The AI Daily Brief: Artificial Intelligence News and Analysis

Episode Title: AI New Year’s: The 10-Week AI Resolution
Host: Nathaniel Whittemore (NLW)
Date: December 31, 2025

Episode Overview

This special end-of-year episode centers on a practical, self-guided "10-Weekend AI Resolution"—a framework developed by NLW to help listeners build comprehensive AI fluency through hands-on projects over the first months of 2026. The episode lays out 10 modular, skill-building weekend projects, each designed to develop core AI capabilities, broaden exposure to tools, and ingrain real-world workflows across automation, research, data, and more. NLW’s accessible and motivating tone encourages listeners of all backgrounds to participate, emphasizing tangible progress and sharing in the community.

Key Discussion Points & Insights

Why a 10-Weekend AI Resolution?

• Purpose: To give listeners a realistic, project-based path to AI fluency by engaging with practical tools and workflows, not just theory.
• Modularity: "This is not a course in the sense that one thing builds upon another. It's 10 different projects [...] practical by default, forcing outputs, not theory, that are highly completable where each project ends with something real." (06:07)
• Audience: Projects are beginner- and intermediate-friendly, each with advanced modifiers for further challenge.

The 10-Weekend AI Project Framework

[07:55] "Call it a self-guided path to AI fluency."

Project Structure:

• Modular—do in any order
• Practical—create something you’ll actually use
• Beginner-friendly with advanced options
• Designed for ~2-3 hours per project
• End deliverable for each

Evaluation Metrics (09:55):

• Outcome quality
• Time saved vs manual process
• Repeatability
• Real-world utility

Preparation (11:15):

• Spend ~30 minutes setting up folders and accounts before starting
• Choose your toolset ahead of time (suggested: Lindy, N8N, Make for automation; Replay, Lovable, or Google AI Studio for Vibe coding)

Weekend-by-Weekend Breakdown

1. [12:39] Resolution Tracker Web App (Vibe Coding)

• Build a web app to track progress through the 10 weeks
• Features: Checklist, notes, progress bar, optional time tracker, file uploads
• Advanced: User authentication, collaboration, mobile optimization
• "We're starting with this both from a practical standpoint [...] as well as by giving you something super tangible right from the beginning." (14:30)

2. [17:02] Model Mapping – Your Personal AI Topography

• Compare several AI models for different tasks—beyond defaulting to one model
• Run the same task through each; document preferences and differences
• Deliverable: One-page “rule of thumb” notes
• Advanced: Build tool-use matrix, include cost and editing time, track consistency over time

3. [20:46] Deep Research Sprint

• Use deep research features in LLMs for a real decision/research question
• Challenge the model, request counter-evidence, iterate and stress-test
• Advanced: Run research through multiple tools, manually cross-check outputs
• "The idea is to close the gap between 'I know AI can theoretically do research' and 'I trust this enough to make a decision.'" (21:40)

4. [24:45] Data Analysis Project

• Apply AI to analyze a real or public dataset
• AI suggests data cleaning, key metrics, hypotheses; deliver insights and actions
• Create summary memo
• Advanced: Build repeatable analysis pipeline or prompt template for ongoing use

5. [28:32] Visual Reasoning – Infographics & Diagrams

• Use tools like nanobananapro or ChatGPT Images 1.5 to visually explain complex ideas
• Emphasis on logical structure, not just aesthetics
• Deliverable: Infographic/diagram that makes your idea clear at a glance
• Advanced: Design a reusable template or visual system; create a library of frameworks

"The project is done when you can explain the idea faster with the visual than with words. When someone who sees the image gets the point without you having to explain it." (32:38)

6. [35:46] Information Pipeline: From Raw Data to Presentation

• Build a workflow using NotebookLM and Gamma to turn information (e.g., reports, notes, transcripts) into professional outputs: summaries, FAQs, decks, or websites
• Advanced: Multiple formats at once; experiment with presentation/website style

7. [41:56] Automation #1: Content Distribution Machine

• Build an automation to handle content production or distribution (using Lindy, N8N, etc.)
• Steps: Trigger > Transformation > Routing > Review > Logging
• Example: Summarize article links into weekly email, auto-generate social posts
• Advanced: Chain automations, add conditional logic or error handling

8. [45:15] Automation #2: Productivity Booster

• Build an automation for inbox follow-ups, lead tracking, or meeting prep
• Helps ensure tasks don’t fall through the cracks
• Steps: Similar to previous automation—trigger, transform, route, review, log
• Example: Auto-summarize emails, draft replies, log next actions
• Advanced: Build a meeting prep bot for scheduled events

