Sunday Morning Reading
13th April 2025
Lets kick things off with the Shopify CEO manifesto getting so much attention this week in its entirety
Team,
We are entering a time where more merchants and entrepreneurs could be created than any other in history. We often talk about bringing down the complexity curve to allow more people to choose this as a career. Each step along the entrepreneurial path is rife with decisions requiring skill, judgement and knowledge. Having Al alongside the journey and increasingly doing not just the consultation, but also doing the work for our merchants is a mindblowing step function change here.
Our task here at Shopify is to make our software unquestionably the best canvas on which to develop the best businesses of the future. We do this by keeping everyone cutting edge and bringing all the best tools to bear so our merchants can be more successful than they themselves used to imagine.
For that we need to be absolutely ahead .Reflexive Al usage is now a baseline expectation at Shopify Maybe you are already there and find this memo puzzling. In that case you already use Al as a thought partner, deep researcher, critic, tutor, or pair programmer. I use it all the time, but even I feel I'm only scratching the surface. It's the most rapid shift to how work is done that I've seen in my career and I've been pretty clear about my enthusiasm for it: you've heard me talk about Al in weekly videos, podcasts, town halls, and...Summit!
Last summer I used agents to create my talk, and presented about that. I did this as a call to action and invitation for everyone to tinker with Al, to dispel any scepticism or confusion that this matters at all levels. Many of you took up the call, and all of us who did have been in absolute awe of the new capabilities and tools that Al can deliver to augment our skills, crafts, and fill in our gaps.What we have learned so far is that using Al well is a skill that needs to be carefully learned by... using it a lot. It's just too unlike everything else. The call to tinker with it was the right one, but it was too much of a suggestion.
This is what I want to change here today. We also learned that, as opposed to most tools, Al acts as a multiplier. We are all lucky to work with some amazing colleagues, the kind who contribute 10X of what was previously thought possible. It's my favorite thing about this company. And what's even more amazing is that, for the first time, we see the tools become 10X themselves. I've seen many of these people approach implausible tasks, ones we wouldn't even have chosen to tackle before, with reflexive and brilliant usage of Al to get 100X the work done.
In my On Leadership memo years ago, I described Shopify as a red queen race based on the Alice in Wonderland story—you have to keep running just to stay still. In a company growing 20-40% year over year, you must improve by at least that every year just to re-qualify. This goes for me as well as everyone else.This sounds daunting, but given the nature of the tools, this doesn't even sound terribly ambitious to me anymore. It's also exactly the kind of environment that our top performers tell us they want. Learning together, surrounded by people who also are on their own journey of personal growth and working on worthwhile, meaningful, and hard problems is precisely the environment Shopify was created to provide.
This represents both an opportunity and a requirement, deeply connected to our core values of Be a Constant Learner and Thrive on Change. These aren't just aspirational phrases-they're fundamental expectations that come with being a part of this world-class team. This is what we founders wanted, and this is what we built.
Using Al effectively is now a fundamental expectation of everyone at Shopify. It's a tool of all trades today, and will only grow in importance. Frankly, I don't think it's feasible to opt out of learning the skill of applying Al in your craft; you are welcome to try, but I want to be honest I cannot see this working out today, and definitely not tomorrow. Stagnation is almost certain, and stagnation is slow-motion failure. If you're not climbing, you're sliding.
Al must be part of your GSD Prototype phase. The prototype phase of any GSD project should be dominated by Al exploration. Prototypes are meant for learning and creating information. Al dramatically accelerates this process. You can learn to produce something that other team mates can look at, use, and reason about in a fraction of the time it used to take.
We will add Al usage questions to our performance and peer review questionnaire. Learning to use Al well is an unobvious skill. My sense is that a lot of people give up after writing a prompt and not getting the ideal thing back immediately. Learning to prompt and load context is important, and getting peers to provide feedback on how this is going will be valuable.
Learning is self directed, but share what you learned. You have access to as much of the cutting edge Al tools as possible. There is chat.shopify.io, which we had for years now Developers have proxy., Copilot, Cursor, Claude code, all pre-tooled and ready to go. We'll learn and adapt together as a team.We'll be sharing Ws (and Ls!) with each other as we experiment with new Al capabilities, and we'll dedicate time to Al integration in our monthly business reviews and product development cycles. Slack and Vault have lots of places where people share prompts that they developed, like #revenue-ai-use-cases and #ai-centaurs.
Before asking for more Headcount and resources, teams must demonstrate why they cannot get what they want done using Al. What would this area look like if autonomous Al agents were already part of the team? This question can lead to really fun discussions and projects.
Everyone means everyone. This applies to all of us-including me and the executive team.
