Func Prog Podcast

I sit down with Don Syme, the creator of F#! We chat about language design, the "sweet spot" of type system expressivity, and how A.I. will affect the future of software development.

Topics covered:
The origin story of F#
Why types, data modeling, and functions beats type-level wizardry
The Object-Oriented tidal wave of the 90s
Designing programming languages for the real world
The case against type classes, and why simpler systems often win in real engineering.
How task-oriented AI workflows are reshaping developer productivity.
Why writing good constraints and guardrails may become as important as writing good code.
Will programming languages still matter?
Continuous AI for teams
Natural language as a programming model

What Kind of Programming is Natural Language Programming?
On Natural Language Programming
The Early History of F#
Bora's Law
On Type Classes
The Max-Abstraction Impulse, and Everything Else Wrong with Type-Level Genericity

In this episode I sit down with Adam Tornhill, founder of CodeScene, to talk about technical debt, Clojure, and why it's so hard to write good software.
Topics covered
From electrical engineering to software psychology
Why writing good code is so hard
The origin story of CodeScene
What technical debt really is, and why traditional metrics like cyclomatic complexity fall short
Code health: measuring what makes code hard to understand
Visualizing code to align engineering and management
The story behind Your Code as a Crime Scene
Making the business case for refactoring
Lean manufacturing vs. software: the visibility problem
Code quality and business impact (10× slower, 15× more defects)
AI-friendly code: when LLMs break (and why)
How technical debt amplifies AI failure rates
AI as an engineering force multiplier (or multiplier of chaos)
The future developer: AI team lead?
Why Adam chose Clojure for CodeScene
Immutability, REPLs, and iterative problem solving
Test-driven development as cognitive support
Performance myths in dynamic languages
Parallelism made simple with immutability
The real drawbacks of Clojure
Static vs dynamic typing in large codebases
Hiring in niche languages: small pool, strong engineers
Naming, domain modeling, and long-term code health
Links
AI-Ready Code: How Code Health Determines AI Performance
Code Red: The Business Impact of Code Quality
Your Code as a Crime Scene
Treat Your Code as a Crime Scene
Beating the Averages
CodeScene.com
AdamTornhill.com

In this episode, I talk to Giacomo Cavalieri, a core Gleam team member. We cover what makes Gleam special and why developers love it, and how it brings modern type safety to the battle-tested Erlang ecosystem. How did Gleam become Stack Overflow's 2nd most admired language in such a short time? Listen to the episode and find out!

Topics Covered
Gleam's design philosophy of simplicity and the "one way of doing things" approach
Statically typed functional programming with the Hindley-Milner type system
How Gleam targets the BEAM VM and JavaScript for full-stack development
The history of BEAM and OTP
Who uses Gleam in production
The Lustre framework for building web applications in Gleam
Integrating Gleam with OTP
How Gleam made it to 2nd Most Admired Language in the Stack Overflow 2025 Survey
How to speak at conferences
Why Gleam deliberately excludes type classes and traits
The future of Gleam
Links
Gleam.run
Gleam Language Tour
Gleam Roadmap
Gleam Case Studies
Giacomo Cavalieri's Website
Giacomo's Func Prog Conference Talk
Giacomo's GitHub
Giacomo's BlueSky
Giacomo's Twitch
Lustre Web Framework
Gleam OTP Library
Stack Overflow Developer Survey 2025
Func Prog Conference
Code BEAM Europe
GOTO Copenhagen
Lambda Days Conference
Strand Case Study
Uncover
The Zen of Python (PEP 20)
Paul Graham's Blub Paradox

In this episode, I sit down with Robert Kreuzer, co-founder and CTO at Channable, to hear what it's like using Haskell in production. You will hear the story of Channable, and how Haskell worked its way into their code base.

Topics covered:
How Channable got started
How pivoting from their initial idea made Channable a success
Using Haskell in production
What are the pros and cons of using Haskell?
Haskell VS Rust
Hiring for Haskell

Links:
Channable
Channable jobs
The origin story of Haskell at Channable
Effectful
David Christensen - Coding for Types
Robert Kreuzer on LinkedIn

What is the future of Haskell, program generation and AI? I sit down with Matthías Páll Gissurarson and try to figure this out, along with the optimal development setup... and of course, deadlifts!
Topics covered:
Haskell
Typed holes
Using AI for code generation
Lift weights, not just monads

Links:
Starting Strength
Pumping Iron
You come to me at runtime, to tell me the code you are executing does not compile
The Lambda Cube
Ghost in the Haskell
Matthias website
CSI: Haskell
Synthesis and Repair for Functional Programming: A Type- and Test-Driven Approach
The Spectacular paper
PropR: Property-Based Automatic Program Repair