Category: 3-SometimeTechTalk

Ryan welcomes Assaf Elovic, head of AI at monday.com, to discuss creating AI tools that users will actually adopt, how they created their Monday Sidekick agent with the user experience in mind, and the opportunities that AI creates for better productivity and more efficiency.

Episode notes:

monday.com is a work management platform that allows you to plan and execute work across departments with a unified, AI-first product suite.

Connect with Assaf on LinkedIn and Twitter.  

Congrats to Populist badge winner Vilx-, who received the badge for their answer to How do you provide a default type for generics?.

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Today, we have a special episode correlated with Fraud awareness week, and brought to you by our friends at SEON - the command center for fraud prevention and AML compliance. SEON connects first party data signals to show you what other solutions can't - by enriching data, understanding context, and taking action from one place... to prevent fraud.

In this episode, we are talking with Husnain "HB" Bajwa, SVP of Product & Risk Solutions. He has been a fraud and risk leader for 30+ years, and leads innovation in fraud prevention and compliance at SEON. HB is going to touch on important topics in the fraud detection and prevention space, such as AI, regulatory pressures, and the perspectives of startups that can get them into trouble.

Questions:

• You’ve spent a lot of time in the world of fraud and compliance. What first drew you to solving these kinds of problems?
• Startups often focus on growth first and worry about fraud later. What’s the hidden risk in that mindset?
• Why do you believe fraud prevention and AML compliance are converging, and what are the benefits of them living in the same system?
• AI gets talked about a lot, but in your view, what are the real, practical ways it’s improving fraud and AML work today?
• We’re seeing more regulatory pressure globally. How can organizations prepare for 2026 to ensure they are taking a risk-based approach to compliance?
• I know your team’s been working on some big innovations, including a new compliance suite built on top of your fraud prevention stack and new AI-driven tools. How are these helping investigators connect the dots faster and uncover hidden relationships, especially when it comes to complex cases?
• What advice would you give to early-stage startups that might think they’re ‘too small’ to be targeted by fraudsters?

Links

• https://seon.io/
• https://www.linkedin.com/in/hbajwa/

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Topics covered in this episode:

• Possibility of a new website for Django
• aiosqlitepool
• deptry
• browsr
• Extras
• Joke

Watch on YouTube

About the show

Sponsored by us! Support our work through:

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Connect with the hosts

• Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky)
• Brian: @brianokken@fosstodon.org / @brianokken.bsky.social
• Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky)

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Brian #1: Possibility of a new website for Django

• Current Django site: djangoproject.com
• Adam Hill’s in progress redesign idea: django-homepage.adamghill.com
• Commentary in the Want to work on a homepage site redesign? discussion

Michael #2: aiosqlitepool

• 🛡️A resilient, high-performance asynchronous connection pool layer for SQLite, designed for efficient and scalable database operations.
• About 2x better than regular SQLite.
• Pairs with aiosqlite
• aiosqlitepool in three points:
  • Eliminates connection overhead: It avoids repeated database connection setup (syscalls, memory allocation) and teardown (syscalls, deallocation) by reusing long-lived connections.
  • Faster queries via "hot" cache: Long-lived connections keep SQLite's in-memory page cache "hot." This serves frequently requested data directly from memory, speeding up repetitive queries and reducing I/O operations.
  • Maximizes concurrent throughput: Allows your application to process significantly more database queries per second under heavy load.

Brian #3: deptry

• “deptry is a command line tool to check for issues with dependencies in a Python project, such as unused or missing dependencies. It supports projects using Poetry, pip, PDM, uv, and more generally any project supporting PEP 621 specification.”
• “Dependency issues are detected by scanning for imported modules within all Python files in a directory and its subdirectories, and comparing those to the dependencies listed in the project's requirements.”

• Note if you use project.optional-dependencies

  [project.optional-dependencies]
  plot = ["matplotlib"]
  test = ["pytest"]
  

• you have to set a config setting to get it to work right:

  [tool.deptry]
  pep621_dev_dependency_groups = ["test", "docs"]
  

Michael #4: browsr

• browsr 🗂️ is a pleasant file explorer in your terminal. It's a command line TUI (text-based user interface) application that empowers you to browse the contents of local and remote filesystems with your keyboard or mouse.
• You can quickly navigate through directories and peek at files whether they're hosted locally, in GitHub, over SSH, in AWS S3, Google Cloud Storage, or Azure Blob Storage.
• View code files with syntax highlighting, format JSON files, render images, convert data files to navigable datatables, and more.

Extras

Brian:

• Understanding the MICRO
• TDD chapter coming out later today or maybe tomorrow, but it’s close.

