Read more: https://knowledge.insead.edu/strategy/ai-maturity-pyramid

Disposable Software — Software Is Now Disposable

The economics of software development are changing rapidly. As AI reduces the cost of writing code, software is becoming increasingly disposable—built quickly, used for a specific purpose, and discarded when it has served its purpose. The article explores how this shift could fundamentally change product development, experimentation, and the way we think about software itself.

Read more: https://auren.substack.com/p/disposable-software-software-is-now

GitHub Spec Kit

GitHub’s Spec Kit introduces a specification-first approach to AI-assisted software development. Instead of jumping directly into code generation, developers begin with structured specifications that AI agents can understand, validate, and implement consistently. A useful glimpse into how software engineering workflows may evolve in an AI-native world.

Read more: https://github.com/github/spec-kit

Leadership — Feynman’s Thinking Habit

Richard Feynman was renowned not just for his intelligence, but for his relentless curiosity and ability to simplify complex ideas. This article explores the thinking habits that made him exceptional—questioning assumptions, explaining concepts in simple language, and embracing continuous learning. A timeless reminder that great thinking often begins with intellectual humility.

Read more: https://thomas-oppong.medium.com/this-is-feynmans-thinking-habit-it-made-him-a-genius-c79cfabaee7c

Fun Stuff

https://blog.devgenius.io/best-programming-humor-compilations-2021-623473bfb0d

The post <strong>The AI Maturity Pyramid</strong> appeared first on Openturf Technologies.

State of the Software Engineering Job Market in 2026

The software engineering market is showing signs of recovery, with hiring increasing across several regions and companies resuming growth after a prolonged slowdown. Beyond the numbers, the article highlights how AI is reshaping hiring patterns, skill expectations, and the types of engineering roles organizations are prioritizing.
Read more: https://newsletter.pragmaticengineer.com/p/state-of-the-job-market-2026

OpenAI’s GPT-5.5 Powers the Next Generation of Coding Agents

OpenAI’s latest GPT-5.5 model is now driving Codex, enabling more capable software engineering agents that can reason across larger contexts, coordinate tasks, and assist throughout the development lifecycle. The article offers a glimpse into how AI agents are moving from simple assistants toward collaborative development systems.
Read more: https://blogs.nvidia.com/blog/openai-codex-gpt-5-5-ai-agents/

Beware the New AI-Powered Travel Scams

From fake booking confirmations to AI-generated accommodation listings, travel scams are becoming increasingly sophisticated. A useful reminder that while AI improves experiences, it also improves deception. Sometimes cybersecurity advice doubles up as travel advice. 😄
Read more: https://www.fastcompany.com/91549123/top-travel-scams-beware-ai-tripadvisor-mcafee

Fun Stuff

The post Reshuffle — Launching the Interactive Companion to the Book appeared first on Openturf Technologies.

AI Toolkit for VS Code — January 2026 Update

Microsoft’s latest update to the AI Toolkit for VS Code brings deeper workflow-aware integration, enabling task execution, evaluation planning, and multi-file reasoning directly inside the editor. A notable leap toward truly AI-native developer environments.
Read more: https://techcommunity.microsoft.com/blog/azuredevcommunityblog/🚀-ai-toolkit-for-vs-code-january-2026-update/4485205

Leadership — AI as the Engineer’s “Iron Man Suit”

Google Cloud’s head of gaming describes AI not as a replacement for creativity but as an amplifier of human capability — an “Iron Man suit” for developers. A sharp leadership perspective on empowering teams to use AI without losing ownership or agency.
Read more: https://www.businessinsider.com/ai-gaming-developers-jack-buser-google-2026-1

Managerial — Reality Check on Enterprise AI Adoption

Industry analysis highlights that 95% of early AI pilots fail — primarily due to unclear KPIs, lack of operational discipline, and misaligned expectations. A grounded, practical take for managers planning 2026 AI roadmaps.
Read more: https://www.linkedin.com/pulse/ai-news-highlights-jan-1320-2026-ali-moheyaldeen-l6fjc

