Suggestions
Lin Classon
Product Leader + Advisor - Strategy + Execution - Chaos Wrangler - Xoogler - x-McKinsey
Lin Classon is a senior executive with extensive experience in product management and strategy. She joined Kognitiv Corporation in February 2021 as SVP, Platform Strategies.13 Currently, she serves as SVP, Global Product Management at Kognitiv Corporation.4
Prior to joining Kognitiv, Lin worked at Google, bringing valuable experience from her time there to her role at Kognitiv.1 She is also a former McKinsey consultant, as indicated by her LinkedIn profile description "Product Leader + Advisor | Strategy + Execution | Xoogler | x-McKinsey".2
At Kognitiv, Lin is responsible for ensuring that emerging trends and critical business requirements of Kognitiv's clients are integrated into the company's Platform-as-a-Service and Managed Loyalty Services offerings.1 She works collaboratively with other executives to drive the company's vision for collaborative commerce, which focuses on enabling organizations to trade and exchange between peers in a secure network.3
Lin is an advocate for data-driven decision-making and has shared insights on machine learning and its applications in business.4 She emphasizes the importance of using data analysis as a tool for managing risks and making informed decisions, rather than seeking absolute certainty.4
Highlights
Every time I interact with a generative AI, I can’t help but feel like I’m talking to Amelia from the Amelia Bedelia books. Remember when she cut holes in a dress because she was asked to "remove spots"? AIs, like Amelia, follow instructions literally. Keep that in mind, and you'll remember to:
- Keep It Literal: Just like Amelia, AI takes everything literally. Be clear and specific; it won’t take offense.
- Give Context: Explain the background and context and the outcome you want, including the desired format.
- Show Not Just Tell: Provide an example (template, article in the same tone, paper in the same format, etc.) to ensure there is no room for misinterpretation.
- One Step at a Time: Break your requests into clear, manageable steps.
- Force It to Wait: For complex tasks, tell the AI to pause after each step and ask for your next instruction.
- Tweak and Tune: If all else fails, start another chat and iterate on your previous attempt. Just like Amelia's employers who never considered letting her go, we shouldn’t give up on these tools, even when they make you want to pull your hair out* sometimes😅
- Warning: In the world of Amelia Bedelia, "pull your hat out" is a very dangerous figure of speech 😆
Not sure how this is going to affect my LinkedIn algo but I want to talk about tax law and accounting rule change: Is it just me, or are we not talking enough about the Tax Cuts and Jobs Act of 2017 and its impact on big tech companies?
Since 2022, the shift from immediate expensing to the requirement to capitalize and amortize R&D costs over several years is reshaping how companies approach innovation and staffing. This new accounting requirement - five years for domestic expenses and a lengthy 15 years for foreign ones - could be influencing not just financial statements but also strategic decisions on where and how R&D teams are deployed globally. Even though various legislative proposals have been introduced to either repeal the requirement to amortize R&D costs or delay its implementation further, there is no telling whether any will be successful and when.
As we navigate these changes, it's crucial to question: How are these tax modifications affecting where companies choose to locate their R&D activities? Could this be driving the trends we see in nearshoring or onshoring of technological development? And what about the broader implications for innovation in the tech sector?
