Francis Nappez Caulliez

Why do freelancers tell us so much about new tech trends? - With an average of 4 hours of training per week, they are pioneers in the adoption of new practices and technologies. - For their part, companies call on them when they haven't (or haven't yet) developed cutting edge expertise in-house. 𝗠𝗮𝗹𝘁’𝘀 𝗧𝗲𝗰𝗵 𝗧𝗿𝗲𝗻𝗱 𝟮𝟬𝟮𝟱 𝗿𝗲𝗽𝗼𝗿𝘁 leverages data from 200,000+ freelancers and millions of project searches on Malt. Trends captured by the report derive directly from thousands of companies using Malt to build real-world tech solutions. What do we learn?  ↗️ 𝗔𝗜 𝗶𝘀 𝗯𝗼𝗼𝗺𝗶𝗻𝗴 - 𝗼𝗳 𝗰𝗼𝘂𝗿𝘀𝗲: AI projects more than tripled in 2024 and demand for RAG even grew x17 in 2024! ↗️ 𝗟𝗼𝘄-𝗰𝗼𝗱𝗲/𝗻𝗼-𝗰𝗼𝗱𝗲 𝗶𝘀 𝗺𝗮𝗸𝗶𝗻𝗴 𝗮 𝘀𝘁𝗿𝗼𝗻𝗴 𝗰𝗼𝗺𝗲𝗯𝗮𝗰𝗸, fuel by synergies with AI: demand grew 40% in 2024. ↗️ 𝗦𝗼𝘃𝗲𝗿𝗲𝗶𝗴𝗻𝘁𝘆 𝗶𝘀 𝘁𝗼𝗽 𝗼𝗳 𝗺𝗶𝗻𝗱 𝗳𝗼𝗿 𝗰𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀, who tend to adopt EU cloud and open LLMs. ❌ 𝗚𝗿𝗲𝗲𝗻 𝘁𝗲𝗰𝗵 𝘀𝗵𝗼𝘂𝗹𝗱 𝗯𝗲 𝗮 𝗽𝗿𝗶𝗼𝗿𝗶𝘁𝘆, 𝗯𝘂𝘁 𝗶𝘁 𝗶𝘀 𝗮 𝗯𝗹𝗶𝗻𝗱 𝘀𝗽𝗼𝘁: despite growing awareness of AI’s energy footprint, we haven’t seen a meaningful increase in demand for green tech skills. Download our full report: https://lnkd.in/eJi_TMwQ #AI #Cybersecurity #Cloud #Sovereignty #TechTrends #DigitalStrategy #LowCode #OpenSource #GreenTech #FreelanceTech #MaltTechTrends

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Fascinating to see how much interest and energy there is around enterprise AI right now — especially when the conversation moves beyond hype to the real-world challenges of building and scaling production-grade solutions. Yesterday at the OVHcloud x YourStory Media AI Startup event, my co-founder SK A.ya and I had the privilege of sharing our perspective on why enterprise AI code generation is still an unsolved problem — and how we’re tackling it at Toystack AI. The questions and insights from the audience reinforced just how relevant these topics are: everyone’s excited about the possibilities of AI, but equally aware of the gaps that need to be solved before it can truly deliver for enterprises at scale. The challenge: Enterprise-grade AI code often lacks structure, security, context-awareness, guardrails, and seamless cloud deployment. The approach we’re taking: At Toystack AI, we’ve built a system that combines multi-agent orchestration, a mix of LLMs, context-rich databases, best-in-class coding patterns, and strict guardrails — all fully integrated with automated, one-click Kubernetes cloud deployments. We also spoke about why a truly enterprise-ready code-gen solution can’t be built in isolation — it has to address real-world client needs and production constraints, not just idealized developer workflows. On the topic of scaling, I shared why getting to $100M+ revenue in this space will require more than the classic product-led growth motion — it calls for a sales-led, custom-service approach that resonates with enterprise realities. It was equally inspiring to learn from other founders doing amazing work in this space: Abhilash Salimath of TrueFan AI, enabling creators to monetize directly and deliver personal wishes — even from Rishabh Pant, in any language! Arvind Venugopal Nair of NeuroPixel.AI, building AI-powered, hyper-personalized marketing and creative intelligence — imagine any clothes on any model, in any setting. Really enjoyed the thoughtful discussion on trends in AI and valuation of AI startups, moderated by Shivani Muthanna of YourStory Media, with insights from a stellar panel: Shubham Jhuria (Aeravti Ventures) Nishant Chandra (Newton School) Ankit K. (Capital-A) Sriram Kannan (Routematic) A big thank you to Satyam Santosh for organizing and to OVHcloud for showcasing the powerful compute and cloud capabilities they’re bringing to India and beyond. The energy in the room was incredible — and the engagement on these tough-but-important topics reminded me how crucial it is to keep building with both ambition and real world pragmatism. #AI #EnterpriseAI #CodeGeneration #LLM #AgenticAI #Toystack #Cloud #DevOps #OVHcloud #AIStartups #Valuation #YourStory