OpenAI’s Prism App for Scientific Research

OpenAI launched Prism, a free AI-driven research assistant that helps scientists write papers, manage references, collaborate, and explore ideas. A refreshing look at AI crossing into academic workflows.
Read more: https://www.techradar.com/pro/were-still-early-but-its-clear-that-ai-will-play-a-meaningful-role-in-how-science-advances-openai-launches-free-prism-app-for-scientific-research

Fun Stuff — Programming Humor

Our usual fun stuff here

The post OpenClaw — The Open-Source Agent Framework Reshaping AI Workflows appeared first on Openturf Technologies.

Every month, Nibbles attempts something simple and deceptively hard:
to curate articles that are worth your time.

Not trending.
Not loud.
Not driven by the algorithm of the week.

As the year comes to a close, we found ourselves asking a harder question:

If someone were to read only a handful of articles from this entire year,
which ones would still matter five or ten years from now?

The result is this Hall of Fame – This Year.

These five articles were not chosen because they were popular, controversial, or technically flashy. They were chosen because they address first principles—how we think, how we build, how we sustain careers, and how we navigate change without losing our bearings.

You will notice a pattern:

• Fewer tools, more thinking
  
• Less hype, more judgment
  
• More emphasis on why than how
  

If Nibbles has ever been useful to you, this is the edition we hope you’ll return to—quietly, repeatedly, and without urgency.

Happy reading and Wish you a happy and Prosperous 2026

 — Team Nibbles

Hall of Fame – Top 5 Articles 

Classic Software Engineering — Multi-Tenant Architecture Patterns

Themes: Architecture · Systems · Scalability

Multi-tenancy is one of those problems that looks simple—until it isn’t.
This article stands out because it does not rush to prescribe solutions. Instead, it walks through trade-offs, isolation strategies, and operational realities that apply regardless of cloud provider, database, or framework.

A genuinely timeless systems-engineering read.

What Went Wrong with the AWS Outage

Themes: Architecture · Reliability · Engineering Judgment

Every large outage eventually becomes a lesson in humility.
This article belongs to the lineage of classic post-mortems that engineers revisit whenever systems fail at scale.

Beyond the technical details, it reinforces an enduring truth:
automation without restraint amplifies risk.

Software Is Changing (Again) — Key Takeaways from Andrej Karpathy

Themes: AI · Architecture · Software Evolution

Few talks manage to give language to a shift that many feel but cannot yet articulate.
Karpathy’s framing of Software 1.0, 2.0, and 3.0 does exactly that.

This piece will likely be referenced for years as engineers recalibrate what it means to “write software” in an AI-first world.

We Need to Start Thinking of AI as “Normal”

Themes: AI · Engineering Philosophy · Judgment

This article performs a rare but necessary function: deflating both hype and fear.

By treating AI as a general-purpose technology—rather than something mystical or existential—it helps engineers return to sober thinking, responsibility, and practical integration. A grounding read that will age well.

Plato’s Cave and the Stubborn Persistence of Ignorance

Themes: Philosophy · Judgment · Craft

Using Plato’s Allegory of the Cave, this article explores how people remain attached to familiar illusions—even when better explanations exist.

Its relevance to modern engineering is subtle but profound:
abstractions, tools, metrics, and even AI can keep us comfortable in the cave unless we actively question what we are seeing.

A rare philosophical piece that quietly sharpens technical judgment

Closing Note

This year’s Hall of Fame reflects a shift.

Less obsession with tools.
More emphasis on judgment.
A renewed respect for fundamentals—even as the surface of software continues to change.

If you keep just five articles from this year, we believe these will repay repeated reading.

That, for us, is the quiet promise of Nibbles.

The post <strong>Best of Nibbles 2025</strong><strong><br></strong> appeared first on Openturf Technologies.

Read more: Network World article 

Engineering Leaders on Strategizing AI for 2026

A roundup of senior engineering leaders discussing how teams are aligning on AI-led feature rollout, balancing speed vs stability, scaling distributed teams, and redefining manager skills for “agentic” AI systems.

