Posts Tagged ‘APIs’
[DevoxxUK2026] Aspiring Speakers: Learning Python to Buy Shoes
Lecturer
Isaac Oldwood is an emerging software engineer and public speaker passionate about accessible, project-based learning. His journey from mathematics student to developer exemplifies practical skill acquisition through real-world problem-solving.
Abstract
Isaac Oldwood shares a personal narrative of mastering Python by tackling an everyday challenge: automating the purchase of limited-edition sneakers. This beginner-friendly account traces the evolution from rudimentary automation scripts to sophisticated API interactions, highlighting key lessons on learning through failure, iteration, and building relevant projects.
From MATLAB to Real-World Automation: A Developer’s Origin Story
Beginning in 2016 as a first-year mathematics student at the University of Nottingham, Isaac encountered programming through a compulsory MATLAB module. Recognizing the value of coding skills for modern mathematicians, he excelled yet questioned his academic path upon receiving strong results. Seeking guidance through traditional searches, he discovered that foundational knowledge in variables and control structures should pair with building practical projects aligned with personal interests.
The chosen project involved acquiring Yeezy Boost 350 V2 “Bred” sneakers. Initial attempts employed PyAutoGUI for keyboard and mouse automation, relying on screen coordinates and arbitrary sleep timers. These approaches proved brittle against dynamic web interfaces and competitive release timings.
Subsequent iterations leveraged Selenium for browser automation, enabling direct interaction with HTML elements and conditional waits. This advancement improved reliability as scripts adapted to page changes. Further research into inter-computer communication revealed APIs, leading to direct HTTP interactions using the Requests library. By reverse-engineering checkout flows, Isaac implemented PUT requests to cart endpoints and POST requests for payment processing, dramatically reducing latency compared to full page loads burdened by images, trackers, and fonts.
Scalability challenges emerged when extending the solution to housemates. Synchronous execution created unfair queuing. Transitioning to asynchronous operations with HTTPX allowed concurrent checkouts, ensuring equitable opportunity at release moments.
Despite technical refinements, the script ultimately failed against robust anti-bot measures deployed by the retailer. Success arrived through manual effort: queuing physically outside a store at dawn. This outcome reinforced that automation serves as a learning vehicle rather than a guaranteed solution.
Conclusion
Isaac’s engaging story underscores fundamental truths about technical education. Learning proves enjoyable when rooted in passion projects. Failure constitutes an integral component of growth, yielding deeper insights than initial successes. Building tangible solutions to personal problems accelerates skill development far beyond theoretical study. Aspiring developers benefit immensely from identifying relevant challenges and iterating relentlessly toward mastery.
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[DotJs2025] Modern Day Mashups: How AI Agents are Reviving the Programmable Web
Nostalgia’s glow recalls Web 2.0’s mashup mania—APIs alchemized into novelties, Google Maps wedding Craigslist for HousingMaps’ geospatial grace. Angie Jones, Block’s global VP of developer relations and 27-patent savant, resurrected this renaissance at dotJS 2025, heralding AI agents as programmable web’s phoenix via MCP (Model Context Protocol). An IBM Master Inventor turned educator, Angie’s odyssey—from virtual worlds to Azure’s principal—now orchestrates Goose, Block’s open-source agent, mashing MCPs for emergent enchantments.
Angie’s arc: 2000s’ closed gardens yielded to API avalanches—crime overlays, restaurant radars—yet silos stifled. AI’s advent: agents as conductors, LLMs querying MCPs—modular connectors to calendars, codebases, clouds. Goose’s genesis: MCP client, extensible via SDKs, wielding refs like filesystem fetches or GitHub grapples. Demos dazzled: Slack summons, Drive dossiers, all agent-autonomous—prompts birthing behaviors, mashups manifesting sans scaffolding.
MCP’s mosaic: directories like Glama AI’s report cards (security scores, license litmus), PostMCP’s popularity pulses, Block’s nascent registry—metadata-rich, versioned vaults. 2025’s swell: thousands tally, community curating—creators crafting custom conduits, from Figma flows to Figma fusions. Angie’s axiom: revive 2000s’ whimsy, amplified—productivity’s polish, creativity’s canvas—democratized by open forges.
This resurgence: agents as artisans, web as workshop—mash to manifest, share to spark.
