Date: 04-Jan-2025

Hey {{first_name | AI enthusiast}},

Wish you all a very happy and prosperous New Year!

Today’s date is an important slash sentimental one for me! Today marks the 27th anniversary of the date that I started my working career as newly minted engineer.

I started work in a tech. consulting company, not knowing how important a part, technology would play in my career. And one day lead to me publishing a newsletter on AI and technology.

Alright, enough reminiscing! In this edition, we have a ton of goodies to get you thinking about the future of work in these times of Gen AI and robotics.

Hope you enjoy it!

— Renjit Philip

PS: If you want to unleash the power of AI agents to grow your business, setup time speak to me, here»

AI is no longer just changing how work gets done. It is forcing a rethink of income, ownership, and the role work plays in life.

This shift is not theoretical anymore. Some of the most influential tech leaders are openly planning for it.

The idea of a lifelong full time job is quietly eroding. Income is starting to detach from hours worked. The harder debate now centers on ownership, upside, and meaning that work provides.

What tech leaders are really saying

Elon Musk frames the future as universal high income. AI and robotics can potentially create abundance at a scale where poverty fades. Saving money matters less when goods and services become cheap. In his framing, automation upgrades daily life. It shifts from threat to default condition.

Bill Gates takes a slower and more practical view. He imagines a two or three day workweeks. Productivity gains compound before jobs disappear. He reckons that manufacturing, logistics, and food systems change first. Labor demand reshapes gradually, not overnight.

Jamie Dimon of JP Morgan, echoes this transition logic. He has suggested a three and a half day workweek. Even conservative financial institutions see shorter schedules ahead.

This signals a hybrid era. Automation rises while work still exists.

Jensen Huang of NVIDIA, remains cautious on redistribution models. Universal income and wealth are unresolved questions. AI may democratize capability like information once did.

Income systems lag capability shifts.

Sam Altman focuses on ownership rather than payouts. He proposes a universal basic wealth tied to AI capacity. People receive stakes in the AI systems or companies themselves. His concern is psychological as much as economic. Passive dividends alone do not create a purpose in people’s lives.

Dario Amodei of Anthropic introduces urgency into this debate. He warns that half of entry level white collar jobs could vanish. Unemployment could spike within a few years.
The transition phase may hurt even if abundance follows. Meaning cannot rely on employment alone.

Demis Hassabis, co-founder of DeepMind, talks about radical abundance. Advanced AI could end zero sum economics. Distribution of wealth then becomes a political, not technical matter to resolve. The open question remains how people spend their time.

Signals founders should not ignore

Reporting highlighted by TechCrunch points to 2026 as a turning point. AI could shift from task support to full role automation. A large share of companies reportedly plan workforce replacement by then.

However, there is an opportunity here: New AI focused roles appear at the same time. Builders, operators, and integrators become critical.

🔹 So what? What this means for builders:

Founders face pressure and opportunity together. Products must work in a world with fewer traditional roles. Demand will rise for training, orchestration, and transition tools. from a non-AI world to an AI first world of work.

Design for the messy middle- This future is not only about machines doing the work.
It is about who earns, who owns, and who feels relevant.

The companies built for the transition phase will matter most. That middle period will decide whether AI becomes a safety net, a wealth engine, or a breaking point.

Someone published the biggest haul of system prompts on GitHub. And it has grown by leaps and bounds over the last year. I do worry about the implications of leaking system prompts and the security vulnerabilities that it implies.

But in the meantime, it is a useful tool to study how system prompts are defined and designed. For those of you build AI applications, this can be instructive.

Here is the link to it»

Grok Collections API: Built-in RAG for Fast, Accurate Data Retrieval

The new Grok Collections API lets teams turn messy documents into searchable knowledge stores without wrestling with infrastructure; fast indexing and hybrid search make long files actionable.

🔹 Key Insights

For founders building AI-driven workflows, this API turns buried data into a searchable engine without heavy backend work; developers can focus on insights rather than infrastructure. Try it out here» link

In the south of China, a humanoid robot straight out of a sci-fi movie was spotted walking side by side with real armed cops.

It happened in Shenzhen, where the machine, EngineAI T800, casually joined police patrol like it’s 2049 already.