Read more: Notchup

10 Essential Software Design Best Practices for 2025

A refresh on evergreen software engineering discipline: principles like SOLID, DRY, TDD, code review, deploy small & fast — useful for teams wanting less AI-centric focus.

Read more: DocuWriter.ai

Modern Caching Strategies Beyond Redis and Memcached

A deep look into caching architectures in the age of edge computing: cache invalidation, tiered layers, adaptive TTLs, and how CDN-level intelligence reshapes classic system-design choices.

Read more:  Infoq

Fun Stuff — Programming Humor

“Why did the developer go broke? Because he used up all his cache 💸”

The post What Went Wrong with the AWS Outage appeared first on Openturf Technologies.

🔗 Read the full post

AI Killed my Job

In this article, tech workers from companies like TikTok and Google share personal accounts of how management has deployed AI to reduce, degrade, or outright replace their roles, often using the promise of automation to justify layoffs. The piece highlights that it’s not AI itself doing the firing—it’s the decisions and justifications made by bosses leveraging AI capabilities 🔗 

Read the full article

I Teach Creative Writing. This is what AI is doing to students

The article argues that AI tools like ChatGPT are reshaping education—not primarily through student cheating, but via their use by teachers and institutions for grading, lesson planning, and feedback. It raises concerns that over-reliance on AI may undermine critical thinking, reduce face-to-face learning, and dilute the educational value of writing and discussion. The author calls for a reevaluation of how AI is integrated into classrooms, with a renewed focus on preserving human-led pedagogy.

Read the full article

These Premium Leaked Startup Prompts Became My Secret Weapon”

The author describes how accessing leaked system prompts from billion‑dollar AI startups transformed their own prompting strategy—until then, their outputs were bland, inconsistent, and lacked personality. Seeing how production-grade prompts are structured gave them the insight to elevate their AI apps, enabling richer, more reliable behavior.

🔗 Read the full article on Medium

Fun Stuff

Our usual fun stuff

The post How I keep up with AI progress (and why you must too) appeared first on Openturf Technologies.

• Software 1.0 – traditional hand‑written code.
  
• Software 2.0 – neural‑network “weights as code”, produced by training on data.
  
• Software 3.0 – large‑language‑model computers that you “program” with English prompts; the prompt is now the source code. 

Take a look at the video here

Learnings from two years of using AI tools for software engineering

Birgitta Böckeler’s guest post in The Pragmatic Engineer distils two years of day‑to‑day experimentation with GenAI coding tools—showing how they evolved from “autocomplete on steroids” to agentic assistants—and spells out what really works: tight verification loops, shared prompt conventions, and deliberate ROI tracking rather than hype-driven adoption.

Read the article here

I Convinced HP’s Board to Buy Palm for $1.2B. Then I Watched Them Kill It in 49 Days

Ex‑HP CTO Phil McKinney explains how he championed Palm’s $1.2 B acquisition for its ahead‑of‑its‑time WebOS, then watched new leadership misread the deal and axe the project within weeks—turning a potential mobile breakthrough into a swift corporate fiasco. Read the full story here

How I Spent 17,784 Hours in 5 Years as a Startup Founder

Startup founder Sam Corcos logged every 15‑minute block of the 17,784 hours he worked building Levels over five years and concludes that rigorously tracking time (and spending it on energizing tasks like still writing code) prevents burnout and keeps priorities clear even as a company scales. Read the piece. Read it here 

Fun Stuff

Our usual fun stuff

The post Key take‑aways from Andrej Karpathy’s keynote “Software Is Changing (Again)” appeared first on Openturf Technologies.

Claude Shannon on Creative Thinking

What are the essential three things for being creative?

• Training and Experience
• Certain Amount of Intelligence or Talent
• Motivation

The full article can be downloaded from here

Personal Discipline: What Is It and How To Create One

The article on Durmonski.com emphasizes the importance of personal discipline, describing it as the ability to regulate behavior, form new habits, and maintain consistency despite challenges. It outlines steps to create effective personal discipline by setting healthy boundaries, avoiding overly strict or non-existent rules, and focusing on long-term goals and self-improvement.

