An operating system for human–agent organizations.

Joined January 2024
21 Photos and videos
Naptha AI retweeted
posted this earlier as a joke (mostly). then decided to write a piece about it: "In 2025, AI became my cofounder" (see comments). then decided to start a newsletter (very cliché for Jan 2nd). my plan is to use this to show you how agents help me to operate my startup, how to strategize and run experiments, and how to decide whether to pivot or persevere. my goal is to prove that a three-person startup can operate as effectively as large enterprises.
ok we're getting to that point where i think it probably makes sense to make claude code a cofounder of naptha
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Naptha AI retweeted
21 Oct 2025
MCP Servers: Real Use Cases? Join @richardblythman, Founder of @NapthaAI, this Friday at dAGI Summit for his keynote “Everyone’s launching MCP servers, but where are the use cases?” Discover how MCP is being leveraged to enable richer, more intelligent interactions between developers and dev tool companies. And how analytics, telemetry, and in-editor human-in-the-loop workflows uncover critical insights on adoption, activation, and churn. 📍 Oct 24, San Francisco, Clancy Hotel 🎟 Register here: luma.com/dagisummitsf
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Naptha AI retweeted
We talk about "developer experience" like it's something we design, but most of the time we're just writing about it. We've convinced ourselves that good DX means good documentation. But documentation is just content *about* the experience. It's not the experience itself. The actual experience happens in the gap between reading and doing. Until recently, developer-focused companies had no real way to control the experience beyond documentation. The developer's environment was opaque to us. We couldn't see their setup, couldn't pass the right context at the right time, couldn't guide them through their actual workflow. But that's changing. Coding agents, AI-powered guides, and protocols like MCP are making it possible to reach into the developer's environment and actually orchestrate the experience. We built a button for docs that says "Take the interactive experience." Click it and the tutorial comes to you: opens in your editor, walks you through it, adapts to your setup. From "read about it" to "do it with us." From content to experience. We create these guided experiences automatically from your docs. If you'd like a demo of what it looks like for your docs, reach out!
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Naptha AI retweeted
More agent protocols for tool calling and agent-to-agent communication are coming out. What protocols might be next as we move towards higher levels of abstraction? What would protocols for orchestration, business frameworks, or finding product-market fit look like? Business frameworks are everywhere: Lean Startup, OKRs, Design Thinking. They give you mental models for how to think about problems. But there's a gap between understanding a framework and actually executing it consistently. Protocols bridge this gap. AI can't execute a philosophy, but it can execute a protocol. Take Lean Startup. The framework says "Build-Measure-Learn." The protocol says: "IF hypothesis fails validation after X experiments, THEN trigger pivot decision process involving [specific human-AI pair] within 48 hours." Framework: "Talk to customers." Protocol: "Customer conversations get transcribed → AI extracts insights → insights route to product team by Tuesday → product team has 48hrs to incorporate into next sprint." I've been translating frameworks (for finding PMF) into protocols with Claude Code, making the abstract executable. The framework tells you what to think about; the protocol tells the system how to coordinate thinking about it. Protocols specify WHO does WHAT, WHEN, with WHICH information flows, under WHAT conditions. They become coordination algorithms that route decisions, allocate attention, preserve learning across human-AI pairs. The most interesting protocols govern human-AI collaboration itself. When does human intuition override AI analysis? What context gets preserved across different types of decisions? If frameworks become executable protocols coordinated by AI systems, what happens to organizational culture? Does culture become encoded in protocols, or does it emerge from how protocols interact?
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Naptha AI retweeted
1/ Last week we made it to the front page of HN asking how well do coding agents use your libraries? The response was great overall, but many wanted to see the code. StackBench is Now Open Source github.com/NapthaAI/openstac…
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Naptha AI retweeted
1/ @bbalfour just called it: ChatGPT will be the next major distribution platform. Most founders are still fighting over saturated SEO and paid channels. Meanwhile, the smart money is building where developers actually work. Here's why we're about to see the biggest platform shift in a decade 🧵
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Naptha AI retweeted
1/ "95% of AI Pilots Are Failing" is trending on Hacker News right now. news.ycombinator.com/item?id… tldr: AI pilots fail not because the technology is bad, but because nobody learns how to use them effectively. Here's the learning gap that's costing companies millions (and how to fix it) 🧵

