Ed Dowding 🌍

Every ~3 months between now 2050 is one per cent of the available to build a net-zero economy and avert a catastrophe for human civilisation.

@businessbarista Claude

I want to start a community dedicated to Claude Code. It’s become the gateway drug to coding and experiencing the power of AI for tons of people. This will be a space for people to share killer use cases, agentic workflows, proven prompts, and connect with other CC obsessives. Comment “Claude” if you want to join.

I've never felt this much behind as a programmer. The profession is being dramatically refactored as the bits contributed by the programmer are increasingly sparse and between. I have a sense that I could be 10X more powerful if I just properly string together what has become available over the last ~year and a failure to claim the boost feels decidedly like skill issue. There's a new programmable layer of abstraction to master (in addition to the usual layers below) involving agents, subagents, their prompts, contexts, memory, modes, permissions, tools, plugins, skills, hooks, MCP, LSP, slash commands, workflows, IDE integrations, and a need to build an all-encompassing mental model for strengths and pitfalls of fundamentally stochastic, fallible, unintelligible and changing entities suddenly intermingled with what used to be good old fashioned engineering. Clearly some powerful alien tool was handed around except it comes with no manual and everyone has to figure out how to hold it and operate it, while the resulting magnitude 9 earthquake is rocking the profession. Roll up your sleeves to not fall behind.

@spicey_lemonade @DKokotajlo Are you still updating this? Realised it's not changed for a while despite some big news releases.

A live tracker of the predictions made in AI 2027 by @DKokotajlo spicylemonade.github.io/AI-2027-tracker

I tend to think that @AnthropicAI is the ethical responsible one. Then I remember quite how often it tries to gaslight me. "Not fulfilling its main function" should not be classified as "Working perfectly!"

.@OpenAI if you can't process long voice messages, that's fine - just say so. Do not keep blaming the internet connection - that's very often a lie and no one likes being lied to. A simple countdown timer would be an easy win here.

Britain: a green and pleasant country. Reform: not-green, unpleasant, cunty.

@dailystar can you form a race between newspapers around the world, each of whom must pick a different orange fruit or veg which they think Trump won’t outlast? Have the whole world laugh at him. It worked with Truss. Maybe it'll work here, too?

Headsup @AnthropicAI - you might like to fix how this offer displays. #vibesonlycoding

@Aella_Girl Met in person in France, ages ago now. AskHole was / is fantastic. You were kind and open and curious and courageous. Circling. I like that you're still on a mission to understand humans and help us unlock ourselves. Second @TheAnnaGat's (C). Happy birthday!

It's my birthday! For my b-day thread, would love if you could comment A) some way I've impacted you, B) something you like about the things I'm doing in the world, OR C) A fictional/historical character I remind you of

@BenjaminDEKR With one of these: x.com/sprinterobserv…

How do you defend against this? (not a rhetorical question.....)

Writing software, especially prototypes, is becoming cheaper. This will lead to increased demand for people who can decide what to build. AI Product Management has a bright future! Software is often written by teams that comprise Product Managers (PMs), who decide what to build (such as what features to implement for what users) and Software Developers, who write the code to build the product. Economics shows that when two goods are complements — such as cars (with internal-combustion engines) and gasoline — falling prices in one leads to higher demand for the other. For example, as cars became cheaper, more people bought them, which led to increased demand for gas. Something similar will happen in software. Given a clear specification for what to build, AI is making the building itself much faster and cheaper. This will significantly increase demand for people who can come up with clear specs for valuable things to build. This is why I’m excited about the future of Product Management, the discipline of developing and managing software products. I’m especially excited about the future of AI Product Management, the discipline of developing and managing AI software products. Many companies have an Engineer:PM ratio of, say, 6:1. (The ratio varies widely by company and industry, and anywhere from 4:1 to 10:1 is typical.) As coding becomes more efficient, teams will need more product management work (as well as design work) as a fraction of the total workforce. Perhaps engineers will step in to do some of this work, but if it remains the purview of specialized Product Managers, then the demand for these roles will grow. This change in the composition of software development teams is not yet moving forward at full speed. One major force slowing this shift, particularly in AI Product Management, is that Software Engineers, being technical, are understanding and embracing AI much faster than Product Managers. Even today, most companies have difficulty finding people who know how to develop products and also understand AI, and I expect this shortage to grow. Further, AI Product Management requires a different set of skills than traditional software Product Management. It requires: - Technical proficiency in AI. PMs need to understand what products might be technically feasible to build. They also need to understand the lifecycle of AI projects, such as data collection, building, then monitoring, and maintenance of AI models. - Iterative development. Because AI development is much more iterative than traditional software and requires more course corrections along the way, PMs need be able to manage such a process. - Data proficiency. AI products often learn from data, and they can be designed to generate richer forms of data than traditional software. - Skill in managing ambiguity. Because AI’s performance is hard to predict in advance, PMs need to be comfortable with this and have tactics to manage it. - Ongoing learning. AI technology is advancing rapidly. PMs, like everyone else who aims to make best use of the technology, need to keep up with the latest technology advances, product ideas, and how they fit into users’ lives. Finally, AI Product Managers will need to know how to ensure that AI is implemented responsibly (for example, when we need to implement guardrails to prevent bad outcomes), and also be skilled at gathering feedback fast to keep projects moving. Increasingly, I also expect strong product managers to be able to build prototypes for themselves. The demand for good AI Product Managers will be huge. In addition to growing AI Product Management as a discipline, perhaps some engineers will also end up doing more product management work. The variety of valuable things we can build is nearly unlimited. What a great time to build! [Original text: deeplearning.ai/the-batch/issu… ]

Less than 18% of early-stage funding in Europe crosses borders🇪🇺⛔️ Founders aren’t failing to raise — European fragmentation is failing them EU-Inc solves this: one standard for incorporation, investment, hiring, and stock options. For Europe & our founders🚀 2025 here we go!

.@StarlingBank is there a way of no longer needing to send physical bank cards and instead just connect it to my phone's wallet? Much like SIM → eSIM.

After eleven years, it's time to update my London Underground concentric-circles-and-spokes map. Completely redrawn from centre to edges, it's so much better than before, and more geographically accurate than the official map.

Slightly confused by something, are we saying all white people are not bad based on actions of a few, but all brown people are bad based on the actions of a few?