You can read the full article here

The Law of Leaky Abstractions

To excel in no code or low code platforms – you need to know how to code – Agree or disagree ? Find out here from one of the founders of stack overflow

It is ok to have an ordinary mind

“I think people who keep an ordinary mind are more relaxed, have no internal distortions, observe things with a more nuanced perspective, are practical and have more patience” – Zhang Yiming, Byte Dance CEO. Read the full transcript here. The counter perspective is refreshing.

The Forty-Year Programmer

You wish to be a ‘coder for life’. This article gives an insight. We love them.

The post Nibbles 50 appeared first on Openturf Technologies.

For a comprehensive understanding, you can read the full article here: Is AI Normal?

Prometheus metrics at 37signals

The article “Prometheus metrics at 37signals” from the 37signals Dev blog details how the company employs Prometheus for observability in its on-premises infrastructure. The Ops team at 37signals migrated applications from the cloud back to their own data centers, necessitating robust monitoring solutions. Prometheus, an open-source monitoring tool, was chosen for its time-series data storage capabilities and its query language, PromQL. The team utilizes Prometheus to ingest, store, and alert based on metrics, ensuring they can confidently manage infrastructure and applications on-premises. The article provides insights into the architecture, metrics generation, and operational practices involved in their Prometheus setup.​

For a comprehensive understanding, you can read the full article here: Prometheus metrics at 37signals

The Batch Issue #298 from DeepLearning.AI covers key AI developments, including:

• OpenAI’s New Models: Introduction of five new models (GPT-4.1 series), excelling in benchmarks and multimodal reasoning.
  Hugging Face’s Open Robot: A new open-source robotics framework to foster innovation.
  
• U.S. AI Chip Regulations: New U.S. export controls on advanced AI chips, impacting global AI development.
  
• Multimodal LLMs: Advancements in text-only LLMs to handle multimodal inputs.
  

Read the full issue here: The Batch Issue #298

Technology Radar

The Thoughtworks Technology Radar Vol. 32, published in April 2025, offers a comprehensive overview of emerging technologies shaping the software development landscape. This edition highlights the pervasive influence of Generative AI (GenAI) across various facets of software engineering, from coding assistants to data management.​

Key Highlights:

• Generative AI in Software Development: The Radar identifies 48 AI-related technologies, emphasizing tools like AI-assisted coding assistants and software engineering agents. These tools are designed to enhance developer productivity by automating code generation and error correction, though they recommend maintaining human oversight to ensure quality and accuracy. ​ThoughtWorks
  
• Evolving Observability Practices: With the increasing complexity of distributed systems, there’s a shift towards advanced observability techniques. The adoption of OpenTelemetry and the development of Large Language Model (LLM)-based observability tools are highlighted as significant trends in monitoring and maintaining system health. ​ThoughtWorks
  
• Data Product Thinking: The Radar advocates for treating data as a product, emphasizing the importance of clear lifecycle management, quality standards, and user-centric design in data handling practices. ​ThoughtWorks
  
• Advanced Retrieval Techniques in GenAI: Innovations like Corrective RAG, Fusion-RAG, and Self-RAG are introduced to optimize the retrieval process in Retrieval Augmented Generation systems, aiming to improve the relevance and accuracy of AI-generated responses. ​ThoughtWorks
  

For a detailed exploration of these trends and more, visit the Thoughtworks Technology Radar Vol. 32

Fun Stuff

Our usual fun stuff

The post We need to start thinking of AI as “normal” appeared first on Openturf Technologies.

Key Points:

1. AI Adoption and Tooling Trends:
   Since the release of ChatGPT in 2022, AI tools have become mainstream, with 75% of developers using them. However, we’re still early in the innovation cycle, and 2025 is expected to bring more complex AI agents.
   
2. Divergent Usage Patterns:
   
   • Bootstrappers: Use AI to go from design to working prototypes quickly, making AI ideal for rapid validation.
     
