What’s happening with the latest releases of large language models? Is the industry hitting the edge of the scaling laws, and do the current benchmarks provide reliable performance assessments? This week on the show, Jodie Burchell returns to discuss the current state of LLM releases.

The most recent release of GPT-5 has been a wake-up call for the LLM industry. We discuss how the current scaling of these systems is reaching a diminishing edge. Jodie also shares how many AI model assessments and benchmarks are flawed. We also take a sober look at the productivity gains from using these tools for software development within companies.

We discuss how newer developers should consider additional factors when looking at the current job market. Jodie digs into how economic changes and rising interest rates are influencing layoffs and hiring freezes. Then we share a wide collection of resources for you to continue exploring these topics.

This episode is sponsored by InfluxData.

Course Spotlight: Exploring Python Closures: Examples and Use Cases

Learn about Python closures: function-like objects with extended scope used for decorators, factories, and stateful functions.

Topics:

00:00:00 – Introduction
00:03:00 – Recent conferences and talks
00:04:18 – What’s going on with LLMs?
00:06:06 – What happened with the GPT-5 release?
00:08:14 – Simon Willison - 2025 in LLMs so far
00:09:00 – How did we get here?
00:10:37 – OpenAI’s and scaling laws
00:12:25 – Pivoting to post-training
00:16:01 – Some history of AI eras
00:17:54 – Issues with measuring performance and benchmarks
00:22:19 – Chatbot Arena
00:24:06 – Languages are finite
00:26:22 – LLMs and the illusion of humanity
00:30:41 – Sponsor: InfluxData
00:31:34 – Types of solutions to move past these limits
00:36:57 – Does AI actually boost developer productivity?
00:44:19 – Agentic Al Programming with Python
00:48:02 – Results of non-programmers vibe coding
00:50:18 – Back to the concept of overfitting
00:52:52 – The money involved in training
00:56:50 – Video Course Spotlight
00:58:21 – Deepseek and new methods of training
01:01:02 – Quantizing and fitting on a local machine
01:04:48 – The layoffs and the economic changes
01:10:32 – AI implementation failures
01:21:01 – Don’t doubt yourself as a developer
01:24:06 – What are you excited about in the world of Python?
01:25:39 – What do you want to learn next?
01:26:42 – What’s the best way to follow your work online?
01:27:04 – Thanks and goodbye

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Show Links:

EuroPython 2025 - July 14th-20th 2025 - Prague, Czech Republic & Remote
Episode #232: Exploring Modern Sentiment Analysis Approaches in Python
GPT-5: Overdue, overhyped and underwhelming. And that’s not the worst of it.
GPT 5’s Rocky Launch Highlights AI Disillusionment - IEEE Spectrum
2025 in LLMs so far, illustrated by Pelicans on Bicycles — Simon Willison
Attention is All You Need - Google
Scaling laws for neural language models - OpenAI
What if AI Doesn’t Get Much Better Than This? - Cal Newport
Hiltzik: AI hype is fading fast - Los Angeles Times
Does AI Actually Boost Developer Productivity? (100k Devs Study) - Yegor Denisov-Blanch, Stanford - YouTube
Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity - METR
Amazon Cloud Chief: Replacing Junior Staff With AI Is ‘Dumbest’ Idea - Business Insider
20 LLM evaluation benchmarks and how they work
MMLU - Measuring Massive Multitask Language Understanding
HellaSwag: Can a Machine Really Finish Your Sentence?
Mechanical Turk - Wikipedia
Amazon Mechanical Turk
Chatbot Arena - LMArena
LLMs Can’t Reason - The Reversal Curse, The Alice In Wonderland Test, And The ARC - AGI Challenge - CustomGPT
Mirror, mirror: LLMs and the illusion of humanity - Jodie Burchell - NDC Oslo 2024 - YouTube
Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lens
Context Rot: How Increasing Input Tokens Impacts LLM Performance - YouTube
Does AI Actually Boost Developer Productivity? (100k Devs Study) - Yegor Denisov-Blanch, Stanford - YouTube
AWS CEO says no more programmers in 2 years - Tech Industry - Blind
MIT report: 95% of generative AI pilots at companies are failing - Fortune
Agentic Al Programming with Python - Talk Python To Me Podcast
Vibe coding through the GPT-5 mess - The Verge
Overfitting - Wikipedia
Andrej Karpathy - Busy Person’s Intro to LLMs - YouTube
AI Isn’t Taking Your Job – The Economy Is - Andrew Stiefel
Commonwealth Bank backtracks on AI job cuts, apologizes for ‘error’ as call volumes rise - ABC News
Klarna CEO Reverses Course By Hiring More Humans, Not AI | Entrepreneur
Has Duolingo Lost Its Streak? - Matt Jones - Medium
McDonald’s removes AI drive-throughs after order errors
OpenAI Usage Plummets in the Summer, When Students Aren’t Cheating on Homework
What Happened When I Tried to Replace Myself with ChatGPT in My English Classroom - Literary Hub
Learning to code in the age of AI — Sheena O’Connell - YouTube
Jodie Burchell - The JetBrains Blog
Jodie Burchell’s Blog - Standard error
Jodie Burchell (@t-redactyl.bsky.social) — Bluesky
Jodie Burchell 🇦🇺🇩🇪 (@t_redactyl@fosstodon.org) - Fosstodon
JetBrains: Essential tools for software developers and teams

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