Code Conversations

The article "Product Management Is Dead" argues that artificial intelligence (AI) is rapidly changing the product management landscape.  AI is automating many previously manual tasks , such as strategy definition and document creation, leading to a  decentralized and accelerated workflow . The author suggests that successful product managers will  need to adapt by automating tasks, expan...

The YouTube video summarizes Google's prompt engineering course, emphasizing a five-step framework for effective prompt design: task, context, references, evaluate, and iterate . This framework can be remembered using the mnemonic "Tiny crabs ride enormous iguanas". The course also covers four methods for iterating on prompts , which include revisiting the prompting framework, simpli...

Customer Value, Customer Centricity, Product Success are some of the ultimate goals of an organisation. And to achieve them one of the focus area for an organisation is to ensure that the teams are setup and interacting efficiently to deliver customer value with speed. In this session, we will discuss how to define an efficient team topology for teams to deliver customer value. we will go through...

It seems that in our industry, many don’t know what to do with DevOps teams. QA team, we know about them. Software engineering teams, we know where to put them. But DevOps? There is a big gap between the leaders and how companies really practice it, like putting it as another team between Dev and Ops. In this video and the previous one, we demystified DevOps teams topologies. For the second video,...

Matthew Skelton, Founder at Conflux and co-author of Team Topologies, joins the community to discuss Untangling software delivery with Team Topologies, flow metrics, and careful decoupling The key predictive IT delivery metrics uncovered by the book Accelerate and the State of DevOps Reports - aka “DORA metrics” - point the way towards flow-centric operating models for every modern enterprise buil...

This video is a free preview from the 2h course "Platform as a Product" available on the Team Topologies Academy: https://bit.ly/3o5aLmt

Manuel Pais discusses how many organizations see Kubernetes as “the” platform, rather than just a technical foundation for a true internal platform. Successful Kubernetes adoption requires thinking about what a platform really means and learning which team structures and interactions work well. And evolve them over time. https://www.youtube.com/watch?v=Iu_T3X-bPqE

Recent research summarised in the book Accelerate points to a set of practices that lead to high software development organisation performance. Simultaneously, research from the Santa Fe institute on Complex Adaptive Systems over the last 20 years seems to point to a grand unified theory of organisational design. So have we cracked it? Do we now have the answer to the question: how do we create an...

Matthew Skelton and Manuel Pais - co-authors of the book Team Topologies - discuss the concept of a Thinnest Viable Platform (TVP) and what this means for organizations building and running modern software systems.

Savvy organisations are discovering the value of treating their internal platforms as products. But what does it mean to treat a “platform as a product”? What benefits does this give, and why would an organisation adopt this approach? In this talk, Manuel Pais, co-author of the book Team Topologies, explains why the platform-as-product approach can be a game-changer for organisations building and...

The "Engineering Room" is a monthly series of conversations with people who are influential in the software industry. In this episode Dave Farley, author of "Continuous Delivery", "Modern Software Engineering" and others, talks to Matthew Skelton co-author of one of the most significant software books of the last 10 years - “Team Topologies”, about the ingredients for long-term, viable, sustainabl...

What is a platform team, and how do you build effective platforms? Platforms are often an important part of the strategy to scale software development beyond small single teams. Dividing work up so that common behaviours and services can be shared, rather than every service team implementing their own version, is a big gain, but it can also be a big cost. Coupling between teams is one of the bigge...

Matthew and Manuel's excellent book Team Topologies described the challenges and proposed patterns for organizing teams effectively. We'll explore their ideas, what patterns are working, and how they might look on Flight Level 2 and 3. https://www.youtube.com/watch?v=ckGjOkMTGKo

AI agents are a type of compound AI system that uses a large language model (LLM) to control its logic. Compound AI systems combine models and other components to solve problems, and they are more adaptable and effective than models alone. Here are some key points about AI agents from the sources: Compound AI Systems: These systems combine different components, including models, programmatic eleme...

https://youtu.be/85RfazjDPwA?si=TM2RugT9QEd1UOZj Comprehensive Overview of PyTorch Tools for Scaling AI Models Scaling AI models often involves adding more layers to neural networks to enhance their ability to capture data nuances and execute complex tasks. However, this scaling process demands increased memory and computational power. To address these challenges, PyTorch offers tools like Distrib...

https://youtu.be/fJ40w_2h8kk?si=YILy9Od6YICopdFf PyTorch is an open-source framework that simplifies the process of building, training, and deploying machine learning and deep learning models. The "Py" signifies its integration with the popular Python programming language, making it easily accessible to the vast community of data scientists who favor Python. PyTorch streamlines the entire model de...

Back propagation is an algorithm that modifies the weights and biases of a neural network to reduce error and improve accuracy. The goal of back propagation is to minimize the difference between the network's output and the desired output. This is an iterative process that continues until the network can reliably produce the desired output. Neural networks consist of layers of interconnected neuro...

Zero-shot prompting asks a question without giving the LLM any other information. It can be unreliable because a word might have multiple meanings. For example, if you ask an LLM to "explain the different types of banks" it might tell you about river banks. Few-shot prompting gives the LLM an example or two before asking the question. This gives the LLM more context so it can give you a better ans...

Supervised learning uses labeled data, like a student learning with a teacher. Unsupervised learning uses unlabeled data and is more like self-study. Supervised learning knows the right answers in advance and aims for accuracy. It can classify data, like filtering spam, or predict values, like stock prices. Unsupervised learning finds hidden patterns on its own. Think about grouping similar custom...

Insurance companies can reduce the stress of car accidents for their customers by using AI to streamline the claims process. Using AI, an insurance company can set up an automated claims processing workflow so customers can provide basic information to begin the claims process immediately after an accident. Customers can also use their smartphones to gather information about the other party, docum...

A Restricted Boltzmann Machine (RBM) is a probabilistic graphical model used for unsupervised learning. RBMs help discover hidden structures in data, making them suitable for applications like video recommendation systems. An RBM consists of two layers: Visible Layer: This layer receives the input data. Hidden Layer: This layer represents features or classifications derived from the input data. Ev...

Knowledge graphs  are a powerful tool for organizing and understanding information. They consist of  nodes , which represent entities such as people, places, or things, and  edges , which represent relationships between those entities. Knowledge graphs can be used to answer questions, make predictions, and find connections between seemingly unrelated information. For example, they can help identif...

Random Forest is a machine learning model used for making predictions. It uses a collection of decision trees, each trained on a random subset of data, to enhance prediction accuracy. Decision trees are a simpler type of model that use a series of decisions to classify data. They are susceptible to problems like bias and overfitting. Imagine deciding whether to play golf. A decision tree might con...

Natural language processing (NLP)  is a field of artificial intelligence that enables computers to understand and process human language. This video from IBM Technology explains the basics of NLP by comparing human language to a computer's understanding. The video describes how NLP uses various techniques to translate unstructured text into structured data that computers can understand. It then hi...

Generative Adversarial Networks (GANs) are a type of unsupervised machine learning algorithm where two submodels, a generator and a discriminator, compete against each other. The generator creates fake samples, while the discriminator attempts to distinguish between real samples from a domain and fake samples from the generator. The adversarial nature of GANs lies in this competition. The generato...