Code Story: Insights from Startup Tech Leaders - S11 Bonus: Clayton Gentry, Podstock

Clayton Gentry has been digitally oriented his whole life. When he was younger, he was into photography and making videos with his friends and for school - either highlight videos for school events or promotional videos for businesses. He's always liked making things look good on a screen, and was attracted to the art of it - which, he attributes to his mother's genes. These days, he lives in Brooklyn, plays guitar, and likes to run in Prospect Park near his home.

Toward the end of 2022, Clayton and his co-founder, Michael, re-connected on starting something new. Given Michael had extensive industry knowledge in the podcast world, Clayton and he combined their super powers to take on the multi-platform nature of podcasting.

This is the creation story of Podstock.

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The Government Huddle with Brian Chidester - Breaking the Huddle: The State of Social Services – Navigating Change to Preserve Critical Programs (Part 3)

Andrew McClanahan, Senior Director at LexisNexis Risk Solutions for Government Relations rejoins for Part Three of the conversation around government program integrity and we tackle the urgent "so what" in today’s government assistance landscape — what can agencies actually do to strengthen their fraud, waste, and abuse defenses amid tightening budgets, AI-driven bot attacks, and mounting operational pressures? We also unpack practical, tech-enabled strategies for modernizing fraud prevention frameworks, streamlining verification processes, and improving both customer experience and staff retention.

Code Story: Insights from Startup Tech Leaders - S11 Bonus: David Asamu, Nesla

David Asamu grew up in Nigeria and got into technology early, through serving his community. He attended University, and continued his community efforts there, and was introduced to the joys of Python programming. Outside of tech, he spends time with his significant other and family. He enjoys soccer, whether it is watching over playing. When asked about food, he mentioned loving Nigerian delicacies, such as Jollof rice.

Previously, David was working at a fintech company. While he was there, he and his friends were observing the trends around AI - and they wanted to get more involved. So they got together and built something over the weekend... and eventually decided to advance AI through research.

This is the creation story of Nesla.

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Big Technology Podcast - Anthony Scaramucci: Elon Musk’s Trump Exit, Tim Cook’s Tariff Problem

Anthony Scaramucci is the founder and managing partner at SkyBridge Capital, and host of The Rest Is Politics US. Scaramucci joins Big Technology Podcast to talk about his brief experience as Trump's communication director, what derailed Elon Musk’s White House stint, the problems with Trump’s 'Big Beautiful Bill,' the state of the trade war, Tim Cook’s tariff troubles, bitcoin, and more. We also cover Long Island culture at the top of the show, if you’re into that. Tune in for a fast paced, fascinating look into the state of the global economy and the tech titans trying to ride it to results.

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Code Story: Insights from Startup Tech Leaders - S11 E2: Clément “Kero” Renault, Meilisearch

Clément "Kero" Renault wanted to be an architect when he was younger. During that time, he also learned about computers and built his first website - and he never stopped building. Funny story, he lost that first website cause it wasn't on Git. Outside of his professional life, he likes to draw, craft and to cook. He also enjoys video games, and mentioned Hidden Reign was his favorite game of all time, alongside the likes of Cyberpunk.

Seven years ago, Kero was in school, and he wanted to build a solid search experience, but not just a general search - one that indexed your data, and allowed you to have a "Google" just for your info. After winning a school hackathon, Kero and his mates wanted to take it to the next level.

This is the creation story of Meilisearch.

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The Stack Overflow Podcast - In a deterministic simulation, you can debug with time travel

Antithesis is an autonomous testing platform that finds bugs in your software with perfect reproducibility.

Connect with Will Wilson on Linkedin.

Congrats to user hannes neukermans whose question How can I do tag wrapping in Visual Studio Code? won them a Stellar Question badge.

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Python Bytes - #434 Most of OpenAI’s tech stack runs on Python

Topics covered in this episode:
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About the show

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Brian #1: Making PyPI’s test suite 81% faster