Michael:

• Peacock is excellent

Joke: I will find you

Gil Luria is the head of technology research at D.A. Davidson. Luria joins Big Technology Podcast for a special Friday edition special report digging into the AI bubble, or whatever term you'd like to use for the questionable investment decisions in AI today. We cover all the bad stuff: debt, depreciation, and losses. We talk about Michael Burry's bet against the technology and why he might be right, and how OpenAI should play this to optimize its potential. Tune in for a comprehensive edition looking at the risks of the AI trade, and what happens from here.

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Ryan welcomes Benjamin Klieger, lead engineer at Groq, to explore the infrastructure behind AI agents, how you can turn a one-minute agent into a ten-second agent, and how they used fast inference and effective evals to build their efficient and reliable Compound agent. 

Episode notes: 

Groq delivers fast, low-cost inference using their custom-designed LPU, the first chip built for inference. Check out their agent, Compound, which can search the web and run code.

Connect with Benjamin on LinkedIn and X. 

Congrats to user Bart Kiers for winning a Stellar Answer badge on their response to Regular expression to match a line that doesn't contain a word. 

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Praveen Ghanta recently turned 47 and started to look at the things he wanted to do - but potentially couldn't do in the future. He's married with 3 teenage kids, and has been into running for quite some time. So much so, that he attempted to run a 5 minute mile... and almost made it. Also, he recently signed up for soccer classes, after having been beat by some eighth grade kids, who helped him realize he needed training in his ball handling skills.

In his prior startup, Praveen and his team stumbled upon a new approach to hiring that fueled the building of this startup, all the way through exit. After that success, he decided to make this approach available to others, and form a business around this very thing - fractional talent for your startup.

This is the creation story of Fraction and DevHawk.

Sponsors

• Vention
• CodeCrafters helps you become a better engineer by building real-world, production-grade projects. Learn hands-on by creating your own Git, Redis, HTTP server, SQLite, or DNS server from scratch. Sign up for free today using this link and enjoy 40% off.
• Full Scale
• Paddle.com
• Sema Software
• PropelAuth
• Postman
• Meilisearch

Links

• https://www.hirefraction.com/
• https://www.devhawk.ai/
• https://www.linkedin.com/in/pghanta/

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In this episode of Leaders of Code, Stack Overflow CEO Prashanth Chandrasekar chats with Ramprasad Rai, VP of Platform Engineering at JPMorgan Chase & Co., about the unique challenges of implementing AI in an enterprise environment. They discuss how organizations can balance AI-driven productivity with strict compliance and security requirements by leveraging a community-driven knowledge system that grounds probabilistic AI tools in internal, trusted expertise.

The discussion also:

• Explores why AI models often hallucinate in enterprise environments due to a lack of internal context. 
• Highlights how Stack Overflow’s structured Q&A data provides ideal fine-tuning material for the next generation of AI models.

Notes

• Connect with Ramprasad Rai on LinkedIn.

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Mustafa Suleyman is the CEO of Microsoft AI and the head of the company’s new superintelligence team. Suleyman joins Big Technology to discuss Microsoft’s push toward “humanist superintelligence” and what changes after its latest OpenAI deal. Tune in to hear whether LLMs can get us there, how self-improving systems might work safely, and what power, data, and memory advancements mean for progress. We also cover Microsoft’s strategy shift to AI self-sufficiency, the economics of frontier models (including price pressure and commoditization), world-model and robotics questions, and the rise of personalized AI companions. Hit play for a candid, technical, and forward-looking conversation about where Microsoft—and AI—are headed next.

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Today, we are another episode in our series, sponsored by our good friends at Railsware. Railsware is a leading product studio with two main focuses - services and products. They have created amazing products like Mailtrap, Coupler and TitanApps, while also partnering with teams like Calendly and Bright Bytes. They deliver amazing products, and have happy customers to prove it.

In this series, we are digging into the company's methods around product engineering and development. In particular, we will cover relevant topics to not only highlight their expertise, but to educate you on industry trends alongside their experience.

In today's episode, we are speaking with Nika Tamayo Flores, Product Lead at Railsware, specifically for the Coupler product. She's been leading complex data-driven products for over eight years, and will enlighten us on conversational analytics, and how they can change a data focused product.

Questions:

• Before we jump to the topic, let’s define what exactly conversational analytics is. How does it differ from traditional dashboard-based data analysis?
• You’ve been integrating AI capacities into Coupler, Railsware’s product focused on data analytics. How would you describe data analytics in pre-AI and AI era?
• What were the key challenges to embedding conversational analytics into Coupler?
• And what’s the result? You’ve already released AI Insights – how do they transform user experience for data exploration?
• How do you ensure conversational analytics provides accurate and reliable insights?
• How does conversational analytics change who can be a "data user" in an organization?
• What's the learning curve like for organizations adopting conversational analytics?
• Where do you see conversational analytics heading - will it eventually replace traditional BI tools, or complement them?

Links

• https://railsware.com/
• https://www.linkedin.com/in/veronica-tamayo-flores/
• https://coupler.io

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