What comes after the IDE?
In this episode of Inference, I sit down with Zach Lloyd, founder of Warp, to talk about a new category he’s coining: the Agentic Development Environment (ADE).
We explore why coding is shifting from keystrokes to prompts, how Warp positions itself against tools like Cursor and Claude Code, and what it means for developers when your “junior dev” is an AI agent that can already set up projects, fix bugs, and explain code line by line.
We also touch on the risks: vibe coding that ships junk to production, the flood of bad software that might follow, and why developers still need to stay in the loop — not as code typists, but as orchestrators, reviewers, and intent-shapers.
This is a conversation about the future of developer workbenches, the end of IDE dominance, and whether ADEs will become the default way we build software. Watch it!
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Guest:
Zach Lloyd, founder of Warp
https://www.linkedin.com/in/zachlloyd/
https://x.com/zachlloydtweets
https://x.com/warpdotdev
https://www.warp.dev/
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Chapters
Turing Post is a newsletter about AI's past, present, and future. Publisher Ksenia Se explores how intelligent systems are built – and how they’re changing how we think, work, and live.
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#Warp #AgenticAI #AgenticDevelopment #AItools #CodingAgents #SoftwareDevelopment #Cursor #ClaudeCode #IDE #ADE #AgenticWorkflows #FutureOfCoding #AIforDevelopers #TuringPost
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30:18
Machines Don’t Think. Kids Do | The AI Literacy Series (Ep. 2)
Do machines think? Try asking a child.
Children are natural philosophers of AI. They draw librarians inside speakers, ask what the robot “wants,” and poke at the cracks in classifiers until bias spills out. They remind us that anthropomorphism is not a mistake – it’s the starting point.
In this second episode of the AI Literacy Series, I sit down again with Stefania Druga – researcher, educator, and my co-author on this project – to explore how kids help us see AI more clearly than most experts.
*We’ll explore:*
- Why words like think, know, imagine matter more than we admit.
- How kids move from magical thinking to system thinking.
- The “Big Three” AI families – classifiers, diffusion models, transformers – explained in ways families can test at home + more!
- How transfer learning works for humans, connecting toy models to civic-scale consequences.
- Six advanced family activities that make bias, prediction, and agency visible.
AI literacy is not just technical instruction – it’s cultural negotiation. And sometimes the best teachers are sitting right at the dinner table.
📌 You can find all mentioned resources & activities here: https://www.turingpost.com/p/ailiteracy2
📌 Subscribe to follow the series and join us in building a living playbook for AI literacy.
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32:12
Stop Teaching Kids About AI. Do This Instead | The AI Literacy Series (Ep. 1)
Would you stop your child from learning how to write and read? AI literacy is the same now. To succeed in life, you have to be fluent in it.
Generative and other types of AI is no longer something you “learn to use.” It’s the environment we all live in. It’s shaping homework, search, gameplay, even family kitchen conversations. And while adoption has crossed a threshold, our understanding of AI literacy is still catching up.
In this first episode of the AI Literacy Series, I sit down with *Stefania Druga* – researcher, educator, creator of Cognimates, and my co-author on this project – to explore a central question: *what does it mean to raise an AI-literate generation – and actually be cool about it?*
*We’ll explore:*
- Why AI literacy is the new baseline, not an add-on.
- How to help kids move from “using AI” to questioning and shaping it.
- Practical frameworks like Graidients, making AI use visible, intentional, and ethical.
- Seven simple activities you can try at home to build fluency together.
This series isn’t about watering down AI for children. It’s about reimagining how we – as builders, parents, and educators – prepare the next generation to live, think, and create inside an always-on model ecosystem. Doesn't matter if you are an AI expert or a total novice – everyone will find something insightful.
📌 You can find all mentioned resources & activities here: https://www.turingpost.com/p/ailiteracy1
📌 Subscribe to follow the series and join us in building a living playbook for AI literacy.
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35:02
When Will Inference Feel Like Electricity? Lin Qiao, co-founder & CEO of Fireworks AI
What limits AI today isn’t imagination – it’s the cost of running it at scale.
In this episode of Inference, Ksenia Se sits down with Lin Qiao, co-founder & CEO of Fireworks AI (an inference-first company) and former head of PyTorch at Meta, where she led the rebuild of Meta’s entire AI infrastructure stack.
