OG Approved - No BS Tech News # 93

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Latest Industry Trends and News 📈🌐

👉 Sam Altman says OpenAI will have a ‘legitimate AI researcher’ by 2028

💡What’s the Big Idea?

Sam Altman says OpenAI is targeting 2028 to build a fully autonomous “legitimate AI researcher” that can independently conduct research and discover new science.

🔑 Key Takeaways for Readers:

1. OpenAI is aiming for an intern-level research assistant by around September 2026 and then a full-fledged autonomous AI researcher by 2028.

2. This shift marks a change from AI as a helper (chatbots, assistants) to AI as an independent thinker—able to propose, conduct, and iterate research rather than simply respond.

3. The timeline is bold and likely optimistic—critical: achieving human-level research means not just data processing but hypothesis-generation, methodology, domain mastery, and novelty; many outside the company doubt or caution the “by 2028” claim.

⚡ Why It Matters (OG lens):

Because if AI goes from assistant to researcher, the whole value chain of human work—especially knowledge work—changes: it flips the power dynamics and forces leaders to ask not “How can we use AI?” but “What roles do humans have left when machines discover what we used to?”

⭐OG Rating:

4/5 I give it a 4 because the ambition is real and signals a strategic pivot (valuable), but the timeline is aggressive and execution risk is high

👉 Cursor 2.0 pivots to multi-agent AI coding, debuts Composer model

💡What’s the Big Idea?

Cursor 2.0 shifts from being a simple AI-assisted coding editor to a full multi-agent platform with its own proprietary model Composer, promising faster, deeper, outcome-driven code generation and review.

🔑 Key Takeaways for Readers:

1. Composer is built for “low-latency agentic coding” and claims to be 4x faster than similar models, with most conversational turns under 30 seconds.

2. The user interface is re-imagined: instead of “files first”, Cursor 2.0 is “agent-first”—you assign intent and let multiple agents work in parallel on isolated code copies via git worktrees or remote machines.

3. With this pivot, the bottleneck is shifting: less “write code” and more “review code & test agents’ output”. Cursor adds native browser tools so agents can self-test, iterate, and you supervise rather than build from scratch.

⚡ Why It Matters (OG lens):

Because if you stop being the one typing lines and instead become the architect of agent teams, your role shifts – from “coder” to “orchestrator of machine coders”, and that changes skill-sets, org structure and what “development productivity” even means.

⭐OG Rating:4/5 I give it a 4 because the ambition is major and this is a clear directional shift in software dev tooling—but execution risk is high (parallel agent workflows, trust in model output, real integration) so it stops short of a perfect score.

👉 Tech giants are spending big on AI in rush to dominate the boom

💡What’s the Big Idea?

Tech giants are pouring hundreds of billions of dollars into AI infrastructure in a be-all-end-all race to dominate the next era of computing

🔑 Key Takeaways for Readers:

1. Major firms such as Microsoft, Alphabet Inc. (Google), Meta Platforms, and Amazon.com, Inc. are each committing multi-$10 billion capex in 2025 just for AI data-centers, chips, and infrastructure.

2. This spending spree is not incremental — it’s structural: the bets are on owning the base layer (compute, data, cloud) so future value shifts away from software + apps to infrastructure + model-control.

3. The scale of investment raises a dual risk: If the AI boom plays out, those who invested massively early will dominate; but if it stalls or the value chain shifts elsewhere (e.g., alternative models, regulation, chip supply), these companies may lose big on sunk costs.

⚡ Why It Matters (OG lens):

Because when infrastructure becomes the battleground, every enterprise, every business model, and every professional must ask: “Do I ride the wave or get crushed under the whales building the wave?”

⭐OG Rating:

4.5/5 I rate this a 4.5 because it’s essential intelligence on where power and dollars are aggregating — glaringly obvious yet under-acknowledged in many circles — the only reason it’s not a full 5 is because the long-term ROI and winners aren’t yet proven, so there’s still a major ‘if’.

👉 Meta forecasts bigger capital costs next year as Zuckerberg lays out aggressive AI buildout

💡What’s the Big Idea?

Meta Platforms is preparing to ramp up capital spending sharply in 2026 by front-loading an aggressive AI infrastructure buildout under Mark Zuckerberg.

🔑 Key Takeaways for Readers:

1. Meta’s Q3 profit collapsed to about $2.7 billion after a one-time tax charge of nearly $16 billion, even though revenue rose 26 %, and costs rose 33 %.

2. CapEx for 2025 was already raised to $70-72 billion, and Meta flagged “notably larger” capital spending for the next year to fuel its AI build-out.

3. Meta is reorganizing its AI efforts, hiring aggressively, and signaling it’s shifting from product-enhancement to infrastructure dominance—compute, chips, and data centers.

⚡ Why It Matters (OG lens):

When an infrastructure-heavy bet like this is placed, your competitive map and resource models—all of them—change. If the base layer shifts, you either build on the new base or you get boxed out.

⭐OG Rating:

This gets a 4 because the scale, ambition, and implications are massive and visible—but the payoff path is still uncertain, risks of over-capitalization are real, and it’s early to call the winner.

OG approved quote

What do you think?

TECHNOLOGY & BREAKTHROUGHS 🚀💡

👉 Nvidia Becomes Big Venture Backer for AI Startups

👉 OpenAI’s For-Profit Path Cleared

👉 Bill Gates: AI is the biggest technical thing ever in my lifetime

👉 How Greed Is Slashing The Tech Job Market

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◼ I am Olivier Gomez, best known as OG.

◼ I support executives and companies in navigating the Automation and AI landscape and getting tangible results from the technology.

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