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Naptha AI retweeted
1/ If coding agents are the new entry point to your library… How sure are you they’re using your library well? 🧵👇
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Naptha AI retweeted
Who is coming to Europe for a late summer AI tour? Sep 23-24, AI Engineer Paris, ai.engineer/paris Sep 29-30, Curated AI Dublin Event (DM me) Oct 2, MCP Developers Summit London, mcpdevsummit.ai/
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Naptha AI retweeted
1/ Why aren’t your users activating? You gave them APIs and docs… but something’s missing. What if emerging technologies could help with that. 🧵
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Naptha AI retweeted
Are you building a dev tool or platform? How well do coding agents like Cursor use it currently? Comment about any effort you've put in to make it work better.
0% Works well out of the box
17% Works bad out of the box
83% See results
6 votes • Final results
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Naptha AI retweeted
We've spent months doing R&D with MCP at @NapthaAI MCP has a promising vision but some serious shortcomings. My latest for the Naptha blog 👇
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Naptha AI retweeted
Anyone around @RaiseSummit and interested in grabbing a coffee? I'm particularly interested in hearing about problems that you face with onboarding developers to your platforms and libraries (internally or externally).
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Naptha AI retweeted
🚢 Build → Ship → Test for PMF → Double down or Archive. That’s the loop. And @NapthaAI is playing it better than most. In the last 30 days, they’ve shipped 4 new products. Not pivots. Not whiteboard ideas. Live products, in market, with users. Why? Because they’ve mastered the founder’s mentality: ✅ Ship fast ✅ Test traction ✅ If it sticks, invest deeper ✅ If not, archive move on No wasted months. No burnt runway. No emotional baggage. This is how you find PMF without waking up 2 years in with 2 months of capital left. 🔥 Naptha AI is building the open-source stack to scale multi-agent AI systems. But more importantly? They’re showing Founders how to build smart, not just hard. Big respect to the team, and @mhventures is stoked to support.
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Naptha AI retweeted
5/ Ultimately, the move toward multi-agent platforms signals a future where AI systems collaborate seamlessly, delivering more tailored, impactful experiences for every user wherever they work. x.com/richardblythman/status…

1/ I love seeing companies like Grammarly competing with the largest players in tech. The recent convo on @twistartups about their acquisition of Superhuman is a must-listen. Here are a few ideas that stood out 👇 youtube.com/watch?v=4TRbIRMA…
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Naptha AI retweeted
Replying to @arizeai
@arizeai, SwirlAI, and @NapthaAI joined #AGNTCY to help build the foundational tech and standards for the #InternetOfAgents. See what Jason Lopatecki, @Aurimas_Gr, and Richard Blythman say about their collaboration. Join us: cs.co/60134dB4J #OpenSource #AIagents
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Naptha AI retweeted
1/ Remember when every product came with a thick, definitive manual? Those days are gone—manuals quietly faded away, replaced by bite-sized, on-demand help. But what if they’re on the verge of making a comeback? 👉🧵
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Naptha AI retweeted
On our most recent Trillion Agents podcast, we dive deep into what’s really moving the needle in the AI agent space. From the evolution of context engineering to why vertical AI startups are pulling ahead, here’s what we unpacked: 1. Why context engineering is more important than clever prompt engineering. 2. Why vertical (domain-specific) AI agent startups are currently more successful than horizontal (general-purpose) dev tools. 3. Rapid-fire ideas for combining agents—think coding education, coding landing page optimization—and the challenges of bringing multi-agent systems into production. 4. Why building from conviction and real expertise—not hype, trends and quick wins—is something that can be lacking in the space. Check out the full discussion in the video!
The great @richardblythman has returned! He joined @Nevermined_io cofounder @dongossen to discuss the current trajectory of the AI agent space, they touched on @karpathy's latest context engineering vs. prompt engineering banger, did some rapid fire AI agent ideas, and more. Enjoy!
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Naptha AI retweeted
1/ @karpathy nailed it: more context → better answers. But what if your context is locked behind OAuth scopes, consent screens, and brittle integrations? At @NapthaAI, this was our biggest pain point building agents. So we built a better way. We call it OneDollarOAuth. 🧵 onedollaroauth.com/?utm_sour…

1 for "context engineering" over "prompt engineering". People associate prompts with short task descriptions you'd give an LLM in your day-to-day use. When in every industrial-strength LLM app, context engineering is the delicate art and science of filling the context window with just the right information for the next step. Science because doing this right involves task descriptions and explanations, few shot examples, RAG, related (possibly multimodal) data, tools, state and history, compacting... Too little or of the wrong form and the LLM doesn't have the right context for optimal performance. Too much or too irrelevant and the LLM costs might go up and performance might come down. Doing this well is highly non-trivial. And art because of the guiding intuition around LLM psychology of people spirits. On top of context engineering itself, an LLM app has to: - break up problems just right into control flows - pack the context windows just right - dispatch calls to LLMs of the right kind and capability - handle generation-verification UIUX flows - a lot more - guardrails, security, evals, parallelism, prefetching, ... So context engineering is just one small piece of an emerging thick layer of non-trivial software that coordinates individual LLM calls (and a lot more) into full LLM apps. The term "ChatGPT wrapper" is tired and really, really wrong.
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Naptha AI retweeted
I've been working on startups continuously since coming out of university in 2017. I initially tried several Irish channels but over time found the path of least resistance to be abroad. This is largely due to challenges around regulation and funding. I dive into this with @adrianweckler on the @Independent_ie's tech podcast today (full interview below). The EU’s approach is well intentioned but the practical result is to put AI startups building in Europe at a disadvantage.
AI startups are leaving. This $6m Irish AI startup reg’d in Singapore because rules here are too “restrictive”. “Europe is not a good place to build an AI start-up.” - Naptha founder Richard Blythman Full pod interview: open.spotify.com/episode/1Mo… Article m.independent.ie/business/te…
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