Every line of code is a decision, and every programming language encodes a philosophy. In The Programming Languages Podcast, Lucas and Luna move past syntax flame wars to examine the actual trade-offs behind Python, Rust, JavaScript, and the modern coding stack. Each episode dissects a specific language feature, framework choice, or ecosystem shift — from Rust's borrow checker and memory safety guarantees to JavaScript's type system evolution with TypeScript, and Python's dominance in machine learning versus its performance bottlenecks. They ground every discussion in real-world benchmarks, open-source projects like Deno and PyPy, and case studies from companies that bet on one language over another. Lucas brings the reporter's instinct for clarity and hard numbers; Luna tests those findings with the engineer's skepticism and hands-on experience. You will walk away understanding not just what a language does, but why it was designed that way, and when you should — or shouldn't — use it
Pitch Analysis
Required Pod Score for this show. PitchCentric checks your profile against host openness, topical fit, and audience signals before you generate a pitch.
Contact path
Verified email
Booking probability
35%
Guest openness
Selective
Verified email on file
80/100
Required Score
Sign up to generate a grounded pitch for The Programming Languages Podcast with Fexingo: Python, Rust, JavaScript, and Modern Coding.
What is The Programming Languages Podcast with Fexingo: Python, Rust, JavaScript, and Modern Coding?
The Programming Languages Podcast with Fexingo: Python, Rust, JavaScript, and Modern Coding is a business podcast hosted by Fexingo, with 155 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.
About the host
Fexingo hosts The Programming Languages Podcast with Fexingo: Python, Rust, JavaScript, and Modern Coding, a business show with 155 episodes published.
Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.
Episode #159
Why D is the Underrated Systems Language of 2026
Aug 18, 202610 minS4
In this episode of The Programming Languages Podcast, Lucas and Luna explore why D, the systems programming language that's been around for over two decades, is quietly becoming the go-to choice for performance-critical applications in 2026. They dive into D's unique blend of C-like performance with modern productivity features, from its powerful metaprogramming to its garbage collector that can be turned off. Using concrete examples like a fintech startup's order-matching engine and a game studio's internal tools, they discuss why D's compile-time function evaluation and template system give it an edge over C++, Rust, and Go for certain workloads. They also tackle D's smaller ecosystem and community, acknowledging the trade-offs. If you're a developer looking for a language that balances low-level control with high-level expressiveness, this episode offers a fresh perspective on a hidden gem that's gaining traction beyond its niche. #DLanguage #SystemsProgramming #Performance #Metaprogramming #CompileTime #CPlusPlusAlternative #RustAlternative #GarbageCollection #Fintech #GameDev #OpenSource #DeveloperTools #ProgrammingLanguages #Technology #FexingoBusiness #BusinessPodcast #TechPodcast #Coding Keep every episode free: buymeacoffee.com/fexingo
In this episode, Lucas and Luna explore how RISC-V, the open-source instruction set architecture, is moving from hobbyist curiosity to a serious contender in data centers and embedded systems. They trace its journey from a 2010 Berkeley project to a 2026 landscape where hyperscalers are designing custom RISC-V silicon, and start-ups like Ventana Microsystems are pushing high-performance implementations. They discuss the economics of open hardware, the role of the RISC-V International foundation, and why software developers should care about a new ISA. With examples like NVIDIA's use of RISC-V microcontrollers in GPUs and Google's involvement, they make the case that RISC-V could disrupt the dominance of x86 and Arm. The episode also touches on the challenges of software ecosystem maturity and the potential for fragmentation. If you are a developer wondering what to learn next, this conversation offers a clear-eyed look at whether RISC-V is a passing trend or a foundational shift. #RISC-V #OpenSourceHardware #InstructionSetArchitecture #ChipDesign #Semiconductors #DataCenter #EmbeddedSystems #VentanaMicrosystems #NVIDIA #Google #Berkeley #Technology #FexingoBusiness #BusinessPodcast #TechTrends #FutureOfComputing #HardwareStartups #ISA Keep every episode free: buymeacoffee.com/fexingo
In this episode of The Programming Languages Podcast, Lucas and Luna explore a surprising twist in the AI world: R, the decades-old statistical language, is making a comeback. They trace R's origins at Bell Labs, its dominance in academic statistics, and its recent resurgence fueled by the need for robust statistical modeling alongside machine learning. With the rise of large language models, developers are rediscovering R's powerful data frame, dplyr, and ggplot2 for data analysis and visualization. Lucas and Luna discuss how R's ecosystem, including tidyverse and RStudio, offers a unique blend of statistical rigor and now AI integration, with tools like tidymodels bridging the gap between classical stats and modern ML. They also examine the challenges R faces, such as performance issues and a steep learning curve, and how new packages like Arrow and duckdb are addressing them. The episode argues that R's statistical foundation is becoming a crucial differentiator in an AI-driven world, making it a language worth revisiting. Tune in for a fresh perspective on R's role in the future of data science. #RProgramming #DataScience #AI #Statistics #Tidyverse #RStudio #MachineLearning #DataVisualization #BusinessPodcast #Technology #Programming #Coding #FexingoBusiness #BusinessPodcast #TechTrends #DataAnalysis #RStats #StatisticalModeling Keep every episode free: buymeacoffee.com/fexingo
