Overview#
A deep dive into the current state of AI in 2026, covering what’s working, what’s hype and what developers should focus on.
Key Topics#
1. The Limits of LLMs#
LLMs still hallucinate. Benchmarks improve but real-world developer experience remains similar. Leading researchers like Yann LeCun are exploring alternatives to the transformer architecture. New approaches like recursive language models show promise for overcoming context window limitations.
2. Google’s Rising Dominance#
Google owns the full stack: competitive models (Gemini 3), custom hardware (TPUs), massive datasets and new protocols (A2A). Unlike OpenAI and Anthropic, they don’t depend on NVIDIA. The A2A protocol enables agent-to-agent communication going beyond MCP’s tool-calling focus.
3. DAGs vs Agents#
The debate continues. Anthropic’s guidance: start simple, optimize single LLM calls first. Use DAGs (deterministic workflows) when errors are costly. Use agents when there’s a human in the loop or mistakes are easily correctable. Always use-case specific.
4. Agentic Coding#
The biggest productivity multiplier for developers. LLMs excel at code due to clean training data and verifiable outputs. Tools like Claude Code and Cursor, combined with spec-driven development, are transforming how engineers work.
5. Context Engineering#
Beyond prompt engineering. The skill of getting the right context, at the right time, in front of the right model. The single most important skill for improving LLM applications.
6. Voice Interfaces#
A 10-year transition is beginning. Voice is 4-5x faster than typing. Silicon Valley is investing heavily in audio interfaces. Start practicing voice-based workflows now.
7. We’re Still Early#
Most companies are at AI maturity level zero. Understanding these concepts puts you in the top percentile. The fundamentals are stable: learn them now while the field is emerging.
Takeaways#
- Don’t wait for AGI - build with current tools
- Watch Google closely in 2026
- Match your architecture (DAG vs agent) to your use case
- Invest in agentic coding skills
- Context engineering > prompt engineering
- Prepare for voice-first interfaces
- You have a competitive advantage - use it
Resources#
- Anthropic: “Building Effective Agents”
- Anthropic: “Claude Code Best Practices for Agentic Coding”
- Yann LeCun’s UCE paper (December 2025)
- Google A2A Protocol documentation
Video script and timestamps available in the full project files.