How AI Helped Me Change My Eating Habits for the Better

10

October

2025

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When I moved out, the comfort of home cooking vanished. In my first uni term in late 2022, quick fixes became the norm, right as modern AI assistants started popping up on campus and online. With classes and a tight budget, cooking time shrank, even though training still demanded 3,000–3,300 kcal a day and roughly 160 g of protein to stay on track for recovery and performance. I leaned on a handful of reliable dishes at first, but the routine got stale, and searching for new, trustworthy recipes ate up time I didn’t have.

That same year, chat-based tools went mainstream and changed how I handled everyday planning, including food and fitness. Early meal-plan outputs were clunky, but the picture shifted in 2024 when GPT‑4o arrived: the free tier began offering guided web answers and richer, link-filled results I could act on quickly. Finally, AI offered accurate macro breakdowns paired with direct links, so I could jump straight to workable recipes without the usual scavenger hunt.

My prompts looked like this:

You are an expert nutritionist and sports dietician.

  • Please write a 7-day detailed meal plan for the goal of Muscle Gain, that will explicitly list:
  • the meals to have each day,
  • the ingredients of each meal,
  • the quantity of each ingredient  
  • the total macro  
  • calorie count of each day’s worth of meals.
  • Include breakfast, lunch and dinner.
  • Ensure the plan is written in a table format.
  • Write the exact amount of each food ingredient to be used.
  • Include links for each recipe
  • Please write a separate meal plan for each of the 7 days without repeating any days.
  • Ensure the answer fits within one chat response and do not repeat any days. Base this plan on the following criteria:
  • Meal Plan Goal: here describe your physical statistics

With that setup, the heavy lift of planning moved off my plate. Meals stayed diverse and aligned with training, and protein targets (about 1.4–2.0 g/kg) were easy to track because each recipe came with references and clean summaries. Next, I’m trialing agents to automate the weekly rotation, lists, and substitutions end-to-end, keeping everything current and ready to use.

Have you also used AI to help with planning your meals or workouts? Please comment down if you have any good suggestions!

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Can Blockchain Protect Creators in the Age of GenAI?

19

September

2025

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Generative AI is revolutionizing creativity, but it also exposes deep cracks in how ownership and intellectual property (IP) are managed. Most models are trained on vast datasets scraped from the internet, raising questions about whether creators gave consent, and how they can be recognized or compensated when their work is reused (Balan et al., 2023).

One promising answer lies in blockchain whose immutable, decentralized ledger, can record provenance, encode usage rights, and automate payments. The DECORAIT project shows how this could work: it allows creators to opt in or opt out of AI training, embeds provenance metadata through the Coalition for Content Provenance and Authenticity, and uses smart contracts to distribute rewards whenever a creator’s content contributes to a synthetic output (Balan et al., 2023).

Blockchain can underpin decentralized data marketplaces, allowing creators to monetize AI training data directly, while NFTs serve as tamper-proof certificates of authenticity and enable secondary royalties (Telles, 2025). Consulting leaders argue that blockchain may become the first mainstream safeguard against GenAI-driven IP risks. Encoding corporate knowledge assets (such as contracts, white papers, and presentations) into NFTs with embedded permissions, organizations could control how AI systems access and reuse their data (KPMG, 2023). Such mechanisms not only create new revenue models and reduce reliance on intermediaries but could also lower the risk of costly lawsuits, like the Getty Images case against Stability AI over alleged copyright misuse.

While challenges like blockchain scalability or regulatory uncertainty remain, the direction is clear. As GenAI blurs the boundary between human and machine creativity, blockchain provides a foundation for consent, attribution, and compensation which ensures that creators remain empowered in the AI economy.

Balan, K., Black, A., Jenni, S., Gilbert, A., Parsons, A., & Collomosse, J. (2023, September 25). DECORAIT — DECentralized Opt-in/out Registry for AI Training. arXiv.org. https://arxiv.org/abs/2309.14400v1

Blockchain and generative AI: A perfect pairing? (2023). KPMG. https://kpmg.com/us/en/articles/2023/blockchain-artificial-intelligence.html

Telles, Y. (2025, March 6). Generative AI and blockchain. Ventionteams. Retrieved September 19, 2025, from https://ventionteams.com/blog/generative-ai-blockchain

Popple, L. (2025, July 29). Getty Images v Stability AI: where are we after the trial – copyright? Taylor Wessing. https://www.taylorwessing.com/en/insights-and-events/insights/2025/07/getty-v-stability

How it works – Content Authenticity Initiative. (n.d.). https://contentauthenticity.org/how-it-works/

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