Why Gleam Is the Functional Language for Reliable Systems
Aug 15, 202610 minS4
In this episode, Lucas and Luna dive into Gleam, a statically typed functional language that's been quietly gaining traction among developers building reliable, concurrent systems. They explore how Gleam's Erlang heritage brings battle-tested fault tolerance to modern web backends, why its type system catches bugs before they reach production, and how its approach to pattern matching and immutability simplifies complex logic. The hosts discuss Gleam's growing ecosystem, including its web framework Wisp, and compare it to TypeScript and Rust for building resilient services. They also touch on Gleam's unique position in the BEAM ecosystem, offering a safe entry point for developers unfamiliar with Erlang's syntax. Along the way, they share practical examples of how Gleam improves developer experience and reduces runtime surprises, and they examine why companies are starting to adopt it for critical systems. The episode wraps with a look at whether Gleam could become a mainstream choice for cloud-native development. Tune in for a clear, no-hype breakdown of a language that's making reliability cool again. #GleamLang #FunctionalProgramming #BEAM #Erlang #TypeSafety #WebDevelopment #CloudNative #DeveloperExperience #Concurrency #Wisp #ReliableSystems #PatternMatching #Immutability #ProgrammingLanguages #TechPodcast #FexingoBusiness #BusinessPodcast #Technology Keep every episode free: buymeacoffee.com/fexingo
Why Haskell Is the Hidden Gem of Financial Software
Aug 14, 20269 minS4
In this episode, Lucas and Luna explore why Haskell, a language often dismissed as academic, is quietly powering critical financial software. They start with a concrete anchor: the 2013 Knight Capital incident, where a flawed software deployment caused a $440 million loss in 45 minutes — a failure that Haskell's type system could have prevented. They discuss how hedge funds and banks use Haskell for high-assurance trading systems, citing companies like Standard Chartered and the cryptocurrency exchange Cardano. Lucas explains key concepts like pure functions, immutability, and the Maybe type, showing how they eliminate entire categories of bugs. Luna pushes back on Haskell's steep learning curve and small talent pool, and they debate whether its benefits justify the costs. The episode concludes with a look at how Haskell's principles are influencing mainstream languages and what that means for the future of programming. Listeners will come away understanding why some of the world's most risk-averse organizations choose Haskell — and why it might be worth learning, even if they never write it in production. #Haskell #FunctionalProgramming #FinancialSoftware #ProgrammingLanguages #TechPodcast #SoftwareEngineering #TypeSystems #KnightCapital #StandardChartered #Cardano #PureFunctions #Immutability #MaybeType #HighAssurance #Technology #FexingoBusiness #BusinessPodcast #Coding Keep every episode free: buymeacoffee.com/fexingo
Every question we get asked before someone starts their trial.
If you have a concern about deliverability, AI quality, data privacy, or whether this will actually work for your specific situation, it's probably answered below.
What is the difference between Founder Solo and Founder Pro?
Founder Solo gives you 50 AI pitches per month using the credit model (Standard pitches cost 1 credit, Enriched pitches cost 2). Founder Pro raises that to 200 credits per month and adds full Booking Probability access, unlimited Magic Match, Apollo enrichment credits, and data export capabilities. Both plans use the same credit system, so you can stretch your monthly budget further by using Standard-mode drafting.
How do agency tiers work?
Agency tiers have no base fee. You pay per managed client and per talent profile. Agency Standard is $199 per client per month; Agency Pro is $399 per client per month. Both add $39 per talent profile per month. Your own team's user seats are always free.
What is a talent profile?
A talent profile represents one person (founder, executive, or spokesperson) you are booking onto podcasts. It includes their bio, topics, headshots, and outreach history. Team plans include 5 profiles; agency plans are pay-as-you-go.
Can I switch plans later?
Yes, at any time. Upgrades take effect immediately; downgrades apply at the end of the current billing period. Contact support if you need help migrating between plan families.
Do you offer a free trial?
Every paid plan includes a 15-day free trial. Your card is saved at signup but you will not be charged until day 16. Cancel any time from your dashboard.
What happens if I cancel?
You keep access until the end of your current billing period. No charges after that. Your data is retained for 30 days in case you reactivate.
Is the 20% annual discount automatic?
Yes. Select Annual on the pricing toggle and the discounted price is applied automatically at checkout. The annual price shown is the full year cost.
What if I have more than 50 profiles or 20 clients?
That is our Enterprise tier. Contact our sales team and we will build a custom plan with volume pricing, a dedicated account manager, and SLA guarantees.