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AI tools are evolving fast with razzle-dazzle, but lasting enterprise success hinges on reasoning, math, and business goal alignment, creating enduring foundations.
In 2008, while building computer vision systems at Pongr, my team and I pored over thousands of images by hand. We studied geometric points, distilling them into scores that powered image recognition for consumer-generated photos.
Curious about computer vision fundamentals—image recognition, object detection, or tracking? I’d love to share practical tips in a one-on-one session. Book a call with me to dive into how these techniques work and may apply to your business: Schedule a Call.
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“AI empowers product managers with technical skills to build polished POCs in days, not months. Coding skills help, but clear goals and relentless iteration—think 1,000+ cycles in 40~50 hours—are key. AI’s power grows, and so do PMs who use it well.”
That manual, disciplined process forced us to zero in on what mattered most. It wasn’t glamorous, but it built early AI systems that worked.
Back then, a colleague introduced me to Tom Yeh, a brilliant grad student at MIT CSAIL who became an advisor to our team. Tom’s approach was uncompromising: no shortcuts, just a relentless focus on understanding systems from the ground up.
Today, as a professor at the University of Colorado Boulder, he teaches AI by Hand, a course that drills down to the math, dot products, matrix multiplication, and gradients that power models like LLaMA 4 or GPT-4.5. Read Tom’s blog.
Tom has mentioned in a recent post how young students from India and China are taught fundamentals, developing a command of core critical thinking skills before they’re introduced to tools. This deliberate, slower path, steeped in pencil-and-paper exercises, forges clarity. It’s a model for how we should approach AI in business.
Before diving into models or vendors, step back:
What are we solving for—speed, profitability, customer loyalty, or resilience?
How will we measure progress?
Who shapes the outcome?
As we explored a few weeks ago, backcasting, starting with your desired future state and working backward, grounds AI in strategy. Data scientists alone can’t drive this. Product leaders, operators, and marketers must define what success looks like, ensuring technology serves business needs.
Tools evolve. Fundamentals and strategic alignment endure.
🗓️ Noteworthy Upcoming Events
SuperAI Singapore | Ai4 2025 | The AI Summit New York |
|---|---|---|
June 18-19, 2025 | August 11-13, 2025 | December 10-11, 2025 (tentative) |
Marina Bay Sands, Singapore | MGM Grand, Las Vegas, NV | New York City, NY |
Register here. | Register here. | Register here. |
Asia’s premier AI event, hosting 7,000+ executives, including CEOs and CIOs. Network with leaders from Microsoft, Google, and OpenAI. Sessions dive into AI for finance, healthcare, and supply chains. Early bird pricing: $299-$2,999. A must for strategic partnerships in APAC. | North America’s largest AI summit, drawing 8,000 attendees and 600+ speakers. Tracks cover enterprise AI, ROI, and compliance. Complimentary passes for qualifying execs. Ideal for leaders seeking actionable strategies and high-level networking. | Marking its 10th year, this summit attracts 3,500+ execs to explore practical AI and governance. Features C-level roundtables and case studies on efficiency and compliance. Pricing: ~$449-$3,295. Perfect for leaders prioritizing scalable AI adoption. |
🕚 Balanced & Insightful:
AI promises transformation, but speed without strategy burns resources. Aligning AI with business goals unlocks value, fast. In the AI era, tools and systems, when used well, collapse development cycles, enabling unprecedented speed without sacrificing precision.
Why It Matters:
Clarity Fuels ROI: Define metrics, cost reduction, retention, and efficiency before picking tools.
Cross-Functional Buy-In: Operations, finance, and marketing must shape AI’s purpose.
Scale with Focus: Start with high-impact pilots, predictive maintenance, and churn analysis to gain traction.
Actionable Steps:
Host a series of 1-2 hour whiteboard sessions with stakeholders to capture institutional knowledge and map pain points.
Choose one high-value use case with clear outcomes.
Pilot a modular AI solution, like a RAG-based assistant, for control and rapid iteration.
Strategic AI delivers results that are right and swiftly.
📰 AI Trends & News
AI Regulation Accelerates
The EU’s AI Act, effective 2025, sets strict rules for high-risk AI, impacting global firms. New York leads U.S. state efforts with similar proposals. Businesses must audit vendors for transparency and data provenance to stay compliant. More here…
Generative AI ROI Under Fire
A16z partner Guido Appenzeller warns some vendors hype “AI agents” to inflate prices, often delivering basic chat interfaces. Demand clear ROI, time saved, and revenue gained before committing. Focus on proven use cases like automated reporting or forecasting. More here…
China’s Humanoid AI Boom
China’s $137B push for AI-powered humanoids signals a manufacturing shift. Organizations in Asia and North America must adopt AI for supply chain and operational efficiency to compete. Automate repetitive tasks to offset labor costs. More here…
🔧 Legacy Spotlight
Mid-size enterprises rely on legacy IT—ERP, CRM, and .NET systems—loaded with data but rarely AI-ready. Sprinklenet transforms these with tailored AI pipelines, using open source tools like LangChain for RAG or CrewAI for advanced agentic workflows, unlocking insights and automation without expensive overhauls. Explore Our AI Services.
The Challenge:
Legacy systems lack:
Semantic search for unstructured data, documents and PDFs.
Real-time AI insights, predictive analytics.
Secure integration with modern LLMs.
Solutions:
Build Secure APIs: Expose data, customer records, and inventory without touching databases.
Create Custom RAGs: Index legacy data with tools like Pinecone or Weaviate for secure AI queries.
Advanced Workflow Improvements: AI agents retrieve and act, auto-generating reports or triaging tickets.
LLM Integration: Embed OpenAI, Anthropic and other LLM APIs into workflows for minimal disruption.
Why It Matters:
Extend trusted systems’ lifespan.
Control costs with modular solutions.
Achieve ROI in weeks.
Tip: Start with one system, CRM for example, and one use case, churn prediction. Prototype with open-source tools like LangChain for security and scalability.
Turn legacy IT into a strategic powerhouse with AI.
🗓️ Coming Next: Seeing Is Not Believing
Deepfakes are no longer sci-fi; they’re a real threat to trust and security. In our next edition, we’ll unpack Sprinklenet’s R&D into advanced deepfake detection AI, including techniques to spot subtle visual and audio cues.
We’ll also explore emerging legislation, like the U.S.’s proposed DEFIANCE Act and EU mandates, aimed at curbing malicious deepfake use.
Learn how businesses can stay ahead of bad actors, protect their brand, and navigate this complex landscape.
Jamie Thompson: Sprinklenet
Right now, as you're considering how AI can truly transform your company, perhaps it's to streamline a key process or create a better customer experience.
The big question then becomes: how do you make that vision a practical and efficient reality?
At Sprinklenet, we're actively working with businesses like yours. We take the latest AI advancements and implement them to deliver concrete improvements you can see.
Our focus is on tangible outcomes, not just potential.
Not sure where to start with AI?
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✅ Discover where AI can add real impact
✅ Avoid common scaling mistakes
✅ Get clarity 👇🏼
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