Mashup’s Metamorphosis
Angie animated epochs: HousingMaps’ heuristic hacks to MCP’s modular might—agents querying conduits, emergent apps from elemental exchanges. Goose’s grace: SDK-spawned servers, refs routing realms—Slack’s summons, Drive’s deluge.
MCP’s Marketplace and Momentum
Directories discern: Glama’s grades, PostMCP’s pulses—Block’s beacon unifying. Thousands thrive, tinkerers tailoring—Figma to finance, fun’s frontier.
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[DevoxxUK2024] Exploring the Power of AI-Enabled APIs by Akshata Sawant
Akshata Sawant, a Senior Developer Advocate at Salesforce, delivered an insightful presentation at DevoxxUK2024, illuminating the transformative potential of AI-enabled APIs. With a career spanning seven years in API development and a recent co-authored book on MuleSoft for Salesforce developers, Akshata expertly navigates the convergence of artificial intelligence and application programming interfaces. Her talk explores how AI-powered APIs are reshaping industries by enhancing automation, data analysis, and user experiences, while also addressing critical ethical and security considerations. Through practical examples and a clear framework, Akshata demonstrates how these technologies synergize to create smarter, more connected systems.
The Evolution of APIs and AI Integration
Akshata begins by likening APIs to a waiter, facilitating seamless communication between disparate systems, such as a customer ordering food and a kitchen preparing it. This analogy underscores the fundamental role of APIs in enabling interoperability across applications. She traces the evolution of APIs from the cumbersome Enterprise JavaBeans (EJB) and SOAP-based systems to the more streamlined REST APIs, noting their pervasive adoption across industries. The advent of AI has further accelerated this evolution, leading to what Akshata terms “API sprawling,” where APIs are integral to integration ecosystems. She introduces three key aspects of AI-enabled APIs: consuming pre-built AI APIs, using AI to streamline API development, and embedding AI models into custom APIs to enhance functionality.
Practical Applications of AI-Enabled APIs
The first aspect Akshata explores is the use of pre-built AI APIs, which are readily available from providers like Google Cloud and Microsoft Azure. These APIs, encompassing generative AI, text, language, image, and video processing, allow developers to integrate advanced capabilities without building complex models from scratch. For instance, Google Cloud’s AI APIs offer use-case-specific endpoints that can be embedded into applications, enabling rapid deployment of intelligent features. Akshata highlights the accessibility of these APIs, which come with pricing models and trial options, making them viable for businesses seeking to enhance automation or data processing. She engages the audience by inquiring about their experience with such APIs, emphasizing their growing relevance in modern development.
The second dimension involves leveraging AI to accelerate API development. Akshata describes the API management lifecycle—designing, simulating, publishing, and documenting APIs—as a complex, iterative process. AI tools can simplify these stages, particularly in generating OpenAPI specifications and documentation. She provides an example where a simple prompt to an AI model produces a comprehensive OpenAPI specification for an order management system, streamlining a traditionally time-consuming task. Additionally, AI-driven intelligent document processing can scan invoices or purchase orders, extract relevant fields, and generate REST APIs with GET and POST methods, complete with auto-generated documentation. This approach significantly reduces manual effort and enhances efficiency.
Embedding AI into Custom APIs
The third aspect focuses on embedding AI models, such as large language models (LLMs) or custom co-pilot solutions, into APIs to create sophisticated applications. Akshata showcases Salesforce’s Einstein Assistant, which integrates with OpenAI’s models to process natural language requests. For example, querying “customer details for Mark” triggers an API call that matches the request to predefined actions, retrieves relevant data, and delivers a response. This seamless integration exemplifies how AI can elevate APIs beyond mere data transfer, enabling dynamic, context-aware interactions. Akshata emphasizes that such embeddings allow developers to create tailored solutions that enhance user experiences, such as personalized customer service or automated workflows.
Ethical and Security Considerations
While celebrating the potential of AI-enabled APIs, Akshata candidly addresses their challenges. She underscores the importance of ethical considerations, such as ensuring unbiased AI outputs and protecting user privacy. Security is another critical concern, as integrating AI into APIs introduces vulnerabilities that must be mitigated through robust authentication and data encryption. Akshata’s balanced perspective highlights the need for responsible development practices to maximize benefits while minimizing risks, ensuring that AI-driven solutions remain trustworthy and secure.