  • Alexis Challande
  • The PyPI backend is a project called Warehouse
  • It’s tested with pytest, and it’s a large project, thousands of tests.
  • Steps for speedup
    • Parallelizing test execution with pytest-xdist
      • 67% time reduction
      • --numprocesses=auto allows for using all cores
      • DB isolation - cool example of how to config postgress to give each test worker it’s on db
      • They used pytest-sugar to help with visualization, as xdist defaults to quite terse output
    • Use Python 3.12’s sys.monitoring to speed up coverage instrumentation
      • 53% time reduction
      • Nice example of using COVERAGE_CORE=sysmon
    • Optimize test discovery
      • Always use testpaths
      • Sped up collection time. 66% reduction (collection was 10% of time)
      • Not a huge savings, but it’s 1 line of config
    • Eliminate unnecessary imports
      • Use python -X importtime
      • Examine dependencies not used in testing.
      • Their example: ddtrace
        • A tool they use in production, but it also has a couple pytest plugins included
        • Those plugins caused ddtrace to get imported
        • Using -p:no ddtrace turns off the plugin bits
  • Notes from Brian:
    • I often get questions about if pytest is useful for large projects.
    • Short answer: Yes!
    • Longer answer: But you’ll probably want to speed it up
    • I need to extend this article with a general purpose “speeding up pytest” post or series.
    • -p:no can also be used to turn off any plugin, even builtin ones.
      • Examples include
        • nice to have developer focused pytest plugins that may not be necessary in CI
        • CI reporting plugins that aren’t needed by devs running tests locally

Michael #2: People aren’t talking enough about how most of OpenAI’s tech stack runs on Python

  • Original article: Building, launching, and scaling ChatGPT Images
  • Tech stack: The technology choices behind the product are surprisingly simple; dare I say, pragmatic!
    • Python: most of the product’s code is written in this language.
    • FastAPI: the Python framework used for building APIs quickly, using standard Python type hints. As the name suggests, FastAPI’s strength is that it takes less effort to create functional, production-ready APIs to be consumed by other services.
    • C: for parts of the code that need to be highly optimized, the team uses the lower-level C programming language
    • Temporal: used for asynchronous workflows and operations inside OpenAI. Temporal is a neat workflow solution that makes multi-step workflows reliable even when individual steps crash, without much effort by developers. It’s particularly useful for longer-running workflows like image generation at scale

Michael #3: PyCon Talks on YouTube

Brian #4: Optimizing Python Import Performance

  • Mostly pay attention to #'s 1-3
  • This is related to speeding up a test suite, speeding up necessary imports.
  • Finding what’s slow
    • Use python -X importtime <the reset of the command
    • Ex: python -X importtime ptyest
  • Techniques
    • Lazy imports
      • move slow-to-import imports into functions/methods
    • Avoiding circular imports
      • hopefully you’re doing that already
    • Optimize __init__.py files
      • Avoid unnecessary imports, heavy computations, complex logic
  • Notes from Brian
    • Some questions remain open for me
      • Does module aliasing really help much?
    • This applies to testing in a big way
      • Test collection imports your test suite, so anything imported at the top level of a file gets imported at test collection time, even if you only are running a subset of tests using filtering like -x or -m or other filter methods.
      • Run -X importtime on test collection.
      • Move slow imports into fixtures, so they get imported when needed, but NOT at collection.
  • See also:

Extras

Brian:

  • PEPs & Co.
    • PEP is a ‘backronym”, an acronym where the words it stands for are filled in after the acronym is chosen. Barry Warsaw made this one up.
    • There are a lot of “enhancement proposal” and “improvement proposal” acronyms now from other communities
  • pythontest.com has a new theme
    • More colorful. Neat search feature
    • Now it’s excruciatingly obvious that I haven’t blogged regularly in a while
      • I gotta get on that
    • Code highlighting might need tweaked for dark mode

Michael:

Joke: There is hope.

Talk Python To Me - #507: Agentic AI Workflows with LangGraph

If you want to leverage the power of LLMs in your Python apps, you would be wise to consider an agentic framework. Agentic empowers the LLMs to use tools and take further action based on what it has learned at that point. And frameworks provide all the necessary building blocks to weave these into your apps with features like long-term memory and durable resumability. I'm excited to have Sydney Runkle back on the podcast to dive into building Python apps with LangChain and LangGraph.

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Sydney Runkle: linkedin.com
LangGraph: github.com
LangChain: langchain.com
LangGraph Studio: github.com
LangGraph (Web): langchain.com
LangGraph Tutorials Introduction: langchain-ai.github.io
How to Think About Agent Frameworks: blog.langchain.dev
Human in the Loop Concept: langchain-ai.github.io
GPT-4 Prompting Guide: cookbook.openai.com
Watch this episode on YouTube: youtube.com
Episode #507 deep-dive: talkpython.fm/507
Episode transcripts: talkpython.fm

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The Government Huddle with Brian Chidester - 185: The One with the Fortinet Global CISO

Jim Richberg, Head of Cyber Policy and Global Field CISO at Fortinet rejoins the show for a timely discussion on the fast-evolving landscape of artificial intelligence and we unpack AI’s unprecedented energy demands, its implications on national infrastructure, and the critical cybersecurity considerations government agencies must navigate in this new era. Jim also shares his "Three Rules for Government Technology Transformation," and we explore why education and clear procurement strategies are vital to responsible AI rollout in public sector programs.

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