9. [49:42] Context System: AI-Ready Professional Profile

• Create and store a reusable "context doc"—your role, projects, preferred communication, tasks, terminology
• Also build your own AI operating system to store best prompts, logs, and routines
• Habit: Regularly update and review system
• Advanced: Multiple profiles (work/personal), include writing samples for better context

10. [53:40] AI-Enabled App Creation (Advanced Vibe Coding)

• Use Google AI Studio to create an AI-native product/app: eg, chatbot trained on company FAQs, voice agent, mini agent extracting info from documents
• Advanced: Build for others, get feedback, refine toward a real prototype

Bonus/Substitute: [57:21] Agent Evaluation Gauntlet

• Test agentic tools (like Manus, Genspark) against standard LLMs on 3 types of tasks: research, operations, production
• Score on accuracy, hallucinations, citations/traceability, constraint-following, output usefulness, repeatability
• Deliverable: "Agent scorecard" and specific use cases list going forward

"Most people's mental model is still in chatbot. This weekend is going to update that mental model with firsthand experience of what agents can and can't do reliably." (58:02)

Final Inspiration & Community Engagement

Recap of Outcomes:

"At the end of these 10 weeks you'll have built a personal tracker, a deep research workflow, visual reasoning skills, two active automations, a deployed AI power tool, an AI tool topography, an analysis pipeline, an info processing stack, and a personal AI operating system." (59:40)

• NLW encourages listeners to share their projects at aidbnewyear.com (a free, community-driven hub).
• Stresses that this challenge is open and collaborative, with no upsell—just “a place for people to share what they're doing as we kick off a great 2026.” (01:00:17)
• Expresses gratitude for listeners’ engagement and excitement for the coming year

"You will also, as I said at the beginning, be ahead of 99.99% of people when it comes to the full breadth of what AI can do." (59:40)

Notable Quotes & Memorable Moments

• On the project’s intent:
  "If you do all of these, at the end of these 10 weeks you'll have built a personal tracker, a deep research workflow, visual reasoning skills, two active automations, a deployed AI power tool, an AI tool topography, an analysis pipeline, an info processing stack, and a personal AI operating system." (59:40)

• On why focus on practical outputs:
  "We're basically creating context to go pretty deep on the core capabilities that represent a huge part of the work that we can do with AI right now." (23:33)

• On shifting mental models:
  "Most people's mental model is still in chatbot. This weekend is going to update that mental model with firsthand experience of what agents can and can't do reliably." (58:02)

• On knowledge sharing:
  "Like I said, check out aidbnewyear.com which will be a community hub for anything anyone wants to share about this. Obviously I should say I think this goes without saying, but just for the sake of it, that is a free experience. There's no paid upseller course or anything here, just a place for people to share what they're doing as we kick off a great 2026." (01:00:17)

Timestamps for Major Segments

| Segment | Timestamp | |-------------------------------------------------|-------------| | Why a 10-Weekend AI Resolution | 04:20 | | Project Structure, Evaluation, and Prep | 06:07–12:12 | | Weekend 1: Resolution Tracker | 12:39 | | Weekend 2: Model Mapping | 17:02 | | Weekend 3: Deep Research Sprint | 20:46 | | Weekend 4: Data Analysis | 24:45 | | Weekend 5: Visual Reasoning | 28:32 | | Weekend 6: Information Pipeline | 35:46 | | Weekend 7: Content Automation | 41:56 | | Weekend 8: Productivity Automation | 45:15 | | Weekend 9: AI Operating System | 49:42 | | Weekend 10: AI-Enabled App | 53:40 | | Bonus: Agent Evaluation Gauntlet | 57:21 | | Program Wrap-up and Community Invitation | 59:40+ |

Episode Takeaways

• Accessible and actionable: The 10-weekend challenge breaks down the intimidating landscape of AI into manageable, real-world skills.
• Community-oriented: Listeners are encouraged to share progress and learnings, building collective know-how.
• Evergreen skills: While some tools may evolve rapidly, workflows and thinking patterns will remain valuable.
• Future-focused: Completing the challenge puts participants ahead in the coming year’s fast-moving AI ecosystem.

Listen to this episode to get inspired, set up your year, and build AI habits and skills that will make a real impact in 2026—and beyond!