sit — not where a tutorial assumes you sit.

How to know if it's actually good.

"It feels fast" isn't a metric. The Voice Agent Quality Index gives you three concrete numbers instead — you'll learn to track all three on anything you build.

I
Interruptions
How often the agent starts talking before the user has actually finished. High interruption rate is the fastest way to make an agent feel rude.
M
Missed responses
How often the agent fails to reply at all within a reasonable window. Silence reads as broken, not thoughtful.
L
Latency
Time from the user finishing their turn to the agent starting its reply. Sub-second is the bar production systems are held to.

What this track actually covers — and what it doesn't.

Most AI courses quietly oversell. I'd rather you know exactly what you're getting before you book.

You'll learn this
  • How to design the conversation itself — turn-taking, interruption handling, tone
  • How to pick the right build approach for your situation, and defend that choice
  • How to measure quality objectively instead of by feel
  • How to scope a first use case narrow enough to actually finish
  • Where consent, disclosure and EU data rules apply to what you're building
This needs an engineer
  • Telephony infrastructure — bridging phone networks, call routing
  • Low-level audio engineering — codecs, frame sizing, jitter buffers
  • Custom real-time orchestration written from scratch
  • Self-hosted or edge deployments

Who's already asking about this.

Two live examples of the kind of need this track exists for — described generally, without names.

Technical professional · career transition
Choosing Voice AI as a specialisation
A senior software engineer leaving a large employer, positioning Voice AI Agents as her differentiation lane going into a startup or consulting role — needs the vocabulary, evaluation framework and portfolio structure to prove it, not the engineering itself.
Business owner · outreach & sales
Evaluating a voice agent already in use
A business owner running a voice agent through a no-code platform, wanting an outside, structured quality analysis — is it actually good, or does it just feel fine to the person who built it?

Start with one call. Decide the rest after.

Same structure as the rest of my coaching — a paid diagnostic call first, no obligation to continue.

Diagnostic call
49€ · one-off · 50 minutes
  • Map what you're actually trying to build or evaluate
  • Place you correctly on the build-approach spectrum
  • Leave with a concrete, scoped first step
  • No obligation to continue
Book the call
Monthly partnership
From 300€ · per month
  • Regular 1:1 sessions building your first agent or evaluation framework
  • Written recap after every session
  • Adjusts as your scope becomes clearer
Discuss on the call
Voice agent audit
Defined in your diagnostic
  • An outside quality review of a voice agent already in production
  • Assessed against interruption, latency and missed-response benchmarks
  • For teams and owners, not a DIY checklist
Discuss on the call

Questions people ask first.

Do I need to know how to code?

No. I don't write code myself either — I direct AI to handle the technical layer, and that's exactly the orchestration skill this track teaches. If you're an engineer, this track sharpens your design and evaluation thinking; if you're not, it teaches you to direct someone who is.

Will I build a real voice agent in these sessions?

Where your use case fits a managed platform, yes, live in session. Where it needs custom telephony or infrastructure engineering, we scope it clearly and I help you brief the right engineer — see the "what this doesn't cover" section above.

I already have a voice agent — can you just review it?

Yes — that's the Voice Agent Audit option above. We assess it against concrete quality benchmarks instead of "does it feel okay."

What happens after the diagnostic call?

You get a written recap either way, including where you sit on the build-approach spectrum and a scoped first step — whether or not we continue working together.

One call tells you exactly where you stand.

50 minutes, 49€, and a clear next step — whether that's a session with me or a brief for an engineer.

Book Lesson — 49€ See who I work with

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