Danny Hawkins

1 year at Zed Mobility building for scale in age of AI ⚙️ It’s been a year of solving hard problems, making big bets, and learning faster than ever. Leading this team has been both humbling and energizing - every milestone has been a product of deep collaboration and relentless ownership from the crew. Over the last 12 months, we have seen: - Team scale: Engineering grew from 3–4 hires to a org of 35+ - System scale: Platforms now handle 40x peak load with no critical downtime - Engineering culture: Embedded ownership, transparency, and work-life balance as non-negotiables Key enablers: - Re-architected services for horizontal scalability and better fault isolation - Standardized observability stack for real-time performance insights - Shifted from reactive fixes to proactive reliability engineering Year 2 goals: - Scale via AI, not headcount — embedding LLMs into operations, monitoring, and customer experience - Drive QA automation to accelerate release velocity without sacrificing quality - Mature DevOps → DevSecOps, integrating security at every stage of the pipeline - Invest in developer productivity — faster environments, streamlined CI/CD, and fewer context switches Building not just for today’s demand, but for the next 10x. 🚀 #startups #AI #organisation #GCC #Dubai #Engineering #DevSecOps

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Vibe-code an invoice processing application with production-quality accuracy in minutes ⚡️ I’m excited to release a repo that shows you how to vibe-code your very own Streamlit application from a simple .py file (a few lines of code) that shows how to use our LlamaCloud parsing/extraction SDK. Simply drag the prompt into Cursor/Claude Code, make whatever modifications you’d like, and one-shot a decent-looking app that lets you process invoices using our VLM-enabled extraction capabilities, extract out an output, and review results. The very nature of open-source repos as educational resources is changing. This is a new type of repo where the goal is not to give you just the code, but also the prompts so you can started building whatever application you’d like in a short amount of time! https://lnkd.in/gXdhR29u

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How fast your API partners go live determines how quickly they generate mutual revenue.   A payments company I spoke with tracked time from the signed agreement to the first live transaction with API integration partners, such as e-commerce platforms and merchant processors.   Each week of integration delay cost them $80,000 in partner-driven revenue. Three weeks meant $240,000 in opportunity cost.   Their challenge was manual integration processes that required engineering resources for every new API partner. Every integration meant documentation handoffs, scheduled calls, and custom environment setups.   They were treating API partner onboarding like a consulting project instead of a scalable system.   Then they rebuilt it as a self-service platform. API partners get immediate sandbox access, automated documentation, and standardized authentication flows.   The result: integration time dropped from six weeks to eight days.   Partner-generated revenue increased 40% year-over-year because API partners went live faster and started contributing revenue earlier.   The platform tools that accelerate your internal teams' work the same way for external API partners: - Sandbox environments for testing integrations without engineering support - Real-time API documentation that updates automatically - Streamlined authentication and immediate production access - Consistent 8-day integration timeline When done right, the same platform infrastructure that helps your developers also accelerates partner success.   In this week's newsletter, I show how platform engineering makes API partner onboarding self-service.   Link is in the comments.

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Most people think “agentifying” an app just means replacing buttons with natural language. That’s level one. But real Agentic transformation goes deeper - it redefines what your application can do. At Adopt, we're seeing our customers take agents in a few different directions that expand the capabilities of their app 1️⃣ Systems of Action AND Intelligence Reasoning and Intelligence capabilities embedded in the agent and that add value beyond the app's capabilities of displaying data for the human to analyze. Example: Instead of “Show me last quarter’s pipeline,” users can ask, “Why did pipeline drop last quarter?” The agent analyzes trends, flags anomalies, and recommends action — all in one turn. 2️⃣ App is the command center Agents can span apps. Trigger workflows across Salesforce, Notion, Jira - all from one interface. The app becomes the command center - not a destination, but a launchpad. 3️⃣ Autonomy - beyond prompt and response Users are getting used to offloading workflows entirely to agents that complete the work in the background and come up with the results. This kind of 'autonomy' was not possible with apps before. Agents will anticipate needs, generate plans, and work towards outcomes. 'Prepare a QBR deck with latest usage + churn insights.' 'Run a pricing experiment - 20% discount for dormant users in EMEA.' That’s real delegation. So yes, natural language is step one. But agentifying your app means much more. At Adopt, we're enabling you to make this shift - fast.

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