The Path Forward
Al will totally change Shopify, our work, and the rest of our lives. We're all in on this! I couldn't think of a better place to be part of this truly
unprecedented change than being here. You don't just get a front-row seat, but are surrounded by a whole company learning and pushing things forward together.
Our job is to figure out what entrepreneurship looks like in a world where Al is universally available. And I intend for us to do the best possible job
of that, and to do that I need everyone's help. I already laid out a lot of the Al projects in the themes this year- our roadmap is clear, and our
product will better match our mission. What we need to succeed is our collective sum total skill and ambition at applying our craft, multiplied by Al, for the benefit of our merchants.
-Tobi CEO Shopify (edited)
Google's new Agent2Agent (A2A) protocol rivals Anthropic's MCP. Politically motivated, A2A lets enterprise partners (Salesforce, SAP) keep data/workflow control. This standards war pits A2A's potential enterprise security appeal against MCP's strong developer momentum. Let the AI Agent protocol wars begin
https://www.koyeb.com/blog/a2a-and-mcp-start-of-the-ai-agent-protocol-wars
Google/DeepMind’s new Agent2Agent (A2A) protocol is the clearest sign yet, we’re moving from siloed agents to fully interoperable agent ecosystems.
While Anthropic’s Model Context Protocol (MCP) is about enriching input-output context between an app and a single model, A2A is about enabling autonomous agents to coordinate across distributed tasks, independent of their model provider.
This isn’t theoretical. It’s tactical.
Let’s say you have an AI agent that manages vendor contracts using Claude via MCP. It’s great at summarizing, redlining, and generating negotiation drafts. But what if that agent needs real-time pricing data from a separate agent tuned on financial models, or wants to route an approved deal to an execution agent tied into a company’s ERP system?
This is where A2A comes in.
It lets agents broadcast capabilities (via JSON Agent Cards), negotiate execution protocols, share multimodal artifacts (including audio or video), and dynamically update each other as long-running tasks evolve.
In short, MCP is vertical, app to model. A2A is horizontal, agent to agent. You’d use MCP for enhancing interaction with a model, and A2A to orchestrate fleets of models and agents across systems.
It’s the glue for swarms, autonomous, composable, and continuously adaptive.
Speaking of wars the battle for AI agents for Enterprise Investment Research has begun, my money is on AlphaSense
With the rapid advancement in Quantum Computing the word Grover is going to take on a lot more significance than a blue muppet….
https://en.m.wikipedia.org/wiki/Grover%27s_algorithm
GPT-4 is being retired
https://uk.pcmag.com/ai/157540/two-years-after-gpt-4-broke-the-internet-openai-is-quietly-killing-it
Hurrah for AI:
ChatGPT 4.5 passes Turing Test better than a human. Not really surprising it is far smarter than any human I have interacted with and I used to work in a team of AI PHD data scientists from the best universites in the world
https://www.independent.co.uk/tech/ai-turing-test-chatgpt-openai-agi-b2728930.html
Good to see Aussie start-up Canva doing well with a list of new features
Visual Suite 2.0 (or Visual Suite in One Design): Allows users to combine multiple design formats (like presentations, documents, social media assets, websites) into a single, unified project file.
Canva Sheets: Introduces native spreadsheet capabilities within Canva, competing with tools like Excel and Google Sheets. It includes:
AI Integration: Features like Magic Write (for data generation), Magic Insights (for automated analysis and chart ideas), and Magic Formulas (translating plain language into spreadsheet functions).
Data Connectors: Integrates data from external platforms like Google Analytics, HubSpot, Snowflake, and Statista.
Magic Studio at Scale: Leverages Canva Sheets data to apply AI tools (like translation or resizing) across multiple pieces of content simultaneously.
Magic Charts: Integrates sophisticated data visualisation capabilities (from their Flourish acquisition) allowing dynamic charts linked to Sheets data.
Canva Code: Enables users to generate functional, interactive widgets (like calculators or quizzes) using simple text prompts, which can then be embedded into Canva designs.
Conversational AI (Canva AI): A new chat interface allowing users to generate initial designs or images by describing what they want (even uploading references) and refine them through conversation before final editing in the main editor. This also powers enhanced photo editing features.
In case you were wondering:
Very cool, new start-up Rescale provides a cloud platform for high performance computing (HPC), enabling companies to accelerate engineering simulations, AI model training, and complex R&D workflows through automated cloud management and infrastructure access.
This may explain why the Llama 4 models despite having native multimodality were such a flop.
https://fortune.com/2025/04/10/meta-ai-research-lab-fair-questions-departures-future-yann-lecun-new-beginning/