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Yesterday, Anthropic released Sonnet 4.5, the newest foundational AI model. Today, Magic Patterns is already leveraging it under the hood, powering the next million web applications created on our AI-native design tool. Within the first 24 hours, our customers — product managers, designers, website builders — are seeing: - Higher quality styling - Awareness of its context window - Code output that looks more real and natural - Faster generation speeds - Less errors It’s serendipitous timing: this news arrives while the Magic Patterns team is here at LinkedIn HQ talking about AI in Work! The critical question every company should be asking right now: When the next breakthrough model launches, how quickly can your organization put *it* to work? For our customers, the answer is immediate. Today they are waking up to better, faster designs without changing a single workflow. What's your organization's model upgrade strategy?  How do you leverage AI in work?

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There’s a lot of content about entrepreneurship out there, but not nearly as much about what it means to be a second-time founder. (Poke Thibaud Elziere with Twice.) At first glance, it might look easy to launch a new company after a successful exit, but let me tell you the truth. Being an entrepreneur is still immensely hard, especially after spending 3.5 years in a comfortable role at a US unicorn. Here are a few thoughts that come to my mind: • Lose your title, lose your status. Even though you carry more credibility as a repeat entrepreneur, many people will still be less interested in talking to you when you’re a startup with zero revenue. • Finding PMF is still incredibly hard. Just because you know the industry and potential customers doesn’t mean reaching PMF is easy. Sometimes, your industry knowledge can even limit your creativity. • Stealth mode isn’t as cool as it seems. Putting “working on something new” on LinkedIn is practically an invitation for VCs to get in touch. Of course, they don’t want to miss the next big thing. But founders, please don’t spend time on meetings before you’re ready to do it. It’s a huge distraction and a drain on your energy. That being said, I’m back in grind mode, and it feels exhilarating. The Sunday evening excitement about the week ahead is something unique to entrepreneurship.

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When I was in YC, I was surprised to see that startups are now vibe-coding their entire companies in 3 days. Not weeks. Not months. Days. — Here’s the exact $40 stack making it possible: - Lovable/v0 by Vercel → frontend in hours - Cursor/Claude Code → AI pair programmer - Supabase → backend in a box - Stripe → collect payments - Willowvoice.com → Prompt AI with voice, makes coding feel like magic — How the process works: Day 1 — Ship the core logic Start with the simplest version of your product. Forget design or polish. Just get the main feature working (even if it’s just a single button). Day 2 — Talk it into existence Instead of making wireframes in Figma, founders literally talk through what happens with WillowVoice to an AI coding tool: “User clicks this → then sees that…” That narration gets transcribed and fed into AI tools to generate components, layouts, and dashboards. What used to take a day can now be done in an hour. Day 3 — Tighten the flow Once the product works, the final step is smoothing out the onboarding and user flows. Instead of typing long prompts, founders just talk through their fixes with WillowVoice, which AI implements quickly. — What YC founders are learning: 1. Perfect code is the enemy of shipped code 2. AI works best when iteration speed is insane 3. The first version will be wrong anyway → build it in days, not months — The result: A working product in 2–3 days. Crude? Sure. But enough to launch, test, and iterate. YC startups are proving it: the future of development is AI + vibe-coding at the speed of thought. Would you build your next idea this way, or do you think speed comes at too high a cost???

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