We talk about:
Why product-market fit can be the beginning of bankruptcy in GenAI
The iceberg problem of hidden GPU costs
Why inference scales with people, not researchers
2025 as the year of AI agents (coding, hiring, SRE, customer service, medical, marketing)
Open vs closed models – and why Chinese labs are setting new precedents
The coming wave of 100× more efficient AI infrastructure
Watch to hear Lin’s vision for inference, alignment, and the future of AI infrastructure.
And – at the end – Lin shares her very personal journey to overcome fears. Watch it!
Did you like the episode? You know the drill:
📌 Subscribe for more conversations with the builders shaping real-world AI.
💬 Leave a comment if this resonated.
👍 Like it if you liked it.
🫶 Thank you for watching and sharing!
Guest:
Lin Qiao, co-founder & CEO of Fireworks AI and former head of PyTorch at Meta
https://www.linkedin.com/in/lin-qiao-22248b4
https://x.com/lqiao
https://x.com/FireworksAI_HQ
https://fireworks.ai/
📰 Want the transcript and edited version?
Subscribe to Turing Post https://www.turingpost.com/subscribe
Chapters
Turing Post is a newsletter about AI's past, present, and future. Publisher Ksenia Se explores how intelligent systems are built – and how they’re changing how we think, work, and live.
Sign up: Turing Post: https://www.turingpost.com
Follow us
Ksenia and Turing Post:
https://x.com/TheTuringPost
https://www.linkedin.com/in/ksenia-se
https://huggingface.co/Kseniase
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25:50
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25:50
How to Make AI Actually Do Things | Alex Hancock, Block, Goose, MCP Steering Committee
Right now, the biggest leap for AI isn’t a bigger model – it’s giving models and agents a way to act.
In this episode of Inference, I sit down with Alex Hancock – Senior Software Engineer at Block, core contributor to Goose (the open-source, multi-purpose AI agent), and a member of the Model Context Protocol (MCP) Steering Committee – to talk about the infrastructure that’s quietly powering the next wave of AI.
*We cover:*
– What MCP is – and why it’s exploding in adoption
– How it turns models from “brains in jars” into agents with arms and legs
– The MCP Steering Committee’s push for openness and real governance
– Why SDK parity, registry design, and OAuth 2.1 are make-or-break for developers
– How MCP and A2A fit together – and where they might compete
– Context discovery, context management, and why they’re the hardest problems in agentic AI
– The lessons from Goose on staying model-agnostic in a fast-moving ecosystem
– What this shift means for software development – and for the humans in the loop
Alex also shares his view on the next year of protocol development, why he thinks AGI will arrive incrementally, and how a runner’s mindset shapes his approach to building tools that last.
If you’re building agents, connecting models to the world, or just trying to understand the emerging “protocol layer” of AI, this conversation will give you a front-row seat.
Let’s find out how we’re teaching AI to act – and what’s still missing.
*Did you like the episode? You know the drill:*
📌 Subscribe for more conversations with the builders shaping real-world AI.
💬 Leave a comment if this resonated.
👍 Like it if you liked it.
🫶 Thank you for watching and sharing!
*Guest:*
Alex Hancock, Senior Software Engineer at Block, Goose Maintainer & MCP Steering Committee Member
https://www.linkedin.com/in/alexjhancock/
https://x.com/alexjhancock
https://github.com/block/goose
MCP https://github.com/modelcontextprotocol
Building to Last: A New Governance Model for MCP https://blog.modelcontextprotocol.io/posts/2025-07-31-governance-for-mcp/
*📰 Want the transcript and edited version?*
Subscribe to Turing Post: https://www.turingpost.com/subscribe
Chapters *coming*
Turing Post is a newsletter about AI's past, present, and future. Publisher Ksenia Se explores how intelligent systems are built – and how they’re changing how we think, work, and live.
*Follow us:*
Ksenia and Turing Post:
https://x.com/TheTuringPost
https://www.linkedin.com/in/ksenia-se
https://huggingface.co/Kseniase
Inference is Turing Post’s way of asking the big questions about AI — and refusing easy answers. Each episode starts with a simple prompt: “When will we…?” – and follows it wherever it leads.Host Ksenia Se sits down with the people shaping the future firsthand: researchers, founders, engineers, and entrepreneurs. The conversations are candid, sharp, and sometimes surprising – less about polished visions, more about the real work happening behind the scenes.It’s called Inference for a reason: opinions are great, but we want to connect the dots – between research breakthroughs, business moves, technical hurdles, and shifting ambitions.If you’re tired of vague futurism and ready for real conversations about what’s coming (and what’s not), this is your feed. Join us – and draw your own inference.
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