   • Iterators: Use AI for daily development, including refactoring, test generation, and improving efficiency.
     
3. The 70% Problem:
   AI accelerates the first 70% of development but struggles with the final 30%, where expertise is required to ensure maintainability, scalability, and quality. This creates a paradox where experienced engineers benefit the most from AI, while juniors may unknowingly produce fragile, hard-to-maintain systems.
   
4. Knowledge Paradox and Pitfalls:
   
   • Senior developers refine AI-generated code by applying expertise in modularization, error handling, and architectural decisions.
     
   • Juniors, lacking this intuition, often accept AI suggestions blindly, resulting in “house of cards” code that collapses under real-world pressure.
     
5. Practical Patterns for AI Usage:
   
   • AI First Draft: Use AI for initial code but refactor and validate rigorously.
     
   • Constant Conversation: Start fresh AI prompts for each task, maintaining tight review loops.
     
   • Trust but Verify: Manually review AI-generated critical code paths, test rigorously, and maintain high standards.
     
6. Rise of Agentic Software Engineering:
   AI is evolving beyond code generators into collaborative agents capable of taking initiative. Future tools will seamlessly integrate visual, verbal, and environmental inputs, moving towards an “English-first” development paradigm where natural language instructions play a primary role.
   
7. Return of Software as a Craft:
   Rapid AI prototyping may lead to a resurgence in emphasis on polish, error handling, and user experience, with developers focusing on delivering well-crafted, reliable software.
   
8. AI Tools’ Limitations Beyond Coding:
   While AI excels in generating code, software engineering involves much more: planning, reviewing, verifying, shipping, maintaining, and monitoring. AI currently assists only with the “build” stage, but experienced engineers are still needed for everything else.
   
9. AI Agents: Promise and Unknowns for 2025:
   AI agents like Devin, though in their infancy, will likely proliferate in 2025. These agents trade latency for accuracy, but their true productivity impact remains to be seen.
   
10. Increased Demand for Experienced Engineers:
    As AI tools produce more code, complexity increases, requiring experienced engineers to manage, refine, and maintain systems. This suggests that demand for senior developers may actually rise, rather than decline, in the AI-driven future.
    

Conclusion:

AI tools enhance software development by accelerating known patterns, enabling rapid prototyping, and automating routine tasks. However, their limitations necessitate human expertise for building robust, maintainable systems. The future lies in balancing AI assistance with engineering rigor, ensuring that AI complements rather than replaces human judgment.
👉 Read the full article here

Malcolm Gladwell says people who succeed against the odds usually practice these 5 daily habits

This article highlights five daily habits that Malcolm Gladwell identifies as common among people who succeed against the odds: (1) deliberate practice to build mastery, (2) celebrating small wins to maintain motivation, (3) turning adversity into creative solutions, (4) staying curious and open to new perspectives, and (5) focusing on meaningful goals beyond just winning. These habits help build resilience and long-term success.

👉 Read the full article here

The power of the humble embedding

This Stack Overflow article explores the importance of embeddings in AI models, featuring insights from Edo Liberty, Founder and CEO of Pinecone. It highlights how embeddings improve semantic search, enhance vector database efficiency, and support Retrieval-Augmented Generation (RAG). The conversation also touches on fine-tuning models and optimizing AI workflows.

👉 Read the full article here

Foundation Model for Personalized Recommendation

This Netflix Tech Blog article discusses how Netflix is transitioning from maintaining numerous small, specialised recommendation models to a unified foundation model. Inspired by advances in large language models (LLMs), this approach centralizes user interaction data and distributes learnings to other models. By leveraging large-scale data and optimizing tokenization of user interactions, Netflix aims to improve recommendation accuracy, scale efficiently, and reduce maintenance costs.

👉 Read the full article here

Fun Stuff

👉Our usual fun stuff

The post <strong>How AI-assisted coding will change software engineering: hard truths</strong><strong><br></strong><strong> </strong> appeared first